20260910:导出报告优化v2版本

.claude/settings.local.json

@@ -68,7 +68,9 @@
       "Bash(node --check /Users/admin/IdeaProjects/fastbee/yack-web/src/api/iot/report.js)",
       "Bash(sed -i '' 's/direction\\)\\);$/direction\\)\\)\\);/' static_level/StaticLevelAnalyzer.java)",
       "Bash(sed -i '' 's/strainState, direction\\)\\);/strainState, direction\\)\\)\\);/' strain_gauge/StrainGaugeAnalyzer.java)",
-      "Bash(pip3 install *)"
+      "Bash(pip3 install *)",
+      "mcp__filesystem__read_file",
+      "mcp__filesystem__edit_file"
     ]
   }
 }

docs/fastbee-device-report-engine.md

@@ -205,19 +205,28 @@ services:
 ## 4.3 系统配置（oss_config 插入默认记录）
 
 ```sql
-INSERT INTO oss_config
+-- 先停用云 OSS 配置（存量占位符）
+UPDATE `oss_config` SET `status` = '1' WHERE `config_key` IN ('aliyun', 'qiniu');
+
+-- 插入 MinIO 默认配置（endpoint 为云服务器地址，供后端 S3 SDK 连接）
+INSERT IGNORE INTO `oss_config`
 (tenant_id, tenant_name, config_key, access_key, secret_key, bucket_name, prefix,
- endpoint, domain, is_https, region, access_policy, status, del_flag, create_time)
+ endpoint, domain, is_https, region, access_policy, status, del_flag, create_by, create_time, update_by, update_time, remark)
 VALUES
-(1, 'admin', 'minio', '<AccessKey>', '<SecretKey>', 'fastbee', 'report',
- 'http://<minio-host>:9000', '', 'N', '', '1', '0', '0', NOW());
+(1, 'admin', 'minio', 'supermeminio', 'minio20260909', 'fastbee', 'report',
+ 'http://47.1.28.77:9000', '', 'N', '', '0', '0', '0', 'admin', NOW(), 'admin', NOW(), 'MinIO默认存储');
 ```
 
 要点：
 
 - `status='0'` 设为默认，启动时 `OssApplicationRunner` 自动装载进 Redis（`sys_oss:default_config`）。
+- `endpoint` 为后端连接 MinIO 的 S3 API 地址，需确保端口 9000 在安全组/防火墙放行；若后端与 MinIO 同机部署，可改为 `http://127.0.0.1:9000`。
+- `domain` 为空时，`getUrl()` 返回 `http://<endpoint>/<bucketName>`；若配置了 CDN 或公网域名，可填入以生成更友好的 URL。
 - `PlatformType` 增加 `MINIO(5, "MinIO")`（仅用于管理页展示；实际路由走 `config_key`）。
-- bucket 权限 `access_policy=1`（public）时上传后可直接访问 URL；若不想公网直链，下载统一走后端代理。
+- `access_policy=0`（私有），报告下载统一走后端代理接口（`GET /iot/report/download/{reportNo}`），可校验权限和过期状态。
+- `bucket_name='fastbee'`：需在 MinIO 中提前创建此 bucket。
+- `endpoint` 需根据实际 MinIO 部署地址修改（如 `http://192.168.1.100:9000` 或生产域名）。
+- `bucket_name='fastbee'`：需在 MinIO 中提前创建此 bucket。
 
 ## 4.4 报告文件路径
 

fastbee-open-api/src/main/java/com/fastbee/controller/device/DeviceController.java

@@ -140,6 +140,25 @@ public class DeviceController extends BaseController {
         return AjaxResult.success(deviceService.selectUserDeviceStatistic(device));
     }
 
+    /**
+     * 查询树形设备列表（用于报表生成等场景，网关设备可展开显示子设备）
+     */
+    @PreAuthorize("@ss.hasAnyPermi('iot:device:list,iot:report:generate')")
+    @GetMapping("/treeList")
+    @ApiOperation("查询树形设备列表（网关可展开子设备）")
+    public AjaxResult treeList(Device device) {
+        LoginUser loginUser = getLoginUser();
+        if (null == loginUser.getDeptId()) {
+            device.setTenantId(loginUser.getUserId());
+        } else {
+            device.setDeptId(loginUser.getDeptId());
+        }
+        if (Objects.isNull(device.getTenantId())) {
+            device.setTenantId(loginUser.getUserId());
+        }
+        return AjaxResult.success(deviceService.selectDeviceTreeList(device));
+    }
+
     /**
      * 查询所有设备简短列表
      */

fastbee-open-api/src/main/java/com/fastbee/controller/report/ReportController.java

@@ -10,9 +10,9 @@ import com.fastbee.common.exception.ServiceException;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.oss.service.OssClient;
 import com.fastbee.oss.service.OssFactory;
-import com.fastbee.report.api.ReportEngine;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.api.ReportResult;
+import com.fastbee.report.executor.ReportAsyncExecutor;
 import com.fastbee.report.record.ReportRecord;
 import com.fastbee.report.record.ReportRecordQuery;
 import com.fastbee.report.record.ReportRecordService;
@@ -53,7 +53,7 @@ public class ReportController extends BaseController {
             "application/vnd.openxmlformats-officedocument.wordprocessingml.document";
 
     @Resource
-    private ReportEngine reportEngine;
+    private ReportAsyncExecutor reportAsyncExecutor;
 
     @Resource
     private ReportRecordService reportRecordService;
@@ -62,13 +62,34 @@ public class ReportController extends BaseController {
     private RedisCache redisCache;
 
     /**
-     * 生成并导出报表（V1 同步生成）
+     * 异步生成报表（V2 异步生成，立即返回报告编号）
      */
-    @ApiOperation("生成并导出报表")
+    @ApiOperation("异步生成报表")
     @PreAuthorize("@ss.hasPermi('iot:report:generate')")
     @PostMapping("/generate")
     public AjaxResult generate(@RequestBody ReportRequest request) {
-        ReportResult result = reportEngine.generate(request);
+        String reportNo = reportAsyncExecutor.submitAsyncTask(request);
+        return AjaxResult.success("报表生成任务已提交，请稍后查询状态", reportNo);
+    }
+
+    /**
+     * 查询报表生成状态
+     */
+    @ApiOperation("查询报表生成状态")
+    @PreAuthorize("@ss.hasAnyPermi('iot:report:list,iot:device:list')")
+    @GetMapping("/status/{reportNo}")
+    public AjaxResult status(@PathVariable("reportNo") String reportNo) {
+        ReportRecord record = reportRecordService.findByReportNo(reportNo);
+        if (record == null) {
+            throw new ServiceException("报告不存在");
+        }
+        ReportResult result = ReportResult.builder()
+                .reportNo(record.getReportNo())
+                .status(record.getStatus())
+                .fileName(record.getFileName())
+                .fileUrl(record.getFileUrl())
+                .expireTime(record.getExpireTime())
+                .build();
         return AjaxResult.success(result);
     }
 

fastbee-report/src/main/java/com/fastbee/report/analysis/PrimaryMetricResolver.java

@@ -0,0 +1,126 @@
+package com.fastbee.report.analysis;
+
+import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.core.ReportContext;
+import com.fastbee.report.data.MetricData;
+import org.springframework.stereotype.Component;
+
+import java.util.List;
+import java.util.Map;
+
+/**
+ * 主监测指标解析器（统一各 Analyzer 的"主指标"判定口径）
+ *
+ * <p>判定规则（按物模型列表顺序，保证稳定、不依赖时序数据返回顺序）：</p>
+ * <ol>
+ *   <li>排除辅助指标（角度/温度/电压/电量/信号/湿度等），辅助量不作为主监测指标；</li>
+ *   <li>优先返回名称或标识符命中核心关键词的物模型；</li>
+ *   <li>否则返回第一个有数据的非辅助指标；</li>
+ *   <li>再否则返回第一个非辅助指标；最后兜底第一个物模型。</li>
+ * </ol>
+ *
+ * @author FastBee
+ * @date 2026-09-10
+ */
+@Component
+public class PrimaryMetricResolver {
+
+    /** 辅助指标关键词（这些物模型不作为主监测指标） */
+    private static final String[] AUXILIARY_KEYWORDS = {
+            "角度", "angle", "温度", "temperature", "电压", "voltage",
+            "电量", "battery", "信号", "signal", "湿度", "humidity",
+            "电压值", "battery_voltage"
+    };
+
+    /**
+     * 解析主监测指标标识符
+     *
+     * @param context   报告上下文（提供物模型列表，顺序稳定）
+     * @param byIdentity 时序数据分组（用于判断是否有数据）
+     * @param keywords  核心关键词（如"位移"、"缝宽"、"轴力"）
+     * @return 主监测指标标识符；无物模型时返回 null
+     */
+    public String resolve(ReportContext context, Map<String, List<MetricData>> byIdentity, String... keywords) {
+        return resolve(context, byIdentity, false, keywords);
+    }
+
+    /**
+     * 解析主监测指标标识符
+     *
+     * @param allowAuxiliary 是否允许辅助指标（角度/温度等）作为主指标。
+     *                       倾角计、温度计等设备的主监测指标本身就是"角度/温度"，需传 true。
+     */
+    public String resolve(ReportContext context, Map<String, List<MetricData>> byIdentity,
+                          boolean allowAuxiliary, String... keywords) {
+        List<ThingsModel> models = context.getThingsModels();
+        if (models == null || models.isEmpty()) {
+            return byIdentity.isEmpty() ? null : byIdentity.keySet().iterator().next();
+        }
+
+        String firstWithData = null;
+        String firstAny = null;
+
+        for (ThingsModel model : models) {
+            String identity = model.getIdentifier();
+            if (identity == null || identity.trim().isEmpty()) {
+                continue;
+            }
+            String name = model.getModelName() == null ? identity : model.getModelName();
+            String lower = (name + " " + identity).toLowerCase();
+            boolean auxiliary = isAuxiliary(lower);
+
+            // 核心关键词命中优先（倾角计/温度计允许辅助指标作为主指标）
+            if (!auxiliary || allowAuxiliary) {
+                for (String keyword : keywords) {
+                    if (lower.contains(keyword.toLowerCase())) {
+                        return identity;
+                    }
+                }
+            }
+
+            // 辅助指标不参与"第一个"兜底
+            if (auxiliary && !allowAuxiliary) {
+                continue;
+            }
+
+            boolean hasData = byIdentity.containsKey(identity);
+            if (firstAny == null) {
+                firstAny = identity;
+            }
+            if (firstWithData == null && hasData) {
+                firstWithData = identity;
+            }
+        }
+
+        if (firstWithData != null) {
+            return firstWithData;
+        }
+        if (firstAny != null) {
+            return firstAny;
+        }
+        // 全部是辅助指标时，退回第一个物模型
+        return models.get(0).getIdentifier();
+    }
+
+    /**
+     * 是否为辅助指标（角度/温度/电压/电量/信号/湿度等）
+     */
+    public boolean isAuxiliary(String nameAndIdentifier) {
+        for (String keyword : AUXILIARY_KEYWORDS) {
+            if (nameAndIdentifier.contains(keyword)) {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    /**
+     * 是否需要生成独立图表（辅助指标中仅温度/电压等少量关注项可跳过）
+     */
+    public boolean isChartWorthy(String nameAndIdentifier) {
+        return !nameAndIdentifier.contains("电量")
+                && !nameAndIdentifier.contains("battery")
+                && !nameAndIdentifier.contains("信号")
+                && !nameAndIdentifier.contains("signal");
+    }
+}

fastbee-report/src/main/java/com/fastbee/report/analyzer/axial_force/AxialForceAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.axial_force;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class AxialForceAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.AXIAL_FORCE;
@@ -68,23 +77,41 @@ public class AxialForceAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class AxialForceAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "轴力", "应力", "force", "stress");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"力/stress/压力/拉力"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("force") || lower.contains("stress") || lower.contains("轴力") || lower.contains("应力") || lower.contains("压力") || lower.contains("拉力")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class AxialForceAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符，如红线/白线/绿线）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -151,6 +187,15 @@ public class AxialForceAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getCurrent().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "当前轴力占控制值比例：%.2f%%（控制值：%s%s）。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -166,24 +211,137 @@ public class AxialForceAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("轴力/应力时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String forceState = (statistics.getCurrent() != null && statistics.getCurrent().compareTo(BigDecimal.ZERO) >= 0) ? "受拉" : "受压";
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期轴力/应力监测数据显示：当前轴力为%s%s，处于%s状态，较初始值变化%s%s，变化速率为%s%s/天，轴力呈%s趋势。" +
+                        "统计期内最大轴力%s%s，最小轴力%s%s，平均轴力%s%s。",
+                statistics.getCurrent().toPlainString(), unit,
+                forceState,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("轴力呈增大趋势，需关注结构受力状态变化。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("轴力呈减小趋势，结构受力状态趋于稳定。");
+            } else {
+                advice.append("轴力变化稳定，结构受力状态正常。");
+            }
+        }
+
+        // 基于受力状态给出建议
+        String forceState = (statistics.getCurrent() != null && statistics.getCurrent().compareTo(BigDecimal.ZERO) >= 0) ? "受拉" : "受压";
+        if ("受拉".equals(forceState)) {
+            advice.append("当前结构处于受拉状态，需关注材料抗拉强度。");
+        } else {
+            advice.append("当前结构处于受压状态，需关注材料抗压强度。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即采取加固措施，并组织专业人员进行安全评估。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，准备应急预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/crack/CrackMeterAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.crack;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -34,7 +37,7 @@ import java.util.Objects;
 import java.util.stream.Collectors;
 
 /**
- * 裂缝计专项分析器（V1：当前/初始宽度、变化量、速率、趋势、预警、时程图）
+ * 裂缝计专项分析器（当前/初始宽度、变化量、速率、趋势、预警、时程图）
  *
  * @author FastBee
  * @date 2026-08-16
@@ -60,6 +63,12 @@ public class CrackMeterAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.CRACK_METER;
@@ -68,22 +77,41 @@ public class CrackMeterAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
+
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -95,31 +123,14 @@ public class CrackMeterAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "裂缝宽度", "缝宽", "width");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含“宽度/缝宽/width”，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("width") || lower.contains("缝宽") || lower.contains("宽度")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -128,6 +139,32 @@ public class CrackMeterAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -149,6 +186,15 @@ public class CrackMeterAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getCurrent().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "当前裂缝宽度占控制值比例：%.2f%%（控制值：%s%s）。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -164,26 +210,133 @@ public class CrackMeterAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("裂缝宽度时程曲线", metricName, unit, data);
-        // 使用统一键名 timeSeriesChart，兼容所有模板
-        result.getCharts().put("timeSeriesChart", png);
-        result.getCharts().put("crackTrend", png); // 兼容旧版模板
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期裂缝宽度监测数据显示：当前裂缝宽度为%s%s，较初始值变化%s%s，变化速率为%s%s/天，裂缝呈%s趋势。" +
+                        "统计期内最大裂缝宽度%s%s，最小裂缝宽度%s%s，平均裂缝宽度%s%s。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("裂缝宽度呈增大趋势，建议加强监测频率，关注裂缝发展速率。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("裂缝宽度呈减小趋势，结构状态趋于稳定。");
+            } else {
+                advice.append("裂缝宽度变化稳定，结构状态正常。");
+            }
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即采取加固措施，并组织专业人员进行安全评估。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，准备应急预案。");
+            }
+        }
+
+        // 基于变化量给出建议
+        BigDecimal absDelta = statistics.getDelta().abs();
+        if (absDelta.compareTo(new BigDecimal("1")) > 0) {
+            advice.append("裂缝变化量较大（>1mm），建议进行详细的结构安全评估。");
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/deep_displacement/DeepDisplacementAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.deep_displacement;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.DEEP_DISPLACEMENT;
@@ -68,22 +77,41 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
+
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -95,7 +123,11 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：按物模型顺序、排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity,
+                "深部位移", "位移", "displacement", "沉降", "settlement");
+        result.setPrimaryIdentifier(primaryIdentity);
+
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
@@ -103,21 +135,12 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
 
     /**
      * 主监测指标：优先名称/标识符含"位移/displacement/x/y/z"，否则取第一个有数据的指标
+     *
+     * @deprecated 由 {@link PrimaryMetricResolver} 统一解析，保留仅为兼容历史调用
      */
+    @Deprecated
     private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("displacement") || lower.contains("位移") || lower.contains("_x") || lower.contains("_y") || lower.contains("_z")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
+        return primaryMetricResolver.resolve(context, byIdentity, "位移", "displacement");
     }
 
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
@@ -128,13 +151,39 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符，如不同深度的位移测点）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
             conclusions.add(new Conclusion(seq++, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
         } else {
             conclusions.add(new Conclusion(seq++, String.format(
-                    "统计期内深部水平位移由 %s%s 变化至 %s%s，累计位移量 %s%s，位移方向为%s。",
+                    "统计期内深部位移由 %s%s 变化至 %s%s，累计位移量 %s%s，位移方向为%s。",
                     statistics.getInitial().toPlainString(), unit,
                     statistics.getCurrent().toPlainString(), unit,
                     statistics.getDelta().toPlainString(), unit,
@@ -148,6 +197,20 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getDelta().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "累计位移占控制值比例：%.2f%%（控制值：%s%s），需关注潜在滑动面发展趋势。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
+
+            // 位移速率评估
+            if (rate.compareTo(new BigDecimal("2")) > 0) {
+                conclusions.add(new Conclusion(seq++, "位移速率较大，需加密监测频次，必要时启动预警机制。"));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -163,24 +226,133 @@ public class DeepDisplacementAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("深部位移时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期深部位移监测数据显示：当前位移为%s%s，较初始值累计变化%s%s，位移速率为%s%s/天，位移方向呈%s趋势。" +
+                        "统计期内最大位移%s%s，最小位移%s%s，平均位移%s%s。土体内部变形监测正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("深部位移呈增大趋势，可能存在潜在滑动面发展，需结合地质资料分析滑移面位置与形态。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("深部位移呈减小趋势，土体变形趋于稳定。");
+            } else {
+                advice.append("深部位移变化稳定，土体内部变形正常。");
+            }
+        }
+
+        // 基于位移量级给出建议
+        if (statistics.getDelta().abs().compareTo(new BigDecimal("10")) > 0) {
+            advice.append("累计位移量较大，建议加密监测频率，结合测斜孔剖面图分析位移沿深度分布规律。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即启动应急预案，组织专业人员进行地质灾害评估，必要时采取加固措施。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加强巡视检查，准备应急物资，制定应急预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        // 补齐模板预留图表位（无数据时用空白图），避免模板标签缺失导致渲染异常
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/inclinometer/InclinometerAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.inclinometer;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class InclinometerAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.INCLINOMETER;
@@ -68,23 +77,41 @@ public class InclinometerAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class InclinometerAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, true, "倾角", "角度", "angle", "inclin");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"倾角/incline/angle/°"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("incline") || lower.contains("angle") || lower.contains("倾角") || lower.contains("角度")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class InclinometerAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符，如X轴/Y轴倾角）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -150,6 +186,20 @@ public class InclinometerAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getCurrent().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "当前倾角占控制值比例：%.2f%%（控制值：%s%s），需关注结构倾斜发展趋势。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
+
+            // 倾角安全评估
+            if (statistics.getCurrent().abs().compareTo(new BigDecimal("5")) > 0) {
+                conclusions.add(new Conclusion(seq++, "倾角较大，需评估结构倾斜风险，必要时采取纠偏措施。"));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -165,24 +215,132 @@ public class InclinometerAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("倾角时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期倾角监测数据显示：当前倾角为%s%s，较初始值变化%s%s，变化速率为%s%s/天，倾角呈%s趋势。" +
+                        "统计期内最大倾角%s%s，最小倾角%s%s，平均倾角%s%s。结构倾斜监测正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("倾角呈增大趋势，结构倾斜加剧，需分析倾斜原因与影响。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("倾角呈减小趋势，结构倾斜趋缓或回正。");
+            } else {
+                advice.append("倾角变化稳定，结构倾斜状态正常。");
+            }
+        }
+
+        // 基于倾角量级给出建议
+        if (statistics.getCurrent().abs().compareTo(new BigDecimal("3")) > 0) {
+            advice.append("当前倾角较大，建议结合建筑物使用年限、基础形式等因素综合评估结构安全性。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即评估结构安全性，必要时采取纠偏或加固措施。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，制定纠偏预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/rain_gauge/RainGaugeAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.rain_gauge;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class RainGaugeAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.RAIN_GAUGE;
@@ -68,23 +77,41 @@ public class RainGaugeAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class RainGaugeAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "雨量", "降雨", "降水量", "rain");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"雨量/rain/precipitation"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("rain") || lower.contains("雨量") || lower.contains("precipitation") || lower.contains("降水")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class RainGaugeAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -149,6 +185,20 @@ public class RainGaugeAnalyzer implements ReportAnalyzer {
                     rate.toPlainString(), unit,
                     statistics.getMax().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getDelta().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "累计降雨量占控制值比例：%.2f%%（控制值：%s%s），需关注降雨对边坡稳定性的影响。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
+
+            // 降雨强度评估
+            if (statistics.getDelta().abs().compareTo(new BigDecimal("50")) > 0) {
+                conclusions.add(new Conclusion(seq++, "统计期内降雨量较大，需加强巡视检查，关注排水设施运行状况。"));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -164,24 +214,130 @@ public class RainGaugeAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("降雨量时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期降雨监测数据显示：统计期内累计降雨量%s%s，平均日降雨量%s%s/天，降雨呈%s趋势。" +
+                        "统计期内最大单次降雨%s%s，平均降雨强度%s%s。环境气象监测正常。",
+                statistics.getDelta().abs().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("降雨呈增强趋势，需关注降雨对边坡稳定性、地下水位的影响。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("降雨呈减弱趋势，天气转好。");
+            } else {
+                advice.append("降雨强度平稳，气象条件正常。");
+            }
+        }
+
+        // 基于累计降雨量给出建议
+        if (statistics.getDelta().abs().compareTo(new BigDecimal("30")) > 0) {
+            advice.append("统计期内降雨量较大，建议结合地质资料分析降雨对边坡稳定性的影响，必要时加密监测频次。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即启动应急预案，加强巡视检查，做好防汛准备。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加强巡视检查，关注排水设施运行状况，准备应急物资。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/ranging_meter/RangingMeterAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.ranging_meter;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class RangingMeterAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.RANGING_METER;
@@ -68,23 +77,41 @@ public class RangingMeterAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class RangingMeterAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "距离", "位移", "distance");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"距离/distance/range"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("distance") || lower.contains("range") || lower.contains("距离") || lower.contains("测距")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class RangingMeterAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -150,6 +186,15 @@ public class RangingMeterAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getDelta().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "距离变化占控制值比例：%.2f%%（控制值：%s%s），需关注收敛变形趋势。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -165,24 +210,132 @@ public class RangingMeterAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("测距时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期测距监测数据显示：当前测距为%s%s，较初始值变化%s%s，变化速率为%s%s/天，测距呈%s趋势。" +
+                        "统计期内最大测距%s%s，最小测距%s%s，平均测距%s%s。变形监测正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("测距呈增大趋势，可能存在收敛变形，需分析变形原因与速率。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("测距呈减小趋势，可能存在挤压变形或测点位移，需结合其他监测数据分析。");
+            } else {
+                advice.append("测距变化稳定，变形正常。");
+            }
+        }
+
+        // 基于变化量级给出建议
+        if (statistics.getDelta().abs().compareTo(new BigDecimal("5")) > 0) {
+            advice.append("距离变化较大，建议分析变形原因，评估结构安全性。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即评估结构安全性，必要时采取加固措施。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，准备应急预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/static_level/StaticLevelAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.static_level;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class StaticLevelAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.STATIC_LEVEL;
@@ -68,23 +77,41 @@ public class StaticLevelAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class StaticLevelAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "沉降", "高程", "settlement");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"高程/elevation/level/沉降"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("elevation") || lower.contains("level") || lower.contains("高程") || lower.contains("沉降") || lower.contains("水准")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class StaticLevelAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit, result.getStatistics(), window);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多测点高程监测）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -150,6 +186,22 @@ public class StaticLevelAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal absDelta = statistics.getDelta().abs();
+                BigDecimal ratio = absDelta.divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "累计沉降量占控制值比例：%.2f%%（控制值：%s%s）。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
+
+            // 不均匀沉降评估（多测点场景）
+            String differentialSettlement = assessDifferentialSettlement(result.getStatistics());
+            if (StringUtils.isNotEmpty(differentialSettlement)) {
+                conclusions.add(new Conclusion(seq++, differentialSettlement));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -165,24 +217,235 @@ public class StaticLevelAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("静力水准时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        String settlementType = getSettlementType(statistics.getDelta());
+
+        return String.format(
+                "本期静力水准监测数据显示：当前高程为%s%s，较初始值变化%s%s（%s），变化速率为%s%s/天，结构呈%s趋势。" +
+                        "统计期内最大沉降量%s%s，最小沉降量%s%s，平均沉降量%s%s。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit, settlementType,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning,
+                                           String unit, Map<String, Statistics> allStatistics, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
+        }
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("结构呈持续下沉趋势，需关注沉降速率变化及周边环境影响因素。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("结构呈回弹隆起趋势，需关注回弹原因及对结构的影响。");
+            } else {
+                advice.append("沉降变化稳定，结构状态正常。");
+            }
+        }
+
+        // 基于沉降量给出建议
+        BigDecimal absDelta = statistics.getDelta().abs();
+        if (absDelta.compareTo(new BigDecimal("10")) > 0) {
+            advice.append("累计沉降量较大（>10mm），建议进行详细的地基稳定性评估。");
+        }
+
+        // 基于沉降速率给出建议
+        if (window != null) {
+            BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            if (rate != null && rate.compareTo(new BigDecimal("2")) > 0) {
+                advice.append(String.format("沉降速率较快（%.2fmm/天），需加密监测频率。", rate.doubleValue()));
+            }
+        }
+
+        // 不均匀沉降分析
+        if (allStatistics != null && allStatistics.size() > 1) {
+            String differentialAdvice = analyzeDifferentialSettlement(allStatistics);
+            if (StringUtils.isNotEmpty(differentialAdvice)) {
+                advice.append(differentialAdvice);
+            }
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即采取地基加固措施，并组织专业人员进行安全评估。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，制定应急预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多测点高程监测）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    /**
+     * 评估不均匀沉降（多测点场景）
+     */
+    private String assessDifferentialSettlement(Map<String, Statistics> allStatistics) {
+        if (allStatistics == null || allStatistics.size() < 2) {
             return null;
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        BigDecimal maxDelta = null;
+        BigDecimal minDelta = null;
+
+        for (Statistics stats : allStatistics.values()) {
+            if (stats == null || stats.getDelta() == null) {
+                continue;
+            }
+            if (maxDelta == null || stats.getDelta().abs().compareTo(maxDelta) > 0) {
+                maxDelta = stats.getDelta().abs();
+            }
+            if (minDelta == null || stats.getDelta().abs().compareTo(minDelta) < 0) {
+                minDelta = stats.getDelta().abs();
+            }
+        }
+
+        if (maxDelta != null && minDelta != null) {
+            BigDecimal differential = maxDelta.subtract(minDelta);
+            if (differential.compareTo(new BigDecimal("5")) > 0) {
+                return String.format("存在不均匀沉降，测点间最大沉降差为%s%s，建议关注结构整体稳定性。",
+                        differential.toPlainString(), "mm");
+            }
+        }
+
+        return null;
+    }
+
+    /**
+     * 分析不均匀沉降（用于专业建议）
+     */
+    private String analyzeDifferentialSettlement(Map<String, Statistics> allStatistics) {
+        if (allStatistics == null || allStatistics.size() < 2) {
+            return "";
+        }
+
+        BigDecimal maxDelta = null;
+        BigDecimal minDelta = null;
+
+        for (Statistics stats : allStatistics.values()) {
+            if (stats == null || stats.getDelta() == null) {
+                continue;
+            }
+            if (maxDelta == null || stats.getDelta().abs().compareTo(maxDelta) > 0) {
+                maxDelta = stats.getDelta().abs();
+            }
+            if (minDelta == null || stats.getDelta().abs().compareTo(minDelta) < 0) {
+                minDelta = stats.getDelta().abs();
+            }
+        }
+
+        if (maxDelta != null && minDelta != null) {
+            BigDecimal differential = maxDelta.subtract(minDelta);
+            if (differential.compareTo(new BigDecimal("5")) > 0) {
+                return "存在明显不均匀沉降现象，需关注对结构整体稳定性的影响。";
+            }
+        }
+
+        return "";
+    }
+
+    /**
+     * 判断沉降类型
+     */
+    private String getSettlementType(BigDecimal delta) {
+        if (delta == null) {
+            return "待分析";
+        }
+        if (delta.compareTo(BigDecimal.ZERO) > 0) {
+            return "下沉";
+        } else if (delta.compareTo(BigDecimal.ZERO) < 0) {
+            return "隆起";
+        }
+        return "稳定";
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/strain_gauge/StrainGaugeAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.strain_gauge;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class StrainGaugeAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.STRAIN_GAUGE;
@@ -68,23 +77,41 @@ public class StrainGaugeAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class StrainGaugeAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "应变", "strain");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"应变/strain/με"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("strain") || lower.contains("应变") || lower.contains("με")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class StrainGaugeAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -151,6 +187,15 @@ public class StrainGaugeAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getCurrent().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "当前应变占控制值比例：%.2f%%（控制值：%s%s），需关注材料强度储备。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -166,24 +211,137 @@ public class StrainGaugeAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("应变时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String strainState = (statistics.getCurrent() != null && statistics.getCurrent().compareTo(BigDecimal.ZERO) >= 0) ? "拉应变" : "压应变";
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期应变监测数据显示：当前应变为%s%s，处于%s状态，较初始值变化%s%s，应变速率为%s%s/天，应变呈%s趋势。" +
+                        "统计期内最大应变%s%s，最小应变%s%s，平均应变%s%s。结构变形监测正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                strainState,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于应变状态给出建议
+        String strainState = (statistics.getCurrent() != null && statistics.getCurrent().compareTo(BigDecimal.ZERO) >= 0) ? "拉应变" : "压应变";
+        if ("拉应变".equals(strainState)) {
+            advice.append("当前结构处于拉应变状态，需关注材料抗拉强度。");
+        } else {
+            advice.append("当前结构处于压应变状态，需关注材料抗压强度和稳定性。");
+        }
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("应变呈增大趋势，结构变形加剧，需评估应力重分布影响。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("应变呈减小趋势，结构变形趋于稳定。");
+            } else {
+                advice.append("应变变化稳定，结构变形正常。");
+            }
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即评估结构安全性，必要时采取加固或卸载措施。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，准备应急预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/thermometer/ThermometerAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.thermometer;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class ThermometerAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.THERMOMETER;
@@ -68,23 +77,41 @@ public class ThermometerAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class ThermometerAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, true, "温度", "temperature");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"温度/temp/temperature/℃"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("temp") || lower.contains("温度") || lower.contains("temperature")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class ThermometerAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -150,6 +186,21 @@ public class ThermometerAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getCurrent().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "当前温度占控制值比例：%.2f%%（控制值：%s%s），需关注温度对结构的影响。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
+
+            // 温度异常评估
+            BigDecimal tempRange = statistics.getMax().subtract(statistics.getMin());
+            if (tempRange.compareTo(new BigDecimal("20")) > 0) {
+                conclusions.add(new Conclusion(seq++, "统计期内温度波动较大，需关注温差对结构变形的影响。"));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -165,24 +216,133 @@ public class ThermometerAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("温度时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期温度监测数据显示：当前温度为%s%s，较初始值变化%s%s，温度变化速率为%s%s/天，温度呈%s趋势。" +
+                        "统计期内最高温度%s%s，最低温度%s%s，平均温度%s%s。环境温度监测正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("温度呈上升趋势，需关注高温对材料性能和结构变形的影响。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("温度呈下降趋势，需关注低温对材料性能和结构变形的影响。");
+            } else {
+                advice.append("温度变化平稳，环境温度正常。");
+            }
+        }
+
+        // 基于温差给出建议
+        BigDecimal tempRange = statistics.getMax().subtract(statistics.getMin());
+        if (tempRange.compareTo(new BigDecimal("15")) > 0) {
+            advice.append("统计期内温差较大，需分析温差对结构变形的影响，必要时进行温度修正。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即评估温度异常对结构安全的影响，必要时采取保护措施。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加强温度监测，分析温度异常原因。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/vibrating_wire/VibratingWireAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.vibrating_wire;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class VibratingWireAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.VIBRATING_WIRE;
@@ -68,23 +77,41 @@ public class VibratingWireAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class VibratingWireAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "频率", "frequency");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"频率/frequency/Hz"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("frequency") || lower.contains("频率") || lower.contains("hz")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class VibratingWireAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -150,6 +186,15 @@ public class VibratingWireAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getDelta().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "频率变化占控制值比例：%.2f%%（控制值：%s%s），需结合温度补偿分析应力状态。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -165,24 +210,132 @@ public class VibratingWireAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("振弦频率时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期振弦监测数据显示：当前频率为%s%s，较初始值变化%s%s，频率变化速率为%s%s/天，频率呈%s趋势。" +
+                        "统计期内最大频率%s%s，最小频率%s%s，平均频率%s%s。振弦传感器工作正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("振弦频率呈增大趋势，应力状态发生变化，需结合温度补偿计算实际应力值。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("振弦频率呈减小趋势，结构应力状态趋于松弛。");
+            } else {
+                advice.append("振弦频率变化稳定，结构应力状态正常。");
+            }
+        }
+
+        // 基于频率变化量级给出建议
+        if (statistics.getDelta().abs().compareTo(new BigDecimal("50")) > 0) {
+            advice.append("频率变化较大，建议检查传感器零点漂移，进行温度补偿修正。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即校验传感器状态，分析应力超限原因，必要时采取加固措施。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加密监测频率，准备应急预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/analyzer/water_level/WaterLevelAnalyzer.java

@@ -3,6 +3,7 @@ package com.fastbee.report.analyzer.water_level;
 import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.common.utils.StringUtils;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.report.analysis.PrimaryMetricResolver;
 import com.fastbee.report.analysis.QualityAnalyzer;
 import com.fastbee.report.analysis.RateCalculator;
 import com.fastbee.report.analysis.StatisticsCalculator;
@@ -11,10 +12,12 @@ import com.fastbee.report.analysis.WarningAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.api.ReportRequest;
 import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.chart.MetricChartBuilder;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.data.MetricData;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
@@ -60,6 +63,12 @@ public class WaterLevelAnalyzer implements ReportAnalyzer {
     @Resource
     private ChartGenerator chartGenerator;
 
+    @Resource
+    private PrimaryMetricResolver primaryMetricResolver;
+
+    @Resource
+    private MetricChartBuilder metricChartBuilder;
+
     @Override
     public boolean supports(MonitorCategory category) {
         return category == MonitorCategory.WATER_LEVEL;
@@ -68,23 +77,41 @@ public class WaterLevelAnalyzer implements ReportAnalyzer {
     @Override
     public AnalysisResult analyze(ReportContext context, ReportRequest request) {
         AnalysisResult result = new AnalysisResult();
+
+        // 1. 按物模型标识符分组历史数据
         Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
                 .filter(d -> d.getIdentity() != null)
                 .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
 
-        if (byIdentity.isEmpty()) {
-            result.getConclusions().add(new Conclusion(1, "统计期内无有效监测数据，请检查设备上报状态与时间范围。"));
+        // 2. 获取所有监测物模型（即使没有数据也要显示）
+        Map<String, ThingsModel> allModels = context.getThingsModels().stream()
+                .filter(m -> m.getIdentifier() != null)
+                .collect(Collectors.toMap(ThingsModel::getIdentifier, m -> m, (o, n) -> n, LinkedHashMap::new));
+
+        if (allModels.isEmpty()) {
+            result.getConclusions().add(new Conclusion(1, "设备未配置监测物模型，请联系管理员配置。"));
             return result;
         }
 
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
+        // 3. 为每个物模型生成统计数据（包括无数据的物模型）
+        for (Map.Entry<String, ThingsModel> entry : allModels.entrySet()) {
             String identity = entry.getKey();
-            List<MetricData> data = entry.getValue();
+            ThingsModel model = entry.getValue();
+            List<MetricData> data = byIdentity.getOrDefault(identity, new ArrayList<>());
 
             ReportThreshold threshold = context.getThresholds().get(identity);
             BigDecimal controlValue = threshold == null ? null : threshold.getControlValue();
 
             Statistics statistics = statisticsCalculator.calculate(data);
+            // 补充物模型信息（确保即使无数据也有 modelName 和 unit）
+            if (statistics.getModelName() == null || statistics.getModelName().isEmpty()) {
+                statistics.setModelName(model.getModelName());
+            }
+            if (statistics.getUnit() == null || statistics.getUnit().isEmpty()) {
+                statistics.setUnit(model.getUnit());
+            }
+            statistics.setIdentifier(identity);
+
             TrendAnalysis trend = trendAnalyzer.analyze(data);
             QualityAnalysis quality = qualityAnalyzer.analyze(data, context.getTimeWindow(), controlValue);
             WarningAnalysis warning = warningAnalyzer.analyze(
@@ -96,31 +123,14 @@ public class WaterLevelAnalyzer implements ReportAnalyzer {
             result.getWarnings().put(identity, warning);
         }
 
-        String primaryIdentity = resolvePrimaryIdentity(byIdentity, context);
+        // 统一主指标口径：优先名称/标识符命中关键词的物模型，排除角度/温度/电压等辅助量
+        String primaryIdentity = primaryMetricResolver.resolve(context, byIdentity, false, "水位", "液位", "water");
+        result.setPrimaryIdentifier(primaryIdentity);
         buildConclusions(result, context, primaryIdentity);
         buildChart(result, context, primaryIdentity);
         return result;
     }
 
-    /**
-     * 主监测指标：优先名称/标识符含"水位/level/water/depth"，否则取第一个有数据的指标
-     */
-    private String resolvePrimaryIdentity(Map<String, List<MetricData>> byIdentity, ReportContext context) {
-        String fallback = null;
-        for (Map.Entry<String, List<MetricData>> entry : byIdentity.entrySet()) {
-            ThingsModel model = findModel(context, entry.getKey());
-            String name = model == null ? entry.getKey() : (model.getModelName() == null ? entry.getKey() : model.getModelName());
-            String lower = (name + entry.getKey()).toLowerCase();
-            if (lower.contains("level") || lower.contains("water") || lower.contains("水位") || lower.contains("水深") || lower.contains("depth")) {
-                return entry.getKey();
-            }
-            if (fallback == null && !entry.getValue().isEmpty()) {
-                fallback = entry.getKey();
-            }
-        }
-        return fallback == null ? byIdentity.keySet().iterator().next() : fallback;
-    }
-
     private void buildConclusions(AnalysisResult result, ReportContext context, String primaryIdentity) {
         Statistics statistics = result.getStatistics().get(primaryIdentity);
         TrendAnalysis trend = result.getTrends().get(primaryIdentity);
@@ -129,6 +139,32 @@ public class WaterLevelAnalyzer implements ReportAnalyzer {
         TimeWindow window = context.getTimeWindow();
         String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
 
+        // 生成项目概况总结
+        String summary = buildSummary(statistics, trend, unit, window);
+        result.setSummary(summary);
+
+        // 生成专业分析建议
+        String advice = buildProfessionalAdvice(statistics, trend, warning, unit);
+        result.setProfessionalAdvice(advice);
+
+        // 设置安全评估
+        if (warning != null) {
+            result.setSafetyLevel(convertWarningToSafetyLevel(warning.getStatus()));
+            result.setSafetyDescription(warning.getDescription());
+        }
+
+        // 设置控制值
+        ReportThreshold threshold = context.getThresholds().get(primaryIdentity);
+        if (threshold != null && threshold.getControlValue() != null) {
+            result.setControlValue(threshold.getControlValue());
+            result.setControlValueUnit(threshold.getUnit());
+        }
+
+        // 组装多测点数据（支持多物模型标识符）
+        List<MetricPointData> metricPoints = buildMetricPoints(result, context);
+        result.setMetricPoints(metricPoints);
+
+        // 生成详细结论
         List<Conclusion> conclusions = new ArrayList<>();
         int seq = 1;
         if (statistics == null || statistics.getCount() == 0) {
@@ -150,6 +186,15 @@ public class WaterLevelAnalyzer implements ReportAnalyzer {
                     statistics.getMax().toPlainString(), unit,
                     statistics.getMin().toPlainString(), unit,
                     statistics.getAvg().toPlainString(), unit)));
+
+            // 添加控制值对比结论
+            if (result.getControlValue() != null && result.getControlValue().compareTo(BigDecimal.ZERO) != 0) {
+                BigDecimal ratio = statistics.getDelta().abs().divide(result.getControlValue(), 4, BigDecimal.ROUND_HALF_UP)
+                        .multiply(new BigDecimal("100"));
+                conclusions.add(new Conclusion(seq++, String.format(
+                        "水位变化占控制值比例：%.2f%%（控制值：%s%s），需关注渗流场变化。",
+                        ratio.doubleValue(), result.getControlValue().toPlainString(), result.getControlValueUnit())));
+            }
         }
 
         if (trend != null && StringUtils.isNotEmpty(trend.getDescription())) {
@@ -165,24 +210,132 @@ public class WaterLevelAnalyzer implements ReportAnalyzer {
         result.setConclusions(conclusions);
     }
 
-    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
-        List<MetricData> data = context.getMetricDataList().stream()
-                .filter(d -> Objects.equals(d.getIdentity(), primaryIdentity))
-                .collect(Collectors.toList());
-        Statistics statistics = result.getStatistics().get(primaryIdentity);
-        String metricName = statistics == null ? primaryIdentity : statistics.getModelName();
-        String unit = statistics == null ? "" : (statistics.getUnit() == null ? "" : statistics.getUnit());
-        byte[] png = chartGenerator.timeSeriesChart("水位时程曲线", metricName, unit, data);
-        result.getCharts().put("timeSeriesChart", png);
+    /**
+     * 生成项目概况总结
+     */
+    private String buildSummary(Statistics statistics, TrendAnalysis trend, String unit, TimeWindow window) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "统计期内无有效监测数据。";
+        }
+
+        String direction = trend == null ? "待分析" : directionText(trend.getDirection());
+        BigDecimal rate = rateCalculator.ratePerDay(statistics,
+                Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+
+        return String.format(
+                "本期水位监测数据显示：当前水位为%s%s，较初始值变化%s%s，水位变化速率为%s%s/天，水位呈%s趋势。" +
+                        "统计期内最高水位%s%s，最低水位%s%s，平均水位%s%s。渗流监测正常。",
+                statistics.getCurrent().toPlainString(), unit,
+                statistics.getDelta().toPlainString(), unit,
+                rate.toPlainString(), unit,
+                direction,
+                statistics.getMax().toPlainString(), unit,
+                statistics.getMin().toPlainString(), unit,
+                statistics.getAvg().toPlainString(), unit
+        );
     }
 
-    private ThingsModel findModel(ReportContext context, String identity) {
-        if (context.getThingsModels() == null) {
-            return null;
+    /**
+     * 生成专业分析建议
+     */
+    private String buildProfessionalAdvice(Statistics statistics, TrendAnalysis trend, WarningAnalysis warning, String unit) {
+        if (statistics == null || statistics.getCount() == 0) {
+            return "建议检查设备上报状态，确保数据采集正常。";
         }
-        return context.getThingsModels().stream()
-                .filter(m -> Objects.equals(m.getIdentifier(), identity))
-                .findFirst().orElse(null);
+
+        StringBuilder advice = new StringBuilder();
+        advice.append("专业分析：");
+
+        // 基于趋势方向给出建议
+        if (trend != null) {
+            if (TrendAnalysis.DIRECTION_UP.equals(trend.getDirection())) {
+                advice.append("水位呈上升趋势，需关注浸润线位置变化，评估渗流场稳定性。");
+            } else if (TrendAnalysis.DIRECTION_DOWN.equals(trend.getDirection())) {
+                advice.append("水位呈下降趋势，渗流场趋于稳定。");
+            } else {
+                advice.append("水位变化平稳，渗流场稳定。");
+            }
+        }
+
+        // 基于水位变化量级给出建议
+        if (statistics.getDelta().abs().compareTo(new BigDecimal("1")) > 0) {
+            advice.append("水位变化幅度较大，建议分析水位变化原因（降雨、抽排水等），评估对边坡稳定性的影响。");
+        }
+
+        // 基于预警状态给出建议
+        if (warning != null) {
+            if (WarningAnalysis.STATUS_ALARM.equals(warning.getStatus())) {
+                advice.append("当前处于报警状态，建议立即启动排水措施，组织专业人员进行渗流安全评估。");
+            } else if (WarningAnalysis.STATUS_WARNING.equals(warning.getStatus())) {
+                advice.append("当前处于预警状态，建议加强巡视检查，准备应急排水预案。");
+            }
+        }
+
+        return advice.toString();
+    }
+
+    /**
+     * 将预警状态转换为安全等级
+     */
+    private String convertWarningToSafetyLevel(String warningStatus) {
+        if (WarningAnalysis.STATUS_ALARM.equals(warningStatus)) {
+            return "DANGER";
+        } else if (WarningAnalysis.STATUS_WARNING.equals(warningStatus)) {
+            return "WARNING";
+        }
+        return "SAFE";
+    }
+
+    /**
+     * 组装多测点数据（支持多物模型标识符）
+     */
+    private List<MetricPointData> buildMetricPoints(AnalysisResult result, ReportContext context) {
+        List<MetricPointData> points = new ArrayList<>();
+
+        for (Map.Entry<String, Statistics> entry : result.getStatistics().entrySet()) {
+            String identity = entry.getKey();
+            Statistics stats = entry.getValue();
+
+            MetricPointData point = MetricPointData.builder()
+                    .identifier(identity)
+                    .modelName(stats.getModelName())
+                    .initialValue(stats.getInitial())
+                    .initialUnit(stats.getUnit())
+                    .currentValue(stats.getCurrent())
+                    .currentUnit(stats.getUnit())
+                    .changeValue(stats.getDelta())
+                    .changeUnit(stats.getUnit())
+                    .maxValue(stats.getMax())
+                    .minValue(stats.getMin())
+                    .avgValue(stats.getAvg())
+                    .build();
+
+            // 设置预警状态
+            WarningAnalysis warning = result.getWarnings().get(identity);
+            if (warning != null) {
+                point.setWarningStatus(warning.getStatus());
+            }
+
+            // 计算变化速率
+            TimeWindow window = context.getTimeWindow();
+            BigDecimal rate = rateCalculator.ratePerDay(stats,
+                    Duration.between(window.getStartTime(), window.getEndTime()).getSeconds());
+            point.setChangeRate(rate);
+            point.setRateUnit(stats.getUnit() + "/天");
+
+            points.add(point);
+        }
+
+        return points;
+    }
+
+    private void buildChart(AnalysisResult result, ReportContext context, String primaryIdentity) {
+        // 主指标单图 + 其余指标按单位分组多曲线图（展示所有物模型数据）
+        Map<String, List<MetricData>> byIdentity = context.getMetricDataList().stream()
+                .filter(d -> d.getIdentity() != null)
+                .collect(Collectors.groupingBy(MetricData::getIdentity, LinkedHashMap::new, Collectors.toList()));
+        Map<String, byte[]> charts = metricChartBuilder.build(result.getStatistics(), primaryIdentity, byIdentity);
+        result.getCharts().putAll(metricChartBuilder.fillPlaceholders(charts));
     }
 
     private String statusText(String status) {

fastbee-report/src/main/java/com/fastbee/report/api/ReportEngine.java

@@ -1,15 +0,0 @@
-package com.fastbee.report.api;
-
-/**
- * 报告引擎入口
- *
- * @author FastBee
- * @date 2026-08-16
- */
-public interface ReportEngine {
-
-    /**
-     * 生成报告（V1 同步生成，返回报告编号 / 文件地址 / 过期时间）
-     */
-    ReportResult generate(ReportRequest request);
-}

fastbee-report/src/main/java/com/fastbee/report/api/ReportRequest.java

@@ -35,9 +35,9 @@ public class ReportRequest implements Serializable {
     @ApiModelProperty("周期锚点日期 yyyy-MM-dd（默认今天，仅周期预设时使用）")
     private String anchorDate;
 
-    @ApiModelProperty("模板编码，如 DEVICE_CRACK_METER_V1")
+    @ApiModelProperty("模板编码，如 DEVICE_CRACK_METER_V2")
     private String templateCode;
 
-    @ApiModelProperty("导出格式（V1 仅支持 WORD）")
+    @ApiModelProperty("导出格式（目前仅支持 WORD）")
     private String format;
 }

fastbee-report/src/main/java/com/fastbee/report/chart/ChartGenerator.java

@@ -18,6 +18,7 @@ import java.io.ByteArrayOutputStream;
 import java.io.IOException;
 import java.util.Comparator;
 import java.util.List;
+import java.util.Map;
 
 /**
  * Java 图表生成器（JFreeChart → PNG，禁止前端生成图表回传后端）
@@ -77,4 +78,58 @@ public class ChartGenerator {
         }
         return out.toByteArray();
     }
+
+    /**
+     * 生成多曲线时程图 PNG（同名单位的多指标合并展示）
+     *
+     * @param title     图表标题
+     * @param unit      纵轴单位
+     * @param seriesMap 曲线名 → 时序数据（保持插入顺序）
+     */
+    public byte[] multiSeriesChart(String title, String unit, Map<String, List<MetricData>> seriesMap) {
+        TimeSeriesCollection dataset = new TimeSeriesCollection();
+        if (seriesMap != null) {
+            for (Map.Entry<String, List<MetricData>> entry : seriesMap.entrySet()) {
+                TimeSeries series = new TimeSeries(entry.getKey());
+                if (entry.getValue() != null) {
+                    entry.getValue().stream()
+                            .filter(d -> d.getTime() != null && d.getNumericValue() != null)
+                            .sorted(Comparator.comparing(MetricData::getTime))
+                            .forEach(d -> series.add(new Millisecond(d.getTime()), d.getNumericValue().doubleValue()));
+                }
+                dataset.addSeries(series);
+            }
+        }
+
+        JFreeChart chart = ChartFactory.createTimeSeriesChart(
+                title, "时间", unit == null ? "数值" : unit, dataset,
+                true, true, false);
+        chart.setBackgroundPaint(Color.WHITE);
+        chart.getTitle().setFont(CN_TITLE_FONT);
+
+        XYPlot plot = chart.getXYPlot();
+        plot.setBackgroundPaint(Color.WHITE);
+        plot.setDomainGridlinePaint(Color.LIGHT_GRAY);
+        plot.setRangeGridlinePaint(Color.LIGHT_GRAY);
+        plot.getDomainAxis().setLabelFont(CN_FONT);
+        plot.getDomainAxis().setTickLabelFont(new Font("SansSerif", Font.PLAIN, 11));
+        plot.getRangeAxis().setLabelFont(CN_FONT);
+        plot.getRangeAxis().setTickLabelFont(new Font("SansSerif", Font.PLAIN, 11));
+        chart.getLegend().setItemFont(CN_FONT);
+
+        ByteArrayOutputStream out = new ByteArrayOutputStream();
+        try {
+            ChartUtils.writeChartAsPNG(out, chart, 900, 360);
+        } catch (IOException e) {
+            throw new IllegalStateException("图表生成失败", e);
+        }
+        return out.toByteArray();
+    }
+
+    /**
+     * 生成空白占位图（无数据时保持图文排版稳定）
+     */
+    public byte[] blankChart(String title) {
+        return multiSeriesChart(title, null, new java.util.LinkedHashMap<>());
+    }
 }

fastbee-report/src/main/java/com/fastbee/report/chart/MetricChartBuilder.java

@@ -0,0 +1,108 @@
+package com.fastbee.report.chart;
+
+import com.fastbee.report.data.MetricData;
+import com.fastbee.report.model.Statistics;
+import org.springframework.stereotype.Component;
+
+import javax.annotation.Resource;
+import java.util.ArrayList;
+import java.util.LinkedHashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * 监测指标图表构建器（主指标单图 + 其余指标按单位分组多曲线图）
+ *
+ * <p>约定 charts 的 key：</p>
+ * <ul>
+ *   <li>{@code timeSeriesChart}：主监测指标时程曲线（与模板兼容）</li>
+ *   <li>{@code chart2} / {@code chart3}：其余指标按单位分组的时程曲线（最多 2 组）</li>
+ * </ul>
+ *
+ * @author FastBee
+ * @date 2026-09-10
+ */
+@Component
+public class MetricChartBuilder {
+
+    /** 附图最大数量（模板预留 chart2 / chart3 两个位置） */
+    private static final int MAX_EXTRA_CHARTS = 2;
+
+    @Resource
+    private ChartGenerator chartGenerator;
+
+    /**
+     * 构建图表集合
+     *
+     * @param statisticsMap   全部指标统计
+     * @param primaryIdentity 主指标标识符
+     * @param byIdentity      指标 → 时序数据
+     * @return key 为 timeSeriesChart / chart2 / chart3 的 PNG 映射
+     */
+    public Map<String, byte[]> build(Map<String, Statistics> statisticsMap,
+                                     String primaryIdentity,
+                                     Map<String, List<MetricData>> byIdentity) {
+        Map<String, byte[]> charts = new LinkedHashMap<>();
+        if (statisticsMap == null || statisticsMap.isEmpty()) {
+            return charts;
+        }
+
+        // 1. 主监测指标：单独一张图
+        Statistics primary = statisticsMap.get(primaryIdentity);
+        if (primary == null) {
+            primary = statisticsMap.values().iterator().next();
+            primaryIdentity = primary.getIdentifier();
+        }
+        String primaryUnit = primary.getUnit() == null ? "" : primary.getUnit();
+        String primaryName = primary.getModelName() == null ? primaryIdentity : primary.getModelName();
+        charts.put("timeSeriesChart", chartGenerator.timeSeriesChart(
+                primaryName + "时程曲线", primaryName, primaryUnit,
+                byIdentity.getOrDefault(primaryIdentity, new ArrayList<>())));
+
+        // 2. 其余指标：按单位分组，同单位合并为一张多曲线图
+        Map<String, LinkedHashMap<String, List<MetricData>>> groupedByUnit = new LinkedHashMap<>();
+        for (Map.Entry<String, Statistics> entry : statisticsMap.entrySet()) {
+            String identity = entry.getKey();
+            if (identity.equals(primaryIdentity)) {
+                continue;
+            }
+            Statistics statistics = entry.getValue();
+            // 无数据的指标不生成图表
+            if (statistics == null || statistics.getCount() == 0) {
+                continue;
+            }
+            String unit = statistics.getUnit() == null ? "" : statistics.getUnit();
+            String name = statistics.getModelName() == null ? identity : statistics.getModelName();
+            groupedByUnit.computeIfAbsent(unit, k -> new LinkedHashMap<>())
+                    .put(name, byIdentity.getOrDefault(identity, new ArrayList<>()));
+        }
+
+        int index = 2;
+        for (Map.Entry<String, LinkedHashMap<String, List<MetricData>>> entry : groupedByUnit.entrySet()) {
+            if (index > MAX_EXTRA_CHARTS + 1) {
+                break;
+            }
+            String unit = entry.getKey();
+            String title = entry.getValue().keySet().iterator().next() + "等指标时程曲线";
+            if (entry.getValue().size() == 1) {
+                title = entry.getValue().keySet().iterator().next() + "时程曲线";
+            }
+            charts.put("chart" + index,
+                    chartGenerator.multiSeriesChart(title, unit, entry.getValue()));
+            index++;
+        }
+        return charts;
+    }
+
+    /**
+     * 补齐模板预留的图表位，避免模板标签无对应数据导致渲染异常
+     */
+    public Map<String, byte[]> fillPlaceholders(Map<String, byte[]> charts) {
+        Map<String, byte[]> result = new LinkedHashMap<>(charts);
+        for (int i = 2; i <= MAX_EXTRA_CHARTS + 1; i++) {
+            String key = "chart" + i;
+            result.putIfAbsent(key, chartGenerator.blankChart("暂无数据"));
+        }
+        return result;
+    }
+}

fastbee-report/src/main/java/com/fastbee/report/core/ReportAssembler.java

@@ -8,6 +8,8 @@ import com.fastbee.report.model.ReportModel;
 import com.fastbee.report.model.Statistics;
 import org.springframework.stereotype.Component;
 
+import java.util.UUID;
+
 /**
  * 报告模型装配器：AnalysisResult + 上下文 → ReportModel
  *
@@ -18,18 +20,29 @@ import org.springframework.stereotype.Component;
 public class ReportAssembler {
 
     public ReportModel assemble(ReportContext context, AnalysisResult analysis) {
-        String templateCode = StringUtils.isNotEmpty(context.getRequest().getTemplateCode())
-                ? context.getRequest().getTemplateCode()
-                : "DEVICE_" + context.getCategory().name() + "_V1";
+        // 默认使用专业模版，如未配置 templateCode 则根据监测分类自动选择
+        String templateCode = "DEVICE_" + context.getCategory().name() + "_V2";
 
         ReportPeriod period = context.getTimeWindow().getPeriod();
         String serialNumber = context.getDevice().getSerialNumber();
         if (StringUtils.isEmpty(serialNumber)) {
             serialNumber = String.valueOf(context.getDevice().getDeviceId());
         }
-        String fileName = serialNumber + "-" + period.getDesc() + "-监测分析报告.docx";
+        // 末尾追加随机后缀，避免同一设备同一周期重复导出时文件名相同
+        String randomSuffix = UUID.randomUUID().toString().replace("-", "").substring(0, 6);
+        String fileName = context.getCategory().getDesc() + "-监测分析报告-" + randomSuffix + ".docx";
 
-        Statistics primary = analysis.getStatistics().values().stream().findFirst().orElse(null);
+        // 主监测指标：优先使用 Analyzer 解析的 primaryIdentifier（与概况/结论/统计指标口径一致）
+        Statistics primary = null;
+        if (StringUtils.isNotEmpty(analysis.getPrimaryIdentifier())) {
+            primary = analysis.getStatistics().get(analysis.getPrimaryIdentifier());
+        }
+        if (primary == null) {
+            primary = analysis.getStatistics().values().stream().findFirst().orElse(null);
+        }
+
+        // 添加监测分类描述
+        String categoryDesc = context.getCategory().getDesc() + "监测分析报告";
 
         return ReportModel.builder()
                 .reportNo(context.getReportNo())
@@ -43,6 +56,7 @@ public class ReportAssembler {
                 .productName(context.getProduct().getProductName())
                 .deviceId(context.getDevice().getDeviceId())
                 .category(context.getCategory())
+                .categoryDesc(categoryDesc)  // 添加分类描述
                 .metricName(primary == null ? null : primary.getModelName())
                 .metricUnit(primary == null ? null : primary.getUnit())
                 .analysis(analysis)

fastbee-report/src/main/java/com/fastbee/report/core/ReportContext.java

@@ -42,4 +42,10 @@ public class ReportContext {
     private Map<String, ReportThreshold> thresholds;
 
     private String reportNo;
+
+    /** 创建人用户名（从主线程传递，避免异步线程无法访问 SecurityContext） */
+    private String createBy;
+
+    /** 租户ID（从主线程传递） */
+    private Long tenantId;
 }

fastbee-report/src/main/java/com/fastbee/report/core/ReportContextBuilder.java

@@ -4,6 +4,8 @@ import com.fastbee.common.enums.MonitorCategory;
 import com.fastbee.iot.domain.Device;
 import com.fastbee.iot.domain.Product;
 import com.fastbee.iot.domain.ThingsModel;
+import com.fastbee.common.utils.SecurityUtils;
+import com.fastbee.common.core.domain.model.LoginUser;
 import com.fastbee.iot.mapper.SubGatewayMapper;
 import com.fastbee.iot.service.IDeviceService;
 import com.fastbee.iot.service.IProductService;
@@ -62,14 +64,14 @@ public class ReportContextBuilder {
             throw new ReportException("设备不存在: " + request.getDeviceId());
         }
 
-        // 网关设备特殊处理：使用第一个有监测分类的子设备构建上下文
+        // 网关设备不允许直接生成报表：网关是通信中继，真正的监测设备是子设备
         Integer deviceType = device.getDeviceType();
         if (deviceType != null && deviceType == DEVICE_TYPE_GATEWAY) {
-            Device subDevice = resolveFirstMonitorSubDevice(request.getDeviceId());
-            if (subDevice == null) {
-                throw new ReportException("网关设备下无可用监测子设备，请选择具体监测设备");
-            }
-            device = subDevice;
+            List<Long> subDeviceIds = subGatewayMapper.selectSubDeviceIdsByGwDeviceId(request.getDeviceId());
+            String tip = (subDeviceIds == null || subDeviceIds.isEmpty())
+                    ? "该网关下未绑定子设备"
+                    : "请选择具体监测设备（网关下有 " + subDeviceIds.size() + " 个子设备）";
+            throw new ReportException("网关设备不能直接生成报告。" + tip);
         }
 
         if (device.getProductId() == null) {
@@ -110,6 +112,24 @@ public class ReportContextBuilder {
         context.setMetricDataList(metricDataList);
         context.setThresholds(thresholds);
         context.setReportNo(reportNo);
+
+        // 从主线程获取用户信息，传递到异步线程
+        String username = null;
+        Long tenantId = null;
+        try {
+            LoginUser loginUser = SecurityUtils.getLoginUser();
+            if (loginUser != null) {
+                username = loginUser.getUsername();
+                if (loginUser.getUser() != null && loginUser.getUser().getDept() != null) {
+                    tenantId = loginUser.getUser().getDept().getDeptUserId();
+                }
+            }
+        } catch (Exception ignored) {
+            // 非登录态（如后台任务）时保持为 null
+        }
+        context.setCreateBy(username);
+        context.setTenantId(tenantId);
+
         return context;
     }
 

fastbee-report/src/main/java/com/fastbee/report/executor/ReportAsyncExecutor.java

@@ -1,4 +1,4 @@
-package com.fastbee.report.core;
+package com.fastbee.report.executor;
 
 import com.fastbee.common.core.redis.RedisCache;
 import com.fastbee.common.enums.MonitorCategory;
@@ -7,10 +7,11 @@ import com.fastbee.oss.entity.UploadResult;
 import com.fastbee.oss.service.OssFactory;
 import com.fastbee.report.analyzer.ReportAnalyzer;
 import com.fastbee.report.analyzer.ReportAnalyzerFactory;
-import com.fastbee.report.api.ReportEngine;
 import com.fastbee.report.api.ReportRequest;
-import com.fastbee.report.api.ReportResult;
 import com.fastbee.report.category.MonitorCategoryResolver;
+import com.fastbee.report.core.ReportAssembler;
+import com.fastbee.report.core.ReportContext;
+import com.fastbee.report.core.ReportContextBuilder;
 import com.fastbee.report.exception.ReportException;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.ReportModel;
@@ -20,6 +21,7 @@ import com.fastbee.report.record.ReportRecord;
 import com.fastbee.report.record.ReportRecordService;
 import com.fastbee.report.renderer.ReportRenderer;
 import lombok.extern.slf4j.Slf4j;
+import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
 import org.springframework.stereotype.Component;
 
 import javax.annotation.Resource;
@@ -31,14 +33,14 @@ import java.util.Date;
 import java.util.concurrent.ThreadLocalRandom;
 
 /**
- * 默认报告引擎：周期/分类解析 → 上下文装配 → 分析 → 渲染 → MinIO 上传 → 落库
+ * 报告异步执行器
  *
  * @author FastBee
- * @date 2026-08-16
+ * @date 2026-09-10
  */
 @Slf4j
 @Component
-public class DefaultReportEngine implements ReportEngine {
+public class ReportAsyncExecutor {
 
     private static final String WORD_CONTENT_TYPE =
             "application/vnd.openxmlformats-officedocument.wordprocessingml.document";
@@ -70,8 +72,16 @@ public class DefaultReportEngine implements ReportEngine {
     @Resource
     private RedisCache redisCache;
 
-    @Override
-    public ReportResult generate(ReportRequest request) {
+    @Resource
+    private ThreadPoolTaskExecutor threadPoolTaskExecutor;
+
+    /**
+     * 异步生成报告
+     *
+     * @param request 报告请求
+     * @return 报告编号（立即返回）
+     */
+    public String submitAsyncTask(ReportRequest request) {
         validate(request);
         TimeWindow window = periodResolver.resolve(request);
         MonitorCategory category = categoryResolver.resolveByDeviceId(request.getDeviceId());
@@ -81,36 +91,44 @@ public class DefaultReportEngine implements ReportEngine {
 
         String reportNo = generateReportNo();
         ReportContext context = contextBuilder.build(request, window, category, reportNo);
+
+        // 创建 CREATING 状态记录
         ReportRecord record = reportRecordService.createCreating(context);
+
+        // 提交异步任务到线程池
+        final ReportContext finalContext = context;
+        final ReportRequest finalRequest = request;
+        threadPoolTaskExecutor.execute(() -> asyncGenerate(finalRequest, finalContext, record));
+
+        return reportNo;
+    }
+
+    /**
+     * 异步执行生成逻辑
+     */
+    private void asyncGenerate(ReportRequest request, ReportContext context, ReportRecord record) {
         try {
-            ReportAnalyzer analyzer = analyzerFactory.get(category);
+            String reportNo = context.getReportNo();
+            log.info("开始异步生成报告 reportNo={} deviceId={}", reportNo, request.getDeviceId());
+
+            ReportAnalyzer analyzer = analyzerFactory.get(context.getCategory());
             AnalysisResult analysis = analyzer.analyze(context, request);
             ReportModel model = reportAssembler.assemble(context, analysis);
             byte[] docBytes = reportRenderer.render(model);
 
-            String path = buildObjectPath(window, request.getDeviceId(), reportNo);
+            String path = buildObjectPath(request.getDeviceId(), reportNo);
             UploadResult upload = OssFactory.instance(redisCache)
                     .upload(docBytes, path, WORD_CONTENT_TYPE);
             Date expireTime = new Date(System.currentTimeMillis() + RETENTION_DAYS * 24L * 3600 * 1000);
+
             reportRecordService.markSuccess(record, model.getFileName(), upload.getUrl(), expireTime);
             log.info("报告生成成功 reportNo={} fileUrl={}", reportNo, upload.getUrl());
 
-            return ReportResult.builder()
-                    .reportNo(reportNo)
-                    .status(ReportRecord.STATUS_SUCCESS)
-                    .fileName(model.getFileName())
-                    .fileUrl(upload.getUrl())
-                    .expireTime(expireTime)
-                    .build();
         } catch (Exception e) {
-            log.error("报告生成失败 reportNo={} deviceId={}", reportNo, request.getDeviceId(), e);
+            log.error("报告生成失败 reportNo={} deviceId={}", context.getReportNo(), request.getDeviceId(), e);
             String message = e instanceof ReportException ? e.getMessage()
                     : (e.getMessage() == null ? e.getClass().getSimpleName() : e.getMessage());
             reportRecordService.markFailed(record, message);
-            if (e instanceof ReportException) {
-                throw (ReportException) e;
-            }
-            throw new ReportException("报告生成失败: " + message, e);
         }
     }
 
@@ -123,7 +141,7 @@ public class DefaultReportEngine implements ReportEngine {
         }
         if (StringUtils.isNotEmpty(request.getFormat())
                 && !"WORD".equalsIgnoreCase(request.getFormat())) {
-            throw new ReportException("V1 仅支持 WORD 格式导出");
+            throw new ReportException("目前仅支持 WORD 格式导出");
         }
     }
 
@@ -132,7 +150,7 @@ public class DefaultReportEngine implements ReportEngine {
                 + "-" + String.format("%04d", ThreadLocalRandom.current().nextInt(10000));
     }
 
-    private String buildObjectPath(TimeWindow window, Long deviceId, String reportNo) {
+    private String buildObjectPath(Long deviceId, String reportNo) {
         LocalDate today = LocalDate.now(ZoneOffset.ofHours(8));
         return "report/" + today.format(PATH_DATE) + "/device/" + deviceId + "/" + reportNo + ".docx";
     }

fastbee-report/src/main/java/com/fastbee/report/model/AnalysisResult.java

@@ -2,6 +2,7 @@ package com.fastbee.report.model;
 
 import lombok.Data;
 
+import java.math.BigDecimal;
 import java.util.ArrayList;
 import java.util.LinkedHashMap;
 import java.util.List;
@@ -16,6 +17,30 @@ import java.util.Map;
 @Data
 public class AnalysisResult {
 
+    /** 主监测指标标识符（统一由 Analyzer 解析，ReportAssembler/WordRenderer 共用） */
+    private String primaryIdentifier;
+
+    /** 项目概况总结（开头段落，概括关键数据） */
+    private String summary;
+
+    /** 专业分析建议（基于设备类型和数据分析的工程建议） */
+    private String professionalAdvice;
+
+    /** 安全评估等级（SAFE/WARNING/DANGER/CRITICAL） */
+    private String safetyLevel;
+
+    /** 安全评估说明 */
+    private String safetyDescription;
+
+    /** 控制值（安全参考基准） */
+    private BigDecimal controlValue;
+
+    /** 控制值单位 */
+    private String controlValueUnit;
+
+    /** 多指标对比数据（用于详细表格展示） */
+    private List<MetricPointData> metricPoints = new ArrayList<>();
+
     /** 每个物模型标识符对应的统计指标 */
     private Map<String, Statistics> statistics = new LinkedHashMap<>();
 

fastbee-report/src/main/java/com/fastbee/report/model/MetricPointData.java

@@ -0,0 +1,72 @@
+package com.fastbee.report.model;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.math.BigDecimal;
+
+/**
+ * 测点数据（用于详细表格展示，支持多测点设备）
+ *
+ * @author FastBee
+ * @date 2026-09-09
+ */
+@Data
+@Builder
+@NoArgsConstructor
+@AllArgsConstructor
+public class MetricPointData {
+
+    /** 测点编号（如 MS13-1） */
+    private String pointNo;
+
+    /** 测点名称（如 红线/白线/绿线） */
+    private String pointName;
+
+    /** 物模型标识符 */
+    private String identifier;
+
+    /** 物模型名称 */
+    private String modelName;
+
+    /** 初始值 */
+    private BigDecimal initialValue;
+
+    /** 初始值单位 */
+    private String initialUnit;
+
+    /** 当前值 */
+    private BigDecimal currentValue;
+
+    /** 当前值单位 */
+    private String currentUnit;
+
+    /** 变化量 */
+    private BigDecimal changeValue;
+
+    /** 变化量单位 */
+    private String changeUnit;
+
+    /** 变化速率 */
+    private BigDecimal changeRate;
+
+    /** 变化速率单位 */
+    private String rateUnit;
+
+    /** 最大值 */
+    private BigDecimal maxValue;
+
+    /** 最小值 */
+    private BigDecimal minValue;
+
+    /** 平均值 */
+    private BigDecimal avgValue;
+
+    /** 预警状态（NORMAL/WARNING/ALARM） */
+    private String warningStatus;
+
+    /** 备注 */
+    private String remark;
+}

fastbee-report/src/main/java/com/fastbee/report/model/ReportModel.java

@@ -5,6 +5,7 @@ import com.fastbee.common.enums.ReportPeriod;
 import lombok.Builder;
 import lombok.Data;
 
+import java.math.BigDecimal;
 import java.util.Date;
 
 /**
@@ -49,5 +50,14 @@ public class ReportModel {
     /** 主监测指标单位 */
     private String metricUnit;
 
+    /** 监测分类描述（如"裂缝计监测分析报告"） */
+    private String categoryDesc;
+
+    /** 控制值（安全参考基准） */
+    private BigDecimal controlValue;
+
+    /** 控制值单位 */
+    private String controlValueUnit;
+
     private AnalysisResult analysis;
 }

fastbee-report/src/main/java/com/fastbee/report/record/ReportRecordServiceImpl.java

@@ -1,8 +1,6 @@
 package com.fastbee.report.record;
 
-import com.fastbee.common.core.domain.model.LoginUser;
 import com.fastbee.common.utils.DateUtils;
-import com.fastbee.common.utils.SecurityUtils;
 import com.fastbee.report.core.ReportContext;
 import com.fastbee.report.mapper.ReportRecordMapper;
 import org.springframework.stereotype.Service;
@@ -38,8 +36,8 @@ public class ReportRecordServiceImpl implements ReportRecordService {
         record.setStartTime(toGmt8Date(context.getTimeWindow().getStartTime()));
         record.setEndTime(toGmt8Date(context.getTimeWindow().getEndTime()));
         record.setStatus(ReportRecord.STATUS_CREATING);
-        record.setTenantId(currentTenantId());
-        record.setCreateBy(SecurityUtils.getUsername());
+        record.setTenantId(context.getTenantId());
+        record.setCreateBy(context.getCreateBy());
         record.setCreateTime(now);
         record.setExpireTime(new Date(now.getTime() + RETENTION_DAYS * 24L * 3600 * 1000));
         reportRecordMapper.insert(record);
@@ -58,7 +56,8 @@ public class ReportRecordServiceImpl implements ReportRecordService {
         update.setFileName(fileName);
         update.setFileUrl(fileUrl);
         update.setExpireTime(expireTime);
-        update.setUpdateBy(SecurityUtils.getUsername());
+        // 异步线程中无法访问 SecurityContext，使用创建时的用户名
+        update.setUpdateBy(record.getCreateBy());
         update.setUpdateTime(DateUtils.getNowDate());
         reportRecordMapper.updateById(update);
     }
@@ -69,7 +68,8 @@ public class ReportRecordServiceImpl implements ReportRecordService {
         update.setId(record.getId());
         update.setStatus(ReportRecord.STATUS_FAILED);
         update.setErrorMessage(errorMessage);
-        update.setUpdateBy(SecurityUtils.getUsername());
+        // 异步线程中无法访问 SecurityContext，使用创建时的用户名
+        update.setUpdateBy(record.getCreateBy());
         update.setUpdateTime(DateUtils.getNowDate());
         reportRecordMapper.updateById(update);
     }
@@ -86,17 +86,4 @@ public class ReportRecordServiceImpl implements ReportRecordService {
                         .eq(ReportRecord::getReportNo, reportNo)
                         .last("limit 1"));
     }
-
-    private Long currentTenantId() {
-        try {
-            LoginUser loginUser = SecurityUtils.getLoginUser();
-            if (loginUser != null && loginUser.getUser() != null
-                    && loginUser.getUser().getDept() != null) {
-                return loginUser.getUser().getDept().getDeptUserId();
-            }
-        } catch (Exception ignored) {
-            // 非登录态（如后台任务）时租户为空
-        }
-        return null;
-    }
 }

fastbee-report/src/main/java/com/fastbee/report/renderer/WordRenderer.java

@@ -6,14 +6,20 @@ import com.deepoove.poi.data.ByteArrayPictureRenderData;
 import com.deepoove.poi.data.PictureType;
 import com.deepoove.poi.data.style.PictureStyle;
 import com.deepoove.poi.plugin.table.LoopRowTableRenderPolicy;
+import com.fastbee.common.utils.StringUtils;
 import com.fastbee.report.exception.ReportException;
 import com.fastbee.report.model.AnalysisResult;
 import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
 import com.fastbee.report.model.QualityAnalysis;
 import com.fastbee.report.model.ReportModel;
 import com.fastbee.report.model.Statistics;
 import com.fastbee.report.model.TrendAnalysis;
 import com.fastbee.report.model.WarningAnalysis;
+import org.apache.poi.xwpf.usermodel.XWPFDocument;
+import org.apache.poi.xwpf.usermodel.XWPFTable;
+import org.apache.poi.xwpf.usermodel.XWPFTableCell;
+import org.apache.poi.xwpf.usermodel.XWPFTableRow;
 import org.springframework.stereotype.Component;
 
 import javax.annotation.Resource;
@@ -21,6 +27,7 @@ import java.io.ByteArrayInputStream;
 import java.io.ByteArrayOutputStream;
 import java.io.IOException;
 import java.math.BigDecimal;
+import java.math.RoundingMode;
 import java.text.SimpleDateFormat;
 import java.util.ArrayList;
 import java.util.HashMap;
@@ -45,12 +52,14 @@ public class WordRenderer implements ReportRenderer {
         Map<String, Object> data = buildData(model);
         Configure config = Configure.builder()
                 .bind("conclusions", new LoopRowTableRenderPolicy())
+                .bind("metricPoints", new LoopRowTableRenderPolicy())  // 添加多测点数据绑定
                 .build();
         XWPFTemplate tpl = XWPFTemplate.compile(new ByteArrayInputStream(template), config).render(data);
         try {
             ByteArrayOutputStream out = new ByteArrayOutputStream();
             tpl.write(out);
-            return out.toByteArray();
+            // 后处理：清除循环表格残留的空行，避免排版出现空白行
+            return cleanupEmptyTableRows(out.toByteArray());
         } catch (IOException e) {
             throw new ReportException("Word 渲染失败: " + e.getMessage(), e);
         } finally {
@@ -62,10 +71,45 @@ public class WordRenderer implements ReportRenderer {
         }
     }
 
+    /**
+     * 清除表格中的空白行（poi-tl 循环表格的标记行渲染后会残留为空行）
+     */
+    private byte[] cleanupEmptyTableRows(byte[] docx) {
+        try (XWPFDocument document = new XWPFDocument(new ByteArrayInputStream(docx))) {
+            for (XWPFTable table : document.getTables()) {
+                List<XWPFTableRow> rows = table.getRows();
+                for (int i = rows.size() - 1; i >= 0; i--) {
+                    if (isRowBlank(rows.get(i))) {
+                        table.removeRow(i);
+                    }
+                }
+            }
+            ByteArrayOutputStream buffer = new ByteArrayOutputStream();
+            document.write(buffer);
+            return buffer.toByteArray();
+        } catch (Exception e) {
+            // 后处理失败时返回原始文档，不影响报告生成
+            return docx;
+        }
+    }
+
+    /**
+     * 判断表格行是否完全空白
+     */
+    private boolean isRowBlank(XWPFTableRow row) {
+        for (XWPFTableCell cell : row.getTableCells()) {
+            if (cell.getText() != null && !cell.getText().trim().isEmpty()) {
+                return false;
+            }
+        }
+        return true;
+    }
+
     private Map<String, Object> buildData(ReportModel model) {
         Map<String, Object> data = new HashMap<>();
         AnalysisResult analysis = model.getAnalysis() == null ? new AnalysisResult() : model.getAnalysis();
-        Statistics primary = analysis.getStatistics().values().stream().findFirst().orElse(null);
+        // 主监测指标：与概况/结论口径一致（Analyzer 解析的 primaryIdentifier）
+        Statistics primary = resolvePrimary(analysis);
         TrendAnalysis trend = primary == null ? null : analysis.getTrends().get(primary.getIdentifier());
         QualityAnalysis quality = primary == null ? null : analysis.getQualities().get(primary.getIdentifier());
         WarningAnalysis warning = primary == null ? null : analysis.getWarnings().get(primary.getIdentifier());
@@ -95,6 +139,15 @@ public class WordRenderer implements ReportRenderer {
             statistics.put("totalDelta", str(primary.getTotalDelta()));
             statistics.put("count", primary.getCount());
             statistics.put("unit", primary.getUnit() == null ? "" : primary.getUnit());
+            // 带单位的展示值（单位为空时不产生多余空格）
+            statistics.put("currentWithUnit", withUnit(str(primary.getCurrent()), primary.getUnit()));
+            statistics.put("initialWithUnit", withUnit(str(primary.getInitial()), primary.getUnit()));
+            statistics.put("maxWithUnit", withUnit(str(primary.getMax()), primary.getUnit()));
+            statistics.put("minWithUnit", withUnit(str(primary.getMin()), primary.getUnit()));
+            statistics.put("avgWithUnit", withUnit(str(primary.getAvg()), primary.getUnit()));
+            statistics.put("medianWithUnit", withUnit(str(primary.getMedian()), primary.getUnit()));
+            statistics.put("deltaWithUnit", withUnit(str(primary.getDelta()), primary.getUnit()));
+            statistics.put("totalDeltaWithUnit", withUnit(str(primary.getTotalDelta()), primary.getUnit()));
         } else {
             statistics.put("count", 0);
             statistics.put("unit", "");
@@ -108,7 +161,7 @@ public class WordRenderer implements ReportRenderer {
         qualityMap.put("description", quality == null ? "统计期内无有效数据" : quality.getDescription());
 
         Map<String, Object> warningMap = new HashMap<>();
-        warningMap.put("status", warning == null ? WarningAnalysis.STATUS_NORMAL : warning.getStatus());
+        warningMap.put("status", warning == null ? "正常" : warningStatusText(warning.getStatus()));
         warningMap.put("description", warning == null ? "统计期内无有效数据" : warning.getDescription());
 
         Map<String, Object> analysisMap = new HashMap<>();
@@ -117,26 +170,68 @@ public class WordRenderer implements ReportRenderer {
         analysisMap.put("quality", qualityMap);
         analysisMap.put("warning", warningMap);
 
-        Map<String, Object> charts = new HashMap<>();
-        // 支持通用图表键名（所有分类使用统一的 timeSeriesChart）
-        byte[] timeSeriesChart = analysis.getCharts().get("timeSeriesChart");
-        if (timeSeriesChart != null) {
-            ByteArrayPictureRenderData picture = new ByteArrayPictureRenderData(timeSeriesChart, PictureType.PNG);
-            PictureStyle style = new PictureStyle();
-            style.setWidth(640);
-            style.setHeight(280);
-            picture.setPictureStyle(style);
-            charts.put("timeSeriesChart", picture);
+        // 添加项目概况总结（始终 put，空值兜底）
+        data.put("summary", StringUtils.isNotEmpty(analysis.getSummary())
+                ? analysis.getSummary() : "统计期内无有效监测数据。");
+
+        // 添加专业分析建议（始终 put，空值兜底）
+        data.put("professionalAdvice", StringUtils.isNotEmpty(analysis.getProfessionalAdvice())
+                ? analysis.getProfessionalAdvice() : "暂无专业分析建议。");
+
+        // 添加安全评估（始终 put，空值兜底）
+        data.put("safetyLevel", safetyLevelText(StringUtils.isNotEmpty(analysis.getSafetyLevel())
+                ? analysis.getSafetyLevel() : "待评估"));
+        data.put("safetyDescription", StringUtils.isNotEmpty(analysis.getSafetyDescription())
+                ? analysis.getSafetyDescription() : "暂无评估说明。");
+
+        // 添加控制值（始终 put，空值兜底）
+        data.put("controlValue", analysis.getControlValue() != null
+                ? analysis.getControlValue().toPlainString() : "未配置");
+        data.put("controlValueUnit", analysis.getControlValueUnit() != null
+                ? analysis.getControlValueUnit() : "");
+
+        // 添加多测点数据（始终 put，空列表兜底）
+        List<Map<String, Object>> metricPointsList = new ArrayList<>();
+        if (analysis.getMetricPoints() != null && !analysis.getMetricPoints().isEmpty()) {
+            for (MetricPointData point : analysis.getMetricPoints()) {
+                Map<String, Object> pointMap = new HashMap<>();
+                pointMap.put("pointNo", point.getPointNo() == null ? "" : point.getPointNo());
+                pointMap.put("pointName", point.getPointName() == null ? "" : point.getPointName());
+                pointMap.put("identifier", point.getIdentifier());
+                pointMap.put("modelName", point.getModelName());
+                pointMap.put("initialValue", str(point.getInitialValue()));
+                pointMap.put("initialUnit", point.getInitialUnit() == null ? "" : point.getInitialUnit());
+                pointMap.put("currentValue", str(point.getCurrentValue()));
+                pointMap.put("currentUnit", point.getCurrentUnit() == null ? "" : point.getCurrentUnit());
+                pointMap.put("changeValue", str(point.getChangeValue()));
+                pointMap.put("changeUnit", point.getChangeUnit() == null ? "" : point.getChangeUnit());
+                pointMap.put("changeRate", str(point.getChangeRate()));
+                pointMap.put("rateUnit", point.getRateUnit() == null ? "" : point.getRateUnit());
+                pointMap.put("maxValue", str(point.getMaxValue()));
+                pointMap.put("minValue", str(point.getMinValue()));
+                pointMap.put("avgValue", str(point.getAvgValue()));
+                // 无数据的指标标注"无数据"，避免误报为正常
+                pointMap.put("warningStatus", point.getCurrentValue() == null
+                        ? "无数据" : warningStatusText(point.getWarningStatus()));
+                metricPointsList.add(pointMap);
+            }
         }
-        // 兼容旧版裂缝计模板
-        byte[] crackTrend = analysis.getCharts().get("crackTrend");
-        if (crackTrend != null) {
-            ByteArrayPictureRenderData picture = new ByteArrayPictureRenderData(crackTrend, PictureType.PNG);
+        data.put("metricPoints", metricPointsList);
+
+        // 图表：兼容 timeSeriesChart（主指标）/ chart2 / chart3（分组指标）/ crackTrend（旧模板）
+        Map<String, Object> charts = new HashMap<>();
+        for (Map.Entry<String, byte[]> entry : analysis.getCharts().entrySet()) {
+            byte[] png = entry.getValue();
+            if (png == null || png.length == 0) {
+                continue;
+            }
+            ByteArrayPictureRenderData picture = new ByteArrayPictureRenderData(png, PictureType.PNG);
             PictureStyle style = new PictureStyle();
-            style.setWidth(640);
-            style.setHeight(280);
+            // 适配 A4 页面可用宽度（约 15.9cm ≈ 600px）
+            style.setWidth(600);
+            style.setHeight(240);
             picture.setPictureStyle(style);
-            charts.put("crackTrend", picture);
+            charts.put(entry.getKey(), picture);
         }
 
         List<Map<String, Object>> conclusions = new ArrayList<>();
@@ -155,7 +250,63 @@ public class WordRenderer implements ReportRenderer {
         return data;
     }
 
+    /**
+     * 解析主监测指标统计：优先 primaryIdentifier，兜底第一个
+     */
+    private Statistics resolvePrimary(AnalysisResult analysis) {
+        if (StringUtils.isNotEmpty(analysis.getPrimaryIdentifier())) {
+            Statistics statistics = analysis.getStatistics().get(analysis.getPrimaryIdentifier());
+            if (statistics != null) {
+                return statistics;
+            }
+        }
+        return analysis.getStatistics().values().stream().findFirst().orElse(null);
+    }
+
+    /**
+     * 拼接数值与单位（单位为空时只返回数值，避免尾部空格）
+     */
+    private String withUnit(String value, String unit) {
+        return (unit == null || unit.trim().isEmpty()) ? value : value + " " + unit.trim();
+    }
+
+    /**
+     * 数值格式化：最多保留 6 位小数并去除末尾多余的 0
+     * 例：-499.9277470 → -499.927747；3.9844728 → 3.984473；0.000000 → 0
+     */
     private String str(BigDecimal value) {
-        return value == null ? "-" : value.toPlainString();
+        if (value == null) {
+            return "-";
+        }
+        BigDecimal formatted = value.setScale(6, RoundingMode.HALF_UP).stripTrailingZeros();
+        if (formatted.compareTo(BigDecimal.ZERO) == 0) {
+            return "0";
+        }
+        return formatted.toPlainString();
+    }
+
+    /** 预警状态转中文 */
+    private String warningStatusText(String status) {
+        if (WarningAnalysis.STATUS_ALARM.equals(status)) {
+            return "报警";
+        }
+        if (WarningAnalysis.STATUS_WARNING.equals(status)) {
+            return "预警";
+        }
+        return "正常";
+    }
+
+    /** 安全等级转中文 */
+    private String safetyLevelText(String level) {
+        if ("DANGER".equals(level)) {
+            return "危险";
+        }
+        if ("WARNING".equals(level)) {
+            return "预警";
+        }
+        if ("CRITICAL".equals(level)) {
+            return "临界";
+        }
+        return "安全";
     }
 }

fastbee-report/src/test/java/com/fastbee/report/renderer/WordRendererTest.java

@@ -38,7 +38,7 @@ public class WordRendererTest {
             @Override
             public byte[] resolve(String templateCode) {
                 try (java.io.InputStream in = getClass().getClassLoader()
-                        .getResourceAsStream("templates/DEVICE_CRACK_METER_V1.docx")) {
+                        .getResourceAsStream("templates/DEVICE_CRACK_METER_V2.docx")) {
                     return in == null ? null : cn.hutool.core.io.IoUtil.readBytes(in);
                 } catch (Exception e) {
                     throw new RuntimeException(e);

fastbee-report/src/test/java/com/fastbee/report/renderer/WordRendererV2TemplateTest.java

@@ -0,0 +1,223 @@
+package com.fastbee.report.renderer;
+
+import com.fastbee.common.enums.MonitorCategory;
+import com.fastbee.common.enums.ReportPeriod;
+import com.fastbee.report.chart.ChartGenerator;
+import com.fastbee.report.data.MetricData;
+import com.fastbee.report.model.AnalysisResult;
+import com.fastbee.report.model.Conclusion;
+import com.fastbee.report.model.MetricPointData;
+import com.fastbee.report.model.QualityAnalysis;
+import com.fastbee.report.model.ReportModel;
+import com.fastbee.report.model.Statistics;
+import com.fastbee.report.model.TrendAnalysis;
+import com.fastbee.report.model.WarningAnalysis;
+import org.junit.jupiter.api.Test;
+import org.springframework.test.util.ReflectionTestUtils;
+
+import java.io.InputStream;
+import java.math.BigDecimal;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.Date;
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+
+/**
+ * V2 专业模板渲染冒烟测试：验证循环表格（conclusions/metricPoints）+ 图表 + 概况总结
+ *
+ * @author FastBee
+ * @date 2026-09-10
+ */
+public class WordRendererV2TemplateTest {
+
+    @Test
+    public void testRenderDeepDisplacementV2() {
+        WordRenderer renderer = new WordRenderer();
+        ReflectionTestUtils.setField(renderer, "templateResolver", new WordTemplateResolver() {
+            @Override
+            public byte[] resolve(String templateCode) {
+                InputStream in = getClass().getClassLoader()
+                        .getResourceAsStream("templates/" + templateCode + ".docx");
+                if (in == null) {
+                    throw new IllegalStateException("模板不存在: " + templateCode);
+                }
+                return cn.hutool.core.io.IoUtil.readBytes(in);
+            }
+        });
+
+        ReportModel model = buildDeepDisplacementModel();
+        byte[] docx = renderer.render(model);
+        assertNotNull(docx);
+        assertTrue(docx.length > 0);
+        String magic = new String(new byte[]{docx[0], docx[1]}, StandardCharsets.ISO_8859_1);
+        assertTrue("PK".equals(magic), "渲染结果应为有效 docx(zip)");
+
+        // 输出渲染结果，便于人工检查排版
+        try {
+            java.io.File out = new java.io.File("target/test-output-deep-displacement.docx");
+            java.nio.file.Files.write(out.toPath(), docx);
+            System.out.println("渲染结果已输出: " + out.getAbsolutePath());
+        } catch (Exception ignored) {
+            // 输出失败不影响测试结果
+        }
+    }
+
+    /** 所有 V2 模板均应可渲染（占位符语法校验） */
+    @Test
+    public void testAllV2TemplatesLoadable() {
+        String[] codes = {
+                "CRACK_METER_V2", "DEEP_DISPLACEMENT_V2", "AXIAL_FORCE_V2", "STATIC_LEVEL_V2",
+                "VIBRATING_WIRE_V2", "STRAIN_GAUGE_V2", "WATER_LEVEL_V2", "RANGING_METER_V2",
+                "INCLINOMETER_V2", "THERMOMETER_V2", "RAIN_GAUGE_V2"};
+        for (String suffix : codes) {
+            InputStream in = getClass().getClassLoader()
+                    .getResourceAsStream("templates/DEVICE_" + suffix + ".docx");
+            assertNotNull(in, "模板缺失: DEVICE_" + suffix);
+        }
+    }
+
+    private ReportModel buildDeepDisplacementModel() {
+        // 场景：设备配置了 3 个监测物模型，但只有 Z轴位移 有数据
+        // 其他物模型（X轴位移、温度）也应该在报告中显示，标注"无数据"
+
+        // 第一个物模型：Z轴位移（有数据）
+        Statistics zStats = new Statistics();
+        zStats.setIdentifier("zDisplacement");
+        zStats.setModelName("Z轴位移");
+        zStats.setUnit("mm");
+        zStats.setCount(144);
+        zStats.setCurrent(new BigDecimal("-499.928"));
+        zStats.setInitial(new BigDecimal("-499.92792"));
+        zStats.setMax(new BigDecimal("-499.9272"));
+        zStats.setMin(new BigDecimal("-499.928"));
+        zStats.setAvg(new BigDecimal("-499.927747"));
+        zStats.setMedian(new BigDecimal("-499.927730"));
+        zStats.setDelta(new BigDecimal("-0.00008"));
+        zStats.setTotalDelta(new BigDecimal("0.02554"));
+
+        // 第二个物模型：X轴位移（无数据）- 会在报告中显示"无数据"
+        Statistics xStats = new Statistics();
+        xStats.setIdentifier("xDisplacement");
+        xStats.setModelName("X轴位移");
+        xStats.setUnit("mm");
+        xStats.setCount(0);  // 无数据
+
+        // 第三个物模型：温度（无数据）- 会在报告中显示"无数据"
+        Statistics tempStats = new Statistics();
+        tempStats.setIdentifier("temperature");
+        tempStats.setModelName("温度");
+        tempStats.setUnit("℃");
+        tempStats.setCount(0);  // 无数据
+
+        TrendAnalysis trend = new TrendAnalysis();
+        trend.setIdentifier("zDisplacement");
+        trend.setModelName("Z轴位移");
+        trend.setDirection(TrendAnalysis.DIRECTION_STABLE);
+        trend.setSlope(new BigDecimal("-0.000439"));
+        trend.setRSquared(new BigDecimal("0.1053"));
+        trend.setDescription("整体波动较大，无明显趋势，日变化速率 -0.000439，拟合优度 R²=0.1053");
+
+        QualityAnalysis quality = new QualityAnalysis();
+        quality.setTotal(144);
+        quality.setMissing(0);
+        quality.setDuplicate(12);
+        quality.setOutOfRange(0);
+        quality.setCompletenessRate(new BigDecimal("1.0"));
+        quality.setDescription("统计期内共 144 条数据，预估缺数 0 条，完整率 100.00%，重复值 12 条");
+
+        WarningAnalysis warning = new WarningAnalysis();
+        warning.setStatus(WarningAnalysis.STATUS_NORMAL);
+        warning.setDescription("未配置结构化阈值，暂按正常处理");
+
+        AnalysisResult analysis = new AnalysisResult();
+        analysis.setPrimaryIdentifier("zDisplacement");  // 主监测指标
+        // 添加所有物模型的统计数据（包括无数据的）
+        analysis.getStatistics().put("zDisplacement", zStats);
+        analysis.getStatistics().put("xDisplacement", xStats);
+        analysis.getStatistics().put("temperature", tempStats);
+
+        analysis.getTrends().put("zDisplacement", trend);
+        analysis.getQualities().put("zDisplacement", quality);
+        analysis.getWarnings().put("zDisplacement", warning);
+
+        analysis.setSummary("本期深部位移监测数据显示：当前Z轴位移为-499.928mm，较初始值变化-0.00008mm，位移呈稳定趋势。");
+        analysis.setProfessionalAdvice("专业分析：位移变化稳定，结构状态正常。建议保持现有监测频率。");
+        analysis.setSafetyLevel("SAFE");
+        analysis.setSafetyDescription("监测指标处于正常范围。");
+        analysis.setControlValue(new BigDecimal("500"));
+        analysis.setControlValueUnit("mm");
+
+        // 添加所有测点数据（包括无数据的）
+        analysis.getMetricPoints().add(MetricPointData.builder()
+                .identifier("zDisplacement")
+                .modelName("Z轴位移")
+                .initialValue(new BigDecimal("-499.92792"))
+                .currentValue(new BigDecimal("-499.928"))
+                .changeValue(new BigDecimal("-0.00008"))
+                .changeRate(new BigDecimal("-0.000160"))
+                .maxValue(new BigDecimal("-499.9272"))
+                .minValue(new BigDecimal("-499.928"))
+                .avgValue(new BigDecimal("-499.927747"))
+                .warningStatus("NORMAL")
+                .build());
+
+        // X轴位移无数据
+        analysis.getMetricPoints().add(MetricPointData.builder()
+                .identifier("xDisplacement")
+                .modelName("X轴位移")
+                .warningStatus("无数据")
+                .build());
+
+        // 温度无数据
+        analysis.getMetricPoints().add(MetricPointData.builder()
+                .identifier("temperature")
+                .modelName("温度")
+                .warningStatus("无数据")
+                .build());
+
+        analysis.getConclusions().add(new Conclusion(1, "统计期内深部位移由 -499.92792 变化至 -499.928，位移方向为稳定。"));
+        analysis.getConclusions().add(new Conclusion(2, "平均位移速率 -0.000160mm/天。"));
+        analysis.getConclusions().add(new Conclusion(3, "共监测 3 个物模型：Z轴位移（有数据）、X轴位移（无数据）、温度（无数据）。"));
+
+        List<MetricData> chartData = new ArrayList<>();
+        long base = System.currentTimeMillis();
+        for (int i = 0; i < 10; i++) {
+            MetricData point = new MetricData();
+            point.setIdentity("zDisplacement");
+            point.setModelName("Z轴位移");
+            point.setUnit("mm");
+            point.setTime(new Date(base + i * 3600_000L));
+            point.setValue(String.valueOf(-499.928 + i * 0.001));
+            point.setNumericValue(BigDecimal.valueOf(-499.928 + i * 0.001));
+            chartData.add(point);
+        }
+        byte[] png = new ChartGenerator().timeSeriesChart("深部位移时程曲线", "Z轴位移", "mm", chartData);
+        analysis.getCharts().put("timeSeriesChart", png);
+        // 附图：其他指标分组图（模板预留 chart2 / chart3）
+        java.util.Map<String, java.util.List<MetricData>> grouped = new java.util.LinkedHashMap<>();
+        grouped.put("X轴位移", chartData);
+        analysis.getCharts().put("chart2", new ChartGenerator().multiSeriesChart("其他指标时程曲线", "mm", grouped));
+        analysis.getCharts().put("chart3", new ChartGenerator().blankChart("暂无数据"));
+
+        return ReportModel.builder()
+                .reportNo("REPORT-20260910090000-0001")
+                .templateCode("DEVICE_DEEP_DISPLACEMENT_V2")  // 注意：模板文件名是 DEVICE_DEEP_DISPLACEMENT_V2.docx
+                .fileName("D1903E4N060G-自定义-监测分析报告.docx")
+                .periodDesc("2026-09-09 20:58:18 ~ 2026-09-10 08:58:18")
+                .period(ReportPeriod.CUSTOM)
+                .generatedAt(new Date())
+                .deviceName("固定式测斜仪_1")
+                .serialNumber("D1903E4N060G")
+                .productName("固定式测斜仪")
+                .deviceId(20001L)
+                .category(MonitorCategory.DEEP_DISPLACEMENT)
+                .categoryDesc("深部位移监测分析报告")
+                .metricName("Z轴位移")
+                .metricUnit("mm")
+                .analysis(analysis)
+                .build();
+    }
+}

fastbee-service/fastbee-iot-service/src/main/java/com/fastbee/iot/mapper/DeviceMapper.java

@@ -400,6 +400,15 @@ public interface DeviceMapper extends BaseMapperX<Device> {
      */
     List<Device> selectDeviceListByDeviceIds(@Param("deviceIdList") List<Long> deviceIdList);
 
+    /**
+     * 树形设备列表专用轻量查询：只查树所需字段，复用简短列表的权限过滤，
+     * 避开 is_owner/sub_device_count 逐行关联子查询
+     *
+     * @param device 查询条件
+     * @return 设备简短列表（仅含树所需字段）
+     */
+    List<DeviceShortOutput> selectDeviceTreeBaseList(Device device);
+
     /**
      * 根据监控设备channelId获取设备
      *

fastbee-service/fastbee-iot-service/src/main/java/com/fastbee/iot/mapper/SubGatewayMapper.java

@@ -118,4 +118,12 @@ public interface SubGatewayMapper {
      * @return 子设备ID列表
      */
     List<Long> selectSubDeviceIdsByGwDeviceId(Long gwDeviceId);
+
+    /**
+     * 根据网关设备ID列表批量查询网关与子设备关联（一次查询替代逐网关循环查询）
+     *
+     * @param gwDeviceIdList 网关设备ID列表
+     * @return 网关与子设备关联集合
+     */
+    List<SubGateway> selectSubGatewayListByGwDeviceIds(@Param("gwDeviceIdList") List<Long> gwDeviceIdList);
 }

fastbee-service/fastbee-iot-service/src/main/java/com/fastbee/iot/model/DeviceTreeVO.java

@@ -0,0 +1,78 @@
+package com.fastbee.iot.model;
+
+import io.swagger.annotations.ApiModel;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.util.List;
+
+/**
+ * 树形设备VO（用于设备选择器，网关可展开显示子设备）
+ *
+ * @author FastBee
+ * @date 2026-09-09
+ */
+@Data
+@ApiModel(value = "DeviceTreeVO", description = "树形设备VO")
+public class DeviceTreeVO {
+
+    /**
+     * 设备ID
+     */
+    @ApiModelProperty("设备ID")
+    private Long deviceId;
+
+    /**
+     * 设备名称
+     */
+    @ApiModelProperty("设备名称")
+    private String deviceName;
+
+    /**
+     * 设备序列号
+     */
+    @ApiModelProperty("设备序列号")
+    private String serialNumber;
+
+    /**
+     * 产品ID
+     */
+    @ApiModelProperty("产品ID")
+    private Long productId;
+
+    /**
+     * 产品名称
+     */
+    @ApiModelProperty("产品名称")
+    private String productName;
+
+    /**
+     * 设备类型（1=直连设备，2=网关设备，3=摄像头）
+     */
+    @ApiModelProperty("设备类型（1=直连设备，2=网关设备，3=摄像头）")
+    private Integer deviceType;
+
+    /**
+     * 设备状态（1-未激活，2-禁用，3-在线，4-离线）
+     */
+    @ApiModelProperty("设备状态（1-未激活，2-禁用，3-在线，4-离线）")
+    private Integer status;
+
+    /**
+     * 是否为叶子节点（网关=false，其他=true）
+     */
+    @ApiModelProperty("是否为叶子节点（网关=false，其他=true）")
+    private Boolean isLeaf;
+
+    /**
+     * 子设备列表（仅网关设备有子设备）
+     */
+    @ApiModelProperty("子设备列表")
+    private List<DeviceTreeVO> children;
+
+    /**
+     * 设备完整路径名称（如：网关A / 子设备A-1）
+     */
+    @ApiModelProperty("设备完整路径名称")
+    private String fullPath;
+}

fastbee-service/fastbee-iot-service/src/main/java/com/fastbee/iot/service/IDeviceService.java

@@ -432,4 +432,12 @@ public interface IDeviceService {
 
     public int updateDeviceBySerialNumber(Device device);
 
+    /**
+     * 查询树形设备列表（网关设备可展开显示子设备）
+     *
+     * @param device 查询条件
+     * @return 树形设备列表
+     */
+    List<DeviceTreeVO> selectDeviceTreeList(Device device);
+
 }

fastbee-service/fastbee-iot-service/src/main/java/com/fastbee/iot/service/impl/DeviceServiceImpl.java

@@ -87,6 +87,10 @@ import static com.fastbee.common.utils.SecurityUtils.isAdmin;
 public class DeviceServiceImpl implements IDeviceService {
 
     private static final Logger log = LoggerFactory.getLogger(DeviceServiceImpl.class);
+    /**
+     * SQL IN 子句分批大小（防止过长 IN 列表）
+     */
+    private static final int SQL_IN_BATCH_SIZE = 1000;
     @Value("${server.broker.port}")
     private Long brokerPort;
     @Autowired
@@ -146,6 +150,8 @@ public class DeviceServiceImpl implements IDeviceService {
     @Autowired
     private DeviceMapper deviceMapper;
     @Resource
+    private ProductMapper productMapper;
+    @Resource
     private PlatformDeviceMappingMapper platformDeviceMappingMapper;
     @Autowired
     private DeviceUserMapper deviceUserMapper;
@@ -2374,4 +2380,149 @@ public class DeviceServiceImpl implements IDeviceService {
         return deviceMapper.selectSerialNumbersByProductId(productId);
     }
 
+    /**
+     * 查询树形设备列表（网关设备可展开显示子设备）
+     *
+     * @param device 查询条件
+     * @return 树形设备列表
+     */
+    @Override
+    public List<DeviceTreeVO> selectDeviceTreeList(Device device) {
+        long startTime = System.currentTimeMillis();
+        // 1. 轻量查询所有设备（包含网关和普通设备），只取树所需字段，避开逐行关联子查询
+        List<DeviceShortOutput> allDevices = deviceMapper.selectDeviceTreeBaseList(device);
+
+        // 2. 收集网关设备ID，一次批量查询所有网关-子设备关系（替代逐网关循环查询）
+        List<Long> gatewayIds = allDevices.stream()
+                .filter(d -> d.getDeviceType() != null && d.getDeviceType() == 2)
+                .map(DeviceShortOutput::getDeviceId)
+                .collect(Collectors.toList());
+
+        Map<Long, List<Long>> gatewaySubDeviceMap = new HashMap<>();
+        Set<Long> allSubDeviceIds = new HashSet<>();
+        for (List<Long> batch : partitionList(gatewayIds, SQL_IN_BATCH_SIZE)) {
+            for (SubGateway relation : subGatewayMapper.selectSubGatewayListByGwDeviceIds(batch)) {
+                gatewaySubDeviceMap.computeIfAbsent(relation.getGwDeviceId(), k -> new ArrayList<>())
+                        .add(relation.getSubDeviceId());
+                allSubDeviceIds.add(relation.getSubDeviceId());
+            }
+        }
+
+        // 3. 批量查询子设备信息（轻量查询只查网关/直连设备，子设备需单独查）+ 一次性批量查询产品名称
+        Map<Long, DeviceShortOutput> subDeviceMap = new HashMap<>();
+        if (!allSubDeviceIds.isEmpty()) {
+            List<Device> subDevices = new ArrayList<>();
+            for (List<Long> batch : partitionList(new ArrayList<>(allSubDeviceIds), SQL_IN_BATCH_SIZE)) {
+                subDevices.addAll(deviceMapper.selectDeviceListByDeviceIds(batch));
+            }
+            subDeviceMap = buildSubDeviceShortMap(subDevices);
+        }
+
+        // 4. 合并设备映射：网关/直连设备 + 子设备
+        Map<Long, DeviceShortOutput> deviceMap = allDevices.stream()
+                .collect(Collectors.toMap(DeviceShortOutput::getDeviceId, d -> d, (a, b) -> a));
+        deviceMap.putAll(subDeviceMap); // 添加子设备
+
+        // 5. 构建树形结构（用 Set 判断子设备归属，避免嵌套遍历扫描）
+        List<DeviceTreeVO> treeList = new ArrayList<>();
+        for (DeviceShortOutput d : allDevices) {
+            Integer deviceType = d.getDeviceType();
+
+            // 网关设备
+            if (deviceType != null && deviceType == 2) {
+                DeviceTreeVO gatewayNode = buildDeviceTreeVO(d, false);
+
+                // 添加子设备
+                List<Long> subDeviceIds = gatewaySubDeviceMap.get(d.getDeviceId());
+                if (subDeviceIds != null && !subDeviceIds.isEmpty()) {
+                    List<DeviceTreeVO> children = new ArrayList<>();
+                    for (Long subId : subDeviceIds) {
+                        DeviceShortOutput subDevice = deviceMap.get(subId);
+                        if (subDevice != null) {
+                            DeviceTreeVO childNode = buildDeviceTreeVO(subDevice, true);
+                            childNode.setFullPath(d.getDeviceName() + " / " + (subDevice.getDeviceName() != null ? subDevice.getDeviceName() : subDevice.getSerialNumber()));
+                            children.add(childNode);
+                        }
+                    }
+                    gatewayNode.setChildren(children);
+                }
+                treeList.add(gatewayNode);
+            }
+            // 直连设备或摄像头（不在网关下）
+            else if (deviceType == null || deviceType == 1 || deviceType == 3) {
+                if (!allSubDeviceIds.contains(d.getDeviceId())) {
+                    DeviceTreeVO node = buildDeviceTreeVO(d, true);
+                    treeList.add(node);
+                }
+            }
+        }
+        log.info("树形列表统计时间：{}", System.currentTimeMillis() - startTime);
+
+        return treeList;
+    }
+
+    /**
+     * 子设备列表转 DeviceShortOutput 映射，产品名称一次批量查询（替代逐设备查询产品）
+     */
+    private Map<Long, DeviceShortOutput> buildSubDeviceShortMap(List<Device> subDevices) {
+        Set<Long> productIds = subDevices.stream()
+                .map(Device::getProductId)
+                .filter(Objects::nonNull)
+                .collect(Collectors.toSet());
+        Map<Long, String> productNameMap = new HashMap<>();
+        for (List<Long> batch : partitionList(new ArrayList<>(productIds), SQL_IN_BATCH_SIZE)) {
+            for (Product product : productMapper.selectProductListByProductIds(batch)) {
+                productNameMap.put(product.getProductId(), product.getProductName());
+            }
+        }
+
+        Map<Long, DeviceShortOutput> subDeviceMap = new HashMap<>();
+        for (Device sub : subDevices) {
+            DeviceShortOutput shortOutput = new DeviceShortOutput();
+            shortOutput.setDeviceId(sub.getDeviceId());
+            shortOutput.setDeviceName(sub.getDeviceName());
+            shortOutput.setSerialNumber(sub.getSerialNumber());
+            shortOutput.setProductId(sub.getProductId());
+            shortOutput.setDeviceType(sub.getDeviceType());
+            shortOutput.setStatus(sub.getStatus());
+            if (sub.getProductId() != null) {
+                shortOutput.setProductName(productNameMap.get(sub.getProductId()));
+            }
+            subDeviceMap.put(sub.getDeviceId(), shortOutput);
+        }
+        return subDeviceMap;
+    }
+
+    /**
+     * 将列表按固定大小切分，用于控制 SQL IN 子句长度
+     */
+    private static <T> List<List<T>> partitionList(List<T> list, int size) {
+        List<List<T>> parts = new ArrayList<>();
+        for (int i = 0; i < list.size(); i += size) {
+            parts.add(new ArrayList<>(list.subList(i, Math.min(i + size, list.size()))));
+        }
+        return parts;
+    }
+
+    /**
+     * 构建DeviceTreeVO对象
+     */
+    private DeviceTreeVO buildDeviceTreeVO(DeviceShortOutput d, boolean isLeaf) {
+        DeviceTreeVO vo = new DeviceTreeVO();
+        vo.setDeviceId(d.getDeviceId());
+        vo.setDeviceName(d.getDeviceName());
+        vo.setSerialNumber(d.getSerialNumber());
+        vo.setProductId(d.getProductId());
+        vo.setProductName(d.getProductName());
+        vo.setDeviceType(d.getDeviceType());
+        vo.setStatus(d.getStatus());
+        vo.setIsLeaf(isLeaf);
+        if (d.getDeviceName() != null) {
+            vo.setFullPath(d.getDeviceName());
+        } else {
+            vo.setFullPath(d.getSerialNumber());
+        }
+        return vo;
+    }
+
 }

fastbee-service/fastbee-iot-service/src/main/resources/mapper/iot/DeviceMapper.xml

@@ -419,18 +419,8 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         update iot_device set things_model_value=#{stringValue} where device_id = #{deviceId}
     </update>
 
-    <select id="selectDeviceShortList" parameterType="com.fastbee.iot.domain.Device" resultMap="DeviceShortResult">
-        select d.device_id, d.device_name, p.product_id, p.product_name,p.device_type,
-            d.tenant_id, d.tenant_name, d.serial_number,d.gw_dev_code,
-            d.firmware_version, d.status,d.rssi,d.is_shadow,d.is_simulate ,d.location_way,
-            d.things_model_value, d.active_time,d.create_time, if(null = d.img_url or '' = d.img_url, p.img_url, d.img_url) as img_url,
-            d.longitude, d.latitude,
-            case
-               when (select count(device_id) from iot_device_share du where du.device_id = d.device_id and du.user_id = #{tenantId}) then 0
-               else 1
-               end as is_owner,
-            (select count(1) from iot_device d1 where d1.gw_dev_code = d.serial_number) as sub_device_count,
-        p.protocol_code,p.transport,p.guid,d.project_id
+    <!-- 设备简短列表的 FROM/WHERE 共享片段（含权限过滤，供 selectDeviceShortList 与 selectDeviceTreeBaseList 复用） -->
+    <sql id="selectDeviceShortListJoinWhere">
         from iot_device d
         left join iot_product p on p.product_id=d.product_id
         <if test="groupId != null and groupId !=0  "> left join iot_device_group g on g.device_id=d.device_id </if>
@@ -468,6 +458,28 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         </where>
         group by d.device_id,d.tenant_id
         order by d.create_time desc
+    </sql>
+
+    <select id="selectDeviceShortList" parameterType="com.fastbee.iot.domain.Device" resultMap="DeviceShortResult">
+        select d.device_id, d.device_name, p.product_id, p.product_name,p.device_type,
+            d.tenant_id, d.tenant_name, d.serial_number,d.gw_dev_code,
+            d.firmware_version, d.status,d.rssi,d.is_shadow,d.is_simulate ,d.location_way,
+            d.things_model_value, d.active_time,d.create_time, if(null = d.img_url or '' = d.img_url, p.img_url, d.img_url) as img_url,
+            d.longitude, d.latitude,
+            case
+               when (select count(device_id) from iot_device_share du where du.device_id = d.device_id and du.user_id = #{tenantId}) then 0
+               else 1
+               end as is_owner,
+            (select count(1) from iot_device d1 where d1.gw_dev_code = d.serial_number) as sub_device_count,
+        p.protocol_code,p.transport,p.guid,d.project_id
+        <include refid="selectDeviceShortListJoinWhere"/>
+    </select>
+
+    <!-- 树形设备列表专用轻量查询：只取树所需字段，避开 is_owner/sub_device_count 逐行关联子查询 -->
+    <select id="selectDeviceTreeBaseList" parameterType="com.fastbee.iot.domain.Device" resultMap="DeviceShortResult">
+        select d.device_id, d.device_name, d.serial_number, d.status, d.tenant_id,
+               p.product_id, p.product_name, p.device_type
+        <include refid="selectDeviceShortListJoinWhere"/>
     </select>
 
     <select id="selectDeviceShortStatistic" parameterType="com.fastbee.iot.domain.Device" resultType="com.fastbee.iot.model.DeviceStatistic">

fastbee-service/fastbee-iot-service/src/main/resources/mapper/iot/SubGatewayMapper.xml

@@ -133,6 +133,15 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         where gw_device_id = #{gwDeviceId}
     </select>
 
+    <select id="selectSubGatewayListByGwDeviceIds" resultMap="GatewayResult">
+        select id, gw_device_id, sub_device_id, slave_id
+        from iot_sub_gateway
+        where gw_device_id in
+        <foreach collection="gwDeviceIdList" item="gwDeviceId" open="(" separator="," close=")">
+            #{gwDeviceId}
+        </foreach>
+    </select>
+
     <select id="getIsSelectGateSubDevice" parameterType="com.fastbee.iot.model.gateWay.GateSubDeviceVO"
             resultMap="GatewaySubDeviceResult">
         select d.device_id,d.serial_number,d.device_name

generate_professional_templates.py

@@ -0,0 +1,316 @@
+#!/usr/bin/env python3
+"""
+专业报告模版生成脚本 V2.2
+修复循环表格语法（poi-tl 需要标记行 + 模板行的结构）
+"""
+
+from docx import Document
+from docx.shared import Pt, Cm
+from docx.enum.text import WD_ALIGN_PARAGRAPH
+from docx.enum.table import WD_TABLE_ALIGNMENT
+from docx.oxml.ns import qn
+from docx.oxml import OxmlElement
+import os
+
+
+def set_font(run, name='宋体', size=12, bold=False):
+    """设置字体"""
+    run.font.name = name
+    run._element.rPr.rFonts.set(qn('w:eastAsia'), name)
+    run.font.size = Pt(size)
+    run.bold = bold
+
+
+def add_heading(doc, text, size=14):
+    """添加章节标题"""
+    para = doc.add_paragraph()
+    run = para.add_run(text)
+    set_font(run, '黑体', size, bold=True)
+    para.paragraph_format.space_before = Pt(12)
+    para.paragraph_format.space_after = Pt(6)
+    return para
+
+
+def add_body(doc, text, indent=True):
+    """添加正文段落"""
+    para = doc.add_paragraph()
+    run = para.add_run(text)
+    set_font(run, '宋体', 12)
+    if indent:
+        para.paragraph_format.first_line_indent = Cm(0.74)
+    return para
+
+
+def add_label_para(doc, label, value):
+    """添加 标签：值 段落"""
+    para = doc.add_paragraph()
+    label_run = para.add_run(label)
+    set_font(label_run, '宋体', 12, bold=True)
+    value_run = para.add_run(value)
+    set_font(value_run, '宋体', 12)
+    return para
+
+
+def set_cell_background(cell, color):
+    """设置单元格背景色"""
+    shading = OxmlElement('w:shd')
+    shading.set(qn('w:val'), 'clear')
+    shading.set(qn('w:fill'), color)
+    cell._tc.get_or_add_tcPr().append(shading)
+
+
+def set_cell_vertical_center(cell):
+    """单元格内容垂直居中"""
+    vAlign = OxmlElement('w:vAlign')
+    vAlign.set(qn('w:val'), 'center')
+    cell._tc.get_or_add_tcPr().append(vAlign)
+
+
+def style_header_cell(cell, bg_color='DCE6F1'):
+    """表头单元格样式：加粗 + 居中 + 浅蓝底纹 + 垂直居中"""
+    set_cell_background(cell, bg_color)
+    set_cell_vertical_center(cell)
+    cell.paragraphs[0].alignment = WD_ALIGN_PARAGRAPH.CENTER
+    for run in cell.paragraphs[0].runs:
+        run.bold = True
+
+
+def style_body_cell(cell, align=WD_ALIGN_PARAGRAPH.CENTER):
+    """数据单元格样式：垂直居中"""
+    set_cell_vertical_center(cell)
+    cell.paragraphs[0].alignment = align
+
+
+def set_table_widths(table, widths_cm):
+    """设置表格列宽（厘米）"""
+    for row in table.rows:
+        for i, width in enumerate(widths_cm):
+            if i < len(row.cells):
+                row.cells[i].width = Cm(width)
+
+
+def create_professional_template(template_name, device_type, template_dir):
+    """创建专业报告模版"""
+
+    doc = Document()
+
+    # 页面设置：A4 + 标准页边距
+    section = doc.sections[0]
+    section.page_width = Cm(21.0)
+    section.page_height = Cm(29.7)
+    section.left_margin = Cm(2.54)
+    section.right_margin = Cm(2.54)
+    section.top_margin = Cm(2.54)
+    section.bottom_margin = Cm(2.54)
+
+    # 设置文档默认样式：宋体小四、1.5 倍行距
+    style = doc.styles['Normal']
+    style.font.name = '宋体'
+    style._element.rPr.rFonts.set(qn('w:eastAsia'), '宋体')
+    style.font.size = Pt(12)
+    style.paragraph_format.line_spacing = 1.5
+
+    # ===== 1. 标题 =====
+    title = doc.add_paragraph()
+    title.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    run = title.add_run(f'{device_type}监测分析报告')
+    set_font(run, '黑体', 18, bold=True)
+    title.paragraph_format.space_after = Pt(12)
+
+    # ===== 2. 基本信息 =====
+    info_para = doc.add_paragraph()
+    r1 = info_para.add_run('报告编号：')
+    set_font(r1, '宋体', 12, bold=True)
+    r2 = info_para.add_run('{{report.no}}')
+    set_font(r2, '宋体', 12)
+    r3 = info_para.add_run('    生成时间：')
+    set_font(r3, '宋体', 12, bold=True)
+    r4 = info_para.add_run('{{report.generatedAt}}')
+    set_font(r4, '宋体', 12)
+
+    add_label_para(doc, '报告周期：', '{{report.periodDesc}}')
+    add_label_para(doc, '设备信息：', '设备名称 {{device.name}}｜设备编号 {{device.serialNumber}}｜所属产品 {{device.productName}}')
+    add_label_para(doc, '监测指标：', '{{device.metricName}}')
+    add_label_para(doc, '控制值：', '{{controlValue}} {{controlValueUnit}}')
+
+    # ===== 3. 项目概况 =====
+    add_heading(doc, '一、项目概况')
+    add_body(doc, '{{summary}}')
+
+    # ===== 4. 安全评估 =====
+    add_heading(doc, '二、安全评估')
+    add_label_para(doc, '安全等级：', '{{safetyLevel}}')
+    add_label_para(doc, '评估说明：', '{{safetyDescription}}')
+
+    # ===== 5. 统计指标 =====
+    add_heading(doc, '三、统计指标')
+
+    table = doc.add_table(rows=10, cols=2)
+    table.style = 'Table Grid'
+    table.alignment = WD_TABLE_ALIGNMENT.CENTER
+
+    header_cells = table.rows[0].cells
+    header_cells[0].text = '统计指标'
+    header_cells[1].text = '数值'
+    style_header_cell(header_cells[0])
+    style_header_cell(header_cells[1])
+
+    metrics = [
+        ('当前值', '{{analysis.statistics.currentWithUnit}}'),
+        ('初始值', '{{analysis.statistics.initialWithUnit}}'),
+        ('最大值', '{{analysis.statistics.maxWithUnit}}'),
+        ('最小值', '{{analysis.statistics.minWithUnit}}'),
+        ('平均值', '{{analysis.statistics.avgWithUnit}}'),
+        ('中位数', '{{analysis.statistics.medianWithUnit}}'),
+        ('变化量', '{{analysis.statistics.deltaWithUnit}}'),
+        ('累计变化', '{{analysis.statistics.totalDeltaWithUnit}}'),
+        ('数据量', '{{analysis.statistics.count}}'),
+    ]
+
+    for i, (label, value) in enumerate(metrics, start=1):
+        row = table.rows[i]
+        row.cells[0].text = label
+        row.cells[1].text = value
+        style_body_cell(row.cells[0])
+        style_body_cell(row.cells[1])
+
+    set_table_widths(table, [4.5, 11.0])
+
+    # ===== 6. 测点数据（循环表格） =====
+    add_heading(doc, '四、测点数据')
+
+    # poi-tl LoopRowTableRenderPolicy 需要的结构：
+    # 第1行：表头
+    # 第2行：{{listName}} 标记行（可以是空单元格）
+    # 第3行：模板行，使用 [field] 语法
+    points_table = doc.add_table(rows=3, cols=8)
+    points_table.style = 'Table Grid'
+    points_table.alignment = WD_TABLE_ALIGNMENT.CENTER
+
+    # 表头
+    points_headers = ['测点', '初始值', '当前值', '变化量', '变化速率', '最大值', '最小值', '预警状态']
+    points_header_row = points_table.rows[0]
+    for i, header in enumerate(points_headers):
+        points_header_row.cells[i].text = header
+        style_header_cell(points_header_row.cells[i])
+
+    # 标记行：{{metricPoints}}
+    points_marker_row = points_table.rows[1]
+    points_marker_row.cells[0].text = '{{metricPoints}}'
+
+    # 模板行：[field] 语法
+    points_data_row = points_table.rows[2]
+    points_data = [
+        '[modelName]',
+        '[initialValue]',
+        '[currentValue]',
+        '[changeValue]',
+        '[changeRate]',
+        '[maxValue]',
+        '[minValue]',
+        '[warningStatus]',
+    ]
+    for i, data in enumerate(points_data):
+        points_data_row.cells[i].text = data
+        style_body_cell(points_data_row.cells[i])
+
+    set_table_widths(points_table, [2.6, 1.84, 1.84, 1.84, 1.84, 1.84, 1.84, 1.84])
+
+    # ===== 7. 趋势分析 =====
+    add_heading(doc, '五、趋势分析')
+    add_body(doc, '{{analysis.trend.description}}')
+
+    # ===== 8. 数据质量 =====
+    add_heading(doc, '六、数据质量')
+    add_body(doc, '{{analysis.quality.description}}')
+
+    # ===== 9. 预警状态 =====
+    add_heading(doc, '七、预警状态')
+    add_label_para(doc, '状态：', '{{analysis.warning.status}}')
+    add_body(doc, '{{analysis.warning.description}}', indent=False)
+
+    # ===== 10. 时程曲线（主指标 + 分组指标） =====
+    add_heading(doc, '八、时程曲线')
+
+    chart_para1 = doc.add_paragraph()
+    chart_para1.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    chart_para1.add_run('{{@charts.timeSeriesChart}}')
+
+    chart_para2 = doc.add_paragraph()
+    chart_para2.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    chart_para2.add_run('{{@charts.chart2}}')
+
+    chart_para3 = doc.add_paragraph()
+    chart_para3.alignment = WD_ALIGN_PARAGRAPH.CENTER
+    chart_para3.add_run('{{@charts.chart3}}')
+
+    # ===== 11. 专业分析建议 =====
+    add_heading(doc, '九、专业分析建议')
+    add_body(doc, '{{professionalAdvice}}')
+
+    # ===== 12. 结论（循环表格） =====
+    add_heading(doc, '十、结论')
+
+    # poi-tl LoopRowTableRenderPolicy 结构
+    conclusion_table = doc.add_table(rows=3, cols=2)
+    conclusion_table.style = 'Table Grid'
+    conclusion_table.alignment = WD_TABLE_ALIGNMENT.CENTER
+
+    # 表头
+    conclusion_header_row = conclusion_table.rows[0]
+    conclusion_header_row.cells[0].text = '序号'
+    conclusion_header_row.cells[1].text = '结论内容'
+    style_header_cell(conclusion_header_row.cells[0])
+    style_header_cell(conclusion_header_row.cells[1])
+
+    # 标记行
+    conclusion_marker_row = conclusion_table.rows[1]
+    conclusion_marker_row.cells[0].text = '{{conclusions}}'
+
+    # 模板行
+    conclusion_data_row = conclusion_table.rows[2]
+    conclusion_data_row.cells[0].text = '[seq]'
+    conclusion_data_row.cells[1].text = '[text]'
+    style_body_cell(conclusion_data_row.cells[0])
+    style_body_cell(conclusion_data_row.cells[1], WD_ALIGN_PARAGRAPH.LEFT)
+
+    set_table_widths(conclusion_table, [1.5, 14.0])
+
+    # 保存文档
+    output_path = os.path.join(template_dir, f'{template_name}_V2.docx')
+    doc.save(output_path)
+    print(f'已生成模版: {output_path}')
+    return output_path
+
+
+def main():
+    """主函数"""
+    template_dir = '/Users/admin/IdeaProjects/fastbee/fastbee-report/src/main/resources/templates'
+
+    device_types = {
+        'DEVICE_CRACK_METER': '裂缝计',
+        'DEVICE_DEEP_DISPLACEMENT': '深部位移',
+        'DEVICE_AXIAL_FORCE': '轴力/应力',
+        'DEVICE_STATIC_LEVEL': '静力水准',
+        'DEVICE_VIBRATING_WIRE': '振弦',
+        'DEVICE_STRAIN_GAUGE': '应变计',
+        'DEVICE_WATER_LEVEL': '水位计',
+        'DEVICE_RANGING_METER': '测距仪',
+        'DEVICE_INCLINOMETER': '倾角计',
+        'DEVICE_THERMOMETER': '温度计',
+        'DEVICE_RAIN_GAUGE': '雨量计',
+    }
+
+    print('开始生成专业报告模版 V2.2（修复循环表格语法）...')
+    print(f'模版目录: {template_dir}')
+    print()
+
+    for template_name, device_type in device_types.items():
+        create_professional_template(template_name, device_type, template_dir)
+
+    print()
+    print('所有模版生成完成！')
+
+
+if __name__ == '__main__':
+    main()

sql/fastbee-report.sql

@@ -146,7 +146,9 @@ CREATE TABLE `report_record` (
 
 -- ------------------------------------------------------------
 -- 3. oss_config：MinIO 默认配置（未购买云 OSS → 自建 MinIO）
---    注意：endpoint 需改为实际 MinIO 部署地址；下载统一走后端代理，桶保持私有（access_policy=0）
+--    endpoint：后端连接 MinIO 的 S3 API 地址（若后端与 MinIO 同机可改为 http://127.0.0.1:9000）
+--    domain：为空时 getUrl() 返回 http://<endpoint>/<bucketName>；可配置 CDN/公网域名生成更友好的 URL
+--    注意：端口 9000 需在安全组/防火墙放行；下载统一走后端代理，桶保持私有（access_policy=0）
 -- ------------------------------------------------------------
 UPDATE `oss_config` SET `status` = '1' WHERE `config_key` IN ('aliyun', 'qiniu');
 
@@ -155,7 +157,7 @@ INSERT IGNORE INTO `oss_config`
  endpoint, domain, is_https, region, access_policy, status, del_flag, create_by, create_time, update_by, update_time, remark)
 VALUES
 (1, 'admin', 'minio', 'yack-superme', 'yack-minio20260816', 'fastbee', 'report',
- 'http://127.0.0.1:9000', '', 'N', '', '0', '0', '0', 'admin', NOW(), 'admin', NOW(), 'MinIO默认存储');
+ 'http://47.121.180.229:9000', '', 'N', '', '0', '0', '0', 'admin', NOW(), 'admin', NOW(), 'MinIO默认存储');
 
 -- ------------------------------------------------------------
 -- 4. 历史报表菜单与权限（数据中心 3343 下新增）

yack-web/src/api/iot/device.js

@@ -210,3 +210,12 @@ export function listThingsModel(query) {
         params: query,
     });
 }
+
+// 查询树形设备列表（网关可展开子设备）
+export function listDeviceTree(query) {
+    return request({
+        url: '/iot/device/treeList',
+        method: 'get',
+        params: query,
+    });
+}

yack-web/src/assets/icons/svg/WORD.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg class="icon" width="200px" height="200.00px" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg"><path d="M535.119473 0h69.599248v95.247413C729.226717 96.331138 853.614299 93.92286 977.881468 96.331138a40.459078 40.459078 0 0 1 44.914393 45.516463c2.047037 234.566322 0 469.614299 1.204139 703.819379-1.204139 24.082785 2.287865 50.694262-11.318909 72.248354-16.978363 12.041392-38.893697 10.837253-58.761994 12.041392h-349.200376V1023.518344h-72.248354C354.980245 990.886171 177.490122 960.541863 0 928.752587V95.488241C178.33302 63.578551 356.786453 32.511759 535.119473 0z" fill="#707070" /><path d="M604.718721 131.010348H988.598307v761.979304H604.718721v-95.247413h302.479774v-48.165569H604.718721v-59.002822h302.479774v-48.16557H604.718721v-59.002822h302.479774v-48.165569H604.718721v-60.206961h302.479774V428.673565H604.718721v-60.206961h302.479774v-46.96143H604.718721v-59.604892h302.479774V214.336783H604.718721zM240.827846 341.373471c22.156162-1.324553 44.19191-2.287865 66.348071-3.492003 15.533396 80.4365 31.30762 160.632173 48.165569 240.827845 13.125118-82.724365 27.695202-165.087488 41.783632-247.571025 23.239887-0.842897 46.479774-2.167451 69.719661-3.612418-26.370649 115.356538-49.369708 231.796802-78.148636 346.430856-19.386642 10.355597-48.165569 0-71.52587 1.204139C301.034807 596.169332 283.093133 517.779868 269.245532 438.667921c-13.606773 76.944497-31.30762 153.16651-46.841016 229.508937-22.39699-1.204139-44.793979-2.528692-67.311383-4.094073-19.266228-104.760113-42.024459-208.918156-60.206962-313.919097 19.868297-0.963311 39.857008-1.806209 60.206962-2.528693 12.041392 75.860771 25.648166 151.360301 36.124177 227.341487 16.135466-77.907808 32.873001-155.695202 49.610536-233.603011z" fill="#FFFFFF" /></svg>

yack-web/src/views/bigScreen/home.scss

@@ -1365,3 +1365,69 @@
     width: 100%;
     margin-top: 8px;
 }
+
+/* ========== 分析模式操作按钮 ========== */
+.analysis-action-btns {
+    display: grid;
+    grid-template-columns: 1fr;
+    gap: 10px;
+    margin-top: 4px;
+}
+
+.action-btn {
+    appearance: none;
+    -webkit-appearance: none;
+    outline: none;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    gap: 7px;
+    height: 36px;
+    border-radius: 3px;
+    color: #fff;
+    font-size: 13px;
+    font-weight: 600;
+    letter-spacing: 2px;
+    cursor: pointer;
+    transition: all .18s ease;
+    user-select: none;
+
+    i {
+        font-size: 15px;
+    }
+
+    &:disabled {
+        opacity: .42;
+        cursor: not-allowed;
+        box-shadow: none;
+    }
+
+    &.is-loading {
+        opacity: .75;
+        cursor: wait;
+    }
+}
+
+.action-btn--primary {
+    border: 1px solid rgba(64, 158, 255, .7);
+    background: linear-gradient(180deg, #409EFF, #337ecc);
+    box-shadow: 0 0 12px rgba(64, 158, 255, .25), inset 0 0 8px rgba(255, 255, 255, .08);
+
+    &:not(:disabled):hover {
+        border-color: rgba(102, 185, 255, .85);
+        background: linear-gradient(180deg, #66b1ff, #409EFF);
+        box-shadow: 0 0 16px rgba(64, 158, 255, .4), inset 0 0 8px rgba(255, 255, 255, .12);
+    }
+}
+
+.action-btn--success {
+    border: 1px solid rgba(103, 194, 58, .7);
+    background: linear-gradient(180deg, #67C23A, #529b2e);
+    box-shadow: 0 0 12px rgba(103, 194, 58, .2), inset 0 0 8px rgba(255, 255, 255, .08);
+
+    &:not(:disabled):hover {
+        border-color: rgba(133, 220, 88, .85);
+        background: linear-gradient(180deg, #85ce61, #67C23A);
+        box-shadow: 0 0 16px rgba(103, 194, 58, .35), inset 0 0 8px rgba(255, 255, 255, .12);
+    }
+}

yack-web/src/views/bigScreen/home.vue

@@ -228,16 +228,18 @@
                             <div class="panel-title">分析条件</div>
                             <el-form label-position="top" size="mini" class="analysis-form">
                                 <el-form-item label="设备">
-                                    <el-select v-model="analysisQuery.deviceId" filterable remote clearable placeholder="请选择设备（支持搜索）"
-                                        :remote-method="searchAnalysisDevices" :loading="analysisDeviceSearchLoading"
-                                        @visible-change="onAnalysisDeviceVisible" @change="handleAnalysisDeviceChange">
-                                        <el-option
-                                            v-for="device in analysisDeviceOptions"
-                                            :key="device.deviceId"
-                                            :label="device.deviceName || device.serialNumber"
-                                            :value="device.deviceId"
-                                        />
-                                    </el-select>
+                                    <el-cascader
+                                        v-model="analysisQuery.deviceId"
+                                        :options="deviceTreeOptions"
+                                        :props="cascaderProps"
+                                        :show-all-levels="true"
+                                        placeholder="请选择设备"
+                                        filterable
+                                        clearable
+                                        :loading="deviceTreeLoading"
+                                        @change="handleDeviceTreeChange"
+                                        style="width: 100%;"
+                                    />
                                 </el-form-item>
                                 <el-form-item label="时间范围">
                                     <!-- 预设时间按钮组 -->
@@ -304,14 +306,24 @@
                                         @change="handleCustomTimeChange"
                                     />
                                 </el-form-item>
-                                <el-button type="primary" icon="el-icon-search" :loading="analysisLoading" @click="runAnalysis">查询数据和曲线</el-button>
-                                <el-button
-                                    type="success"
-                                    icon="el-icon-document"
-                                    :loading="reportLoading"
-                                    :disabled="!analysisQuery.deviceId || !analysisQuery.timeRange || analysisQuery.timeRange.length < 2"
-                                    @click="handleGenerateReport"
-                                >生成并导出报表</el-button>
+                                <div class="analysis-action-btns">
+                                    <button type="button" class="action-btn action-btn--primary" :class="{ 'is-loading': analysisLoading }" :disabled="analysisLoading" @click="runAnalysis">
+                                        <i v-if="!analysisLoading" class="el-icon-search"></i>
+                                        <i v-else class="el-icon-loading"></i>
+                                        <span>查询数据和曲线</span>
+                                    </button>
+                                    <button
+                                        type="button"
+                                        class="action-btn action-btn--success"
+                                        :class="{ 'is-loading': reportLoading }"
+                                        :disabled="!analysisQuery.deviceId || !analysisQuery.timeRange || analysisQuery.timeRange.length < 2 || reportLoading"
+                                        @click="handleGenerateReport"
+                                    >
+                                        <i v-if="!reportLoading" class="el-icon-document"></i>
+                                        <i v-else class="el-icon-loading"></i>
+                                        <span>生成并导出报表</span>
+                                    </button>
+                                </div>
                             </el-form>
                         </div>
                         <div class="panel-card analysis-card">
@@ -393,7 +405,7 @@ import { getUserProfile } from '@/api/system/user';
 import { saveAs } from 'file-saver';
 import { generateDeviceReport, downloadReportRecord } from '@/api/iot/report';
 import { blobValidate } from '@/utils/ruoyi';
-import { listDeviceShort, getDeviceShortStatistic, getDeviceStatistic, listThingsModel } from '@/api/iot/device';
+import { listDeviceShort, listDeviceTree, getDeviceShortStatistic, getDeviceStatistic, listThingsModel } from '@/api/iot/device';
 import { listAlertLog } from '@/api/iot/alertLog';
 import { getDataCenterDeviceHistory } from '@/api/data/center';
 import { listProject } from '@/api/iot/project';
@@ -448,6 +460,16 @@ export default {
             analysisDeviceOptions: [],
             selectedAnalysisDevice: null,
             analysisDeviceSearchLoading: false,
+            deviceTreeOptions: [],
+            deviceTreeLoading: false,
+            cascaderProps: {
+                value: 'deviceId',
+                label: 'deviceName',
+                children: 'children',
+                expandTrigger: 'hover',
+                checkStrictly: true, // 允许选择任意节点，在change中判断是否可选
+                emitPath: false,
+            },
             selectedProject: null,
             projectChart: null,
             deviceChart: null,
@@ -670,8 +692,10 @@ export default {
                     this.renderDashboardMap();
                 } else if (value === 'mapView') {
                     this.renderSatelliteMap();
-                } else {
+                } else if (value === 'analysis') {
                     this.resizeAnalysisChart();
+                    // 加载树形设备列表
+                    this.loadDeviceTree();
                 }
             });
         },
@@ -935,6 +959,96 @@ export default {
                     this.analysisDeviceSearchLoading = false;
                 });
         },
+        // 加载树形设备列表
+        loadDeviceTree() {
+            this.deviceTreeLoading = true;
+            const query = { showChild: true, entrance: 2 };
+            if (this.selectedProject) query.projectId = this.selectedProject.id;
+
+            listDeviceTree(query)
+                .then((res) => {
+
+                    if (res.code === 200) {
+                        this.deviceTreeOptions = this.processDeviceTree(res.data || []);
+
+                        // 检查网关设备
+                        const gateways = this.deviceTreeOptions.filter(d => !d.isLeaf);
+                        gateways.forEach((g, i) => {
+                            console.log(`  网关${i+1}: ${g.deviceName}, 子设备数量: ${g.children?.length || 0}`);
+                        });
+                    }
+                })
+                .catch((error) => {
+                    this.deviceTreeOptions = [];
+                })
+                .finally(() => {
+                    this.deviceTreeLoading = false;
+                });
+        },
+        // 处理设备树：保持原始数据结构
+        processDeviceTree(tree) {
+            return tree.map(node => {
+                // 网关节点：保持children，但标记为网关（用于后续判断）
+                if (!node.isLeaf) {
+                    return {
+                        ...node,
+                        label: '🌐 ' + (node.deviceName || node.serialNumber), // 添加网关图标
+                        children: node.children ? this.processDeviceTree(node.children) : []
+                    };
+                }
+                // 叶子节点：可选择，显示完整路径
+                return {
+                    ...node,
+                    label: node.fullPath || node.deviceName || node.serialNumber
+                };
+            });
+        },
+        // 处理树形设备选择变更
+        handleDeviceTreeChange(deviceId) {
+
+            // 查找选中的设备
+            const selectedDevice = this.findDeviceById(this.deviceTreeOptions, deviceId);
+
+            if (!selectedDevice) {
+                this.$message.error('设备信息异常，请重新选择');
+                return;
+            }
+
+            // 判断是否是网关设备
+            if (!selectedDevice.isLeaf) {
+                this.$message.warning('网关设备不能直接生成报告，请选择具体的监测设备');
+                this.analysisQuery.deviceId = null;
+                this.selectedAnalysisDevice = null; // 清空已选设备
+                this.identifierList = []; // 清空物模型列表
+                this.analysisLineList = []; // 清空历史数据
+                return;
+            }
+
+            // 直接使用树中找到的设备对象，而不是在扁平列表中查找
+            this.selectedAnalysisDevice = selectedDevice;
+            this.identifierList = [];
+            this.analysisLineList = [];
+
+            // 加载物模型
+            listThingsModel({ deviceId, pageNum: 1, pageSize: 9999 })
+                .then((res) => {
+                    if (res.code === 200) this.identifierList = res.rows || [];
+                })
+                .catch(() => {
+                    this.identifierList = [];
+                });
+        },
+        // 根据ID查找设备
+        findDeviceById(tree, deviceId) {
+            for (const node of tree) {
+                if (node.deviceId === deviceId) return node;
+                if (node.children) {
+                    const found = this.findDeviceById(node.children, deviceId);
+                    if (found) return found;
+                }
+            }
+            return null;
+        },
         onAnalysisDeviceVisible(visible) {
           if (visible) this.searchAnalysisDevices('');
         },
@@ -1435,16 +1549,22 @@ export default {
                 deviceId: device.deviceId,
                 startTime: moment(this.analysisQuery.timeRange[0]).format('YYYY-MM-DD HH:mm:ss'),
                 endTime: moment(this.analysisQuery.timeRange[1]).format('YYYY-MM-DD HH:mm:ss'),
-                templateCode: 'DEVICE_CRACK_METER_V1',
+                // 不传 templateCode，后端根据设备监测分类自动选择对应模版
                 format: 'WORD',
             })
                 .then((res) => {
                     if (res.code === 200) {
-                        const data = res.data || {};
-                        this.$message.success('报表生成成功，可在历史报表中查看');
-                        if (data.reportNo) {
-                            this.downloadReport(data);
-                        }
+                        // 使用弹框提示用户
+                        this.$alert('报表正在后台生成中，生成完成后可在历史报表中下载', '提交成功', {
+                            confirmButtonText: '查看历史报表',
+                            type: 'success',
+                            callback: action => {
+                                if (action === 'confirm') {
+                                    // 跳转到历史报表页面
+                                    this.$router.push({ path: '/dataCenter/reportHistory' }).catch(() => {});
+                                }
+                            }
+                        });
                     }
                 })
                 .finally(() => {

yack-web/src/views/dataCenter/analysis.vue

@@ -4,9 +4,18 @@
         <el-card style="margin-bottom: 12px">
             <el-form :model="queryParams" ref="queryForm" :inline="true" size="mini" label-width="68px" style="margin-bottom: -18px">
                 <el-form-item label="设备名称" prop="deviceId">
-                    <el-select v-model="queryParams.deviceId" placeholder="请选择设备" filterable @change="handleDeviceChange" style="width: 200px">
-                        <el-option v-for="item in deviceList" :key="item.deviceId" :label="item.deviceName" :value="item.deviceId"></el-option>
-                    </el-select>
+                    <el-cascader
+                        v-model="queryParams.deviceId"
+                        :options="deviceTreeOptions"
+                        :props="cascaderProps"
+                        :show-all-levels="true"
+                        placeholder="请选择设备"
+                        filterable
+                        clearable
+                        :loading="deviceTreeLoading"
+                        @change="handleDeviceTreeChange"
+                        style="width: 280px"
+                    />
                 </el-form-item>
                 <el-form-item label="时间范围" prop="dayDaterange">
                     <el-date-picker
@@ -148,7 +157,7 @@
 
 <script>
 import moment from 'moment';
-import { listDeviceShort, listThingsModel } from '@/api/iot/device.js';
+import { listDeviceShort, listDeviceTree, listThingsModel } from '@/api/iot/device.js';
 import { saveAs } from 'file-saver';
 import { generateDeviceReport, downloadReportRecord } from '@/api/iot/report';
 import { blobValidate } from '@/utils/ruoyi';
@@ -171,6 +180,16 @@ export default {
             pendingCount: 0,
             queried: false,
             deviceList: [],
+            deviceTreeOptions: [],
+            deviceTreeLoading: false,
+            cascaderProps: {
+                value: 'deviceId',
+                label: 'deviceName',
+                children: 'children',
+                expandTrigger: 'hover',
+                checkStrictly: true, // 允许选择任意节点，在change中判断是否可选
+                emitPath: false,
+            },
             identifierList: [],
             pickerOptions: {
                 shortcuts: [
@@ -205,6 +224,70 @@ export default {
             listDeviceShort({ showChild: true, pageNum: 1, pageSize: 9999 }).then((res) => {
                 if (res.code === 200) this.deviceList = res.rows;
             });
+            // 同时加载树形设备列表
+            this.loadDeviceTree();
+        },
+        // 加载树形设备列表
+        loadDeviceTree() {
+            this.deviceTreeLoading = true;
+            listDeviceTree({ showChild: true })
+                .then((res) => {
+                    if (res.code === 200) {
+                        this.deviceTreeOptions = this.processDeviceTree(res.data || []);
+                    }
+                })
+                .catch((error) => {
+                    console.error('加载设备树失败:', error);
+                    this.deviceTreeOptions = [];
+                })
+                .finally(() => {
+                    this.deviceTreeLoading = false;
+                });
+        },
+        // 处理设备树：保持原始数据结构
+        processDeviceTree(tree) {
+            return tree.map(node => {
+                // 网关节点：保持children，但标记为网关（用于后续判断）
+                if (!node.isLeaf) {
+                    return {
+                        ...node,
+                        label: '🌐 ' + (node.deviceName || node.serialNumber), // 添加网关图标
+                        children: node.children ? this.processDeviceTree(node.children) : []
+                    };
+                }
+                // 叶子节点：可选择，显示完整路径
+                return {
+                    ...node,
+                    label: node.fullPath || node.deviceName || node.serialNumber
+                };
+            });
+        },
+        // 处理树形设备选择变更
+        handleDeviceTreeChange(deviceId) {
+            console.log('选择的设备ID:', deviceId);
+
+            // 查找选中的设备
+            const selectedDevice = this.findDeviceById(this.deviceTreeOptions, deviceId);
+
+            // 判断是否是网关设备
+            if (selectedDevice && !selectedDevice.isLeaf) {
+                this.$message.warning('网关设备不能直接生成报告，请选择具体的监测设备');
+                this.queryParams.deviceId = null;
+                return;
+            }
+
+            this.handleDeviceChange(deviceId);
+        },
+        // 根据ID查找设备
+        findDeviceById(tree, deviceId) {
+            for (const node of tree) {
+                if (node.deviceId === deviceId) return node;
+                if (node.children) {
+                    const found = this.findDeviceById(node.children, deviceId);
+                    if (found) return found;
+                }
+            }
+            return null;
         },
         handleDeviceChange(val) {
             this.identifierList = [];
@@ -246,16 +329,22 @@ export default {
                 deviceId: this.queryParams.deviceId,
                 startTime: moment(this.queryParams.dayDaterange[0]).format('YYYY-MM-DD HH:mm:ss'),
                 endTime: moment(this.queryParams.dayDaterange[1]).format('YYYY-MM-DD HH:mm:ss'),
-                templateCode: 'DEVICE_CRACK_METER_V1',
+                // 不传 templateCode，后端根据设备监测分类自动选择对应模版
                 format: 'WORD',
             })
                 .then((res) => {
                     if (res.code === 200) {
-                        const data = res.data || {};
-                        this.$message.success('报表生成成功，可在历史报表中查看');
-                        if (data.reportNo) {
-                            this.downloadReport(data);
-                        }
+                        // 使用弹框提示用户
+                        this.$alert('报表正在后台生成中，生成完成后可在历史报表中下载', '提交成功', {
+                            confirmButtonText: '查看历史报表',
+                            type: 'success',
+                            callback: action => {
+                                if (action === 'confirm') {
+                                    // 跳转到历史报表页面
+                                    this.$router.push({ path: '/dataCenter/reportHistory' }).catch(() => {});
+                                }
+                            }
+                        });
                     }
                 })
                 .finally(() => {