2025.12.18 1. 动态溯源相关分析逻辑调整； 2. 走航报告接口参数调整；

feiyu02

23 小时以前 8eb584869b4fd4de0f51c93f2616f12e51df9193

 src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedSource.kt

@@ -1,7 +1,9 @@
package com.flightfeather.uav.biz.sourcetrace.model

import com.flightfeather.uav.biz.dataanalysis.model.ExceptionType
import com.flightfeather.uav.common.utils.DateUtil
import com.flightfeather.uav.common.utils.MapUtil
import com.flightfeather.uav.domain.entity.BaseRealTimeData
import com.flightfeather.uav.domain.entity.SceneInfo
import com.flightfeather.uav.domain.repository.SceneInfoRep
import com.flightfeather.uav.lightshare.bean.AreaVo
@@ -10,7 +12,6 @@
import com.flightfeather.uav.socket.eunm.FactorType
import org.springframework.beans.BeanUtils
import org.springframework.web.context.ContextLoader
import kotlin.math.round

/**
 * 污染来源
@@ -44,42 +45,44 @@
        // Fixme 2025.5.14: 污染源的坐标是高德地图坐标系（火星坐标系），而走航数据是WGS84坐标系
        // 按照区域检索内部污染源信息
        var result = mutableListOf<SceneInfo>()
        // 1. 首先按照四至范围从数据库初步筛选污染源，此处的区域坐标已转换为火星坐标系
        val polygonTmp = pollutedArea.polygon!!
        val fb = MapUtil.calFourBoundaries(polygonTmp)
        val sceneList = sceneInfoRep.findByCoordinateRange(fb)
        // 2. 再精确判断是否在反向溯源区域多边形内部
        sceneList.forEach {
            val point = it!!.longitude.toDouble() to it.latitude.toDouble()
            if (MapUtil.isPointInPolygon(point, polygonTmp)) {
                result.add(it)
            }
        }
        val polygonTmp = pollutedArea.polygon
        this.sceneList = emptyList()

        val closePolygonTmp = pollutedArea.closePolygon!!
        val closeFb = MapUtil.calFourBoundaries(closePolygonTmp)
        val closeSceneList = sceneInfoRep.findByCoordinateRange(closeFb)
        // 2. 再精确判断是否在反向溯源区域多边形内部
        closeSceneList.forEach {
            val point = it!!.longitude.toDouble() to it.latitude.toDouble()
            if (MapUtil.isPointInPolygon(point, closePolygonTmp)) {
                result.add(it)
        if (polygonTmp != null) {
            val fb = MapUtil.calFourBoundaries(polygonTmp)
            // 1. 首先按照四至范围从数据库初步筛选污染源，此处的区域坐标已转换为火星坐标系
            val sceneList = sceneInfoRep.findByCoordinateRange(fb)
            // 2. 再精确判断是否在反向溯源区域多边形内部
            sceneList.forEach {
                val point = it!!.longitude.toDouble() to it.latitude.toDouble()
                if (MapUtil.isPointInPolygon(point, polygonTmp)) {
                    result.add(it)
                }
            }
        }

        // 根据污染因子的量级，计算主要的污染场景类型，筛选结果
        val mainSceneType = calSceneType(pollutedData)
        if (mainSceneType != null) {
//            this.conclusion = mainSceneType.first
            // 3. 再统一检索近距离污染圆形区域内部的污染源
            val closePolygonTmp = pollutedArea.closePolygon!!
            val closeFb = MapUtil.calFourBoundaries(closePolygonTmp)
            val closeSceneList = sceneInfoRep.findByCoordinateRange(closeFb)
            closeSceneList.forEach {
                val point = it!!.longitude.toDouble() to it.latitude.toDouble()
                if (MapUtil.isPointInPolygon(point, closePolygonTmp)) {
                    result.add(it)
                }
            }
            // 4. 去重
            result = result.distinctBy { it.guid }.toMutableList()

            // 5. 根据污染因子的量级，计算主要的污染场景类型，筛选结果
            val mainSceneType = calSceneType(pollutedData)
            result = result.filter {
                val r = mainSceneType.second.find { s->
                val r = mainSceneType.find { s ->
                    s.value == it.typeId.toInt()
                }
                r != null
            }.toMutableList()
            this.sceneList = findClosestStation(sceneInfoRep, result)
        }

        this.sceneList = findClosestStation(sceneInfoRep, result)

        val txt = summaryTxt(pollutedData, this.sceneList!!)
        this.conclusion = txt
@@ -89,83 +92,43 @@
     * 计算可能的相关污染场景类型以及推理结论
     */
    @Throws(Exception::class)
    private fun calSceneType(pollutedData: PollutedData): Pair<String, List<SceneType>>? {
        var des: String? = null
    private fun calSceneType(pollutedData: PollutedData): List<SceneType> {
        val sceneTypes = mutableListOf<SceneType>()
        pollutedData.statisticMap.entries.forEach { s ->
            val res = when (s.key) {
                // 氮氧化合物，一般由于机动车尾气，同步计算CO
                FactorType.NO2 -> {
                    val coAvg = round(pollutedData.dataList.map { it.co!! }.average()) / 1000
                     "氮氧化合物偏高，CO的量级为${coAvg}mg/m³，一般由于机动车尾气造成，污染源以汽修、加油站为主" to
                            listOf(SceneType.TYPE6, SceneType.TYPE10, SceneType.TYPE17)
                FactorType.NO,
                FactorType.NO2,
                    -> {
                    listOf(SceneType.TYPE1, SceneType.TYPE6, SceneType.TYPE10, SceneType.TYPE17)
                }

                FactorType.CO ->  null

                FactorType.H2S ->  null

                FactorType.SO2 ->  null

                FactorType.O3 ->  null
                // a) pm2.5、pm10特别高，两者在各情况下同步展示，pm2.5占pm10的比重变化，比重越高，越有可能是餐饮
                // b) pm10特别高、pm2.5较高，大颗粒扬尘污染，只展示pm10，pm2.5占pm10的比重变化，工地为主
                FactorType.CO -> listOf(SceneType.TYPE6, SceneType.TYPE10, SceneType.TYPE17)
                FactorType.H2S -> null
                FactorType.SO2 -> null
                FactorType.O3 -> null
                FactorType.PM25,
                FactorType.PM10,
                    -> {
                    val pm25Avg = round(pollutedData.dataList.map { it.pm25!! }.average() * 10) / 10
                    val pm10Avg = round(pollutedData.dataList.map { it.pm10!! }.average() * 10) / 10
                    // 计算异常数据的pm2.5占pm10比重的均值
                    val percentageAvg = pollutedData.dataList.map {
                        it.pm25!! / it.pm10!!
                    }.average()
                    val str =
                        "PM2.5量级为${pm25Avg}μg/m³，PM10量级为${pm10Avg}μg/m³，PM2.5占PM10的比重为${round(percentageAvg * 100)}%"
                     if (percentageAvg > 0.666) {
                        "${str}，比重较大，污染源以餐饮为主，工地次之" to
                                listOf(
                                    SceneType.TYPE1,
                                    SceneType.TYPE2,
                                    SceneType.TYPE3,
                                    SceneType.TYPE14,
                                    SceneType.TYPE5
                                )
                    } else if (percentageAvg < 0.333) {
                        "${str}，比重较小，属于大颗粒扬尘污染，污染源以工地为主" to
                                listOf(
                                    SceneType.TYPE1,
                                    SceneType.TYPE2,
                                    SceneType.TYPE3,
                                    SceneType.TYPE14,
                                    SceneType.TYPE5
                                )
                    } else {
                        "${str}，污染源以餐饮、工地为主" to
                                listOf(
                                    SceneType.TYPE1,
                                    SceneType.TYPE2,
                                    SceneType.TYPE3,
                                    SceneType.TYPE14,
                                    SceneType.TYPE5
                                )
                    }
                }
                // c) VOC较高，同比计算pm2.5的量级，可能存在同步偏高（汽修、加油站）, 同步计算O3是否有高值
                // d) VOC较高，处于加油站（车辆拥堵情况），CO一般较高, 同步计算O3是否有高值
                FactorType.VOC -> {
                    val pm25Avg = round(pollutedData.dataList.map { it.pm25!! }.average() * 10) / 10
                    val coAvg = round(pollutedData.dataList.map { it.co!! }.average()) / 1000
                    val o3Avg = round(pollutedData.dataList.map { it.o3!! }.average() * 10) / 10
                     "VOC偏高，同时PM2.5量级为${pm25Avg}μg/m³，CO量级为${coAvg}mg/m³，O3量级为${o3Avg}μg/m³，污染源以汽修、加油站为主" to
                            listOf(SceneType.TYPE6, SceneType.TYPE17, SceneType.TYPE12)
                    listOf(
                        SceneType.TYPE1,
                        SceneType.TYPE2,
                        SceneType.TYPE3,
                        SceneType.TYPE14,
                        SceneType.TYPE5,
                        SceneType.TYPE18
                    )
                }

                else ->  null
                FactorType.VOC -> {
                    listOf(SceneType.TYPE5, SceneType.TYPE6, SceneType.TYPE17, SceneType.TYPE12, SceneType.TYPE18)
                }

                else -> null
            }
            des = res?.first
            res?.second?.let { sceneTypes.addAll(it) }
            res?.let { sceneTypes.addAll(it) }
        }
        return (des ?: "") to sceneTypes
        return sceneTypes.distinct()
    }

    /**
@@ -205,16 +168,45 @@
        }
    }

    /**
     * 溯源解析
     * @param pollutedData 污染数据
     * @param sceneList 风险源列表
     * @return 溯源描述
     */
    private fun summaryTxt(pollutedData: PollutedData, sceneList: List<SceneInfoVo>): String {
//        pollutedData.exception
//        pollutedData.selectedFactor?.main
        val st = DateUtil.instance.getTime(pollutedData.startTime)
        val et = DateUtil.instance.getTime(pollutedData.endTime)
        var txt =
            "在${st}至${et}之间，出现${pollutedData.exception}"
        pollutedData.statisticMap.entries.forEach {s ->
            txt += "，${s.key.des}最低值为${s.value.min}μg/m³，最高值为${s.value.max}μg/m³，均值为${s.value.avg}μg/m³"

        // 1. 描述异常发生的时间和异常类型
        var txt = "在${st}至${et}之间，出现${pollutedData.exception}${pollutedData.times}次"

        // 2. 描述异常数据的变化情况
        val statArr = mutableListOf<String>()
        pollutedData.statisticMap.entries.forEach { s ->
            val txtArr = mutableListOf<String>()
            s.value.excGroup?.forEach exception@{ p ->
                val preValue = p.getFirstDataValue()
                val curValue = p.getLastDataValue()
                val per = p.per?.times(100)
                val rate = p.rate
                if (preValue == null || curValue == null || per == null) return@exception
                when (pollutedData.exceptionType) {
                    // 量级突变
                    ExceptionType.TYPE4.value -> {
                        txtArr.add("从${preValue}μg/m³突变至${curValue}μg/m³，变化率为${per}%")
                    }
                    // 快速上升
                    ExceptionType.TYPE9.value -> {
                        txtArr.add("从${preValue}μg/m³快速上升至${curValue}μg/m³，变化速率为${rate}μg/m³/秒，变化率为${per}%")
                    }
                }
            }
            statArr.add("${s.key.getTxt()}量级${txtArr.joinToString("，")}")
        }
        txt += "，${statArr.joinToString("；")}"

        // 3. 描述发现的风险源情况
        if (sceneList.isEmpty()) {
            txt += ("，可能存在隐藏风险源。")
        } else {