摘要
聚焦于提升灾前风险辨识、临灾监测预警、灾中态势研判和灾后损失评估的准确性和科学性,该文设计并研制了电网山火“天空地”联合感测大尺度实验平台,具备模拟电网山火起火、发展、蔓延等多阶段灾害情景重现能力,并获取遥感影像、无人机图像、地表火焰温度、近地面热辐射、空中烟雾温度、气象参数、多角度视频图像等全过程测量数据,实现万平方米尺度地表火和林地火全过程、多维度实验感测。提出了初期火点特征识别、多维数据协同火情研判和火灾强度参量感测方法,对于提高山火应急时效性和科学性具有重要支撑作用。
[Objective]Wildfires are one of the most critical disasters faced by power grid facilities.They can easily cause damage to the transmission equipment body,loss of power supply load,and power outages.However,the current power grid’s wildfire sensing methods have certain limitations,especially the ability to accurately reproduce real combustion scenarios,which considerably hampers the precision of mountain fire warnings and the forward-looking level of situational analysis.To address these limitations,large-scale real wildfire experiments in power grid facilities are urgently needed.These experiments will provide comprehensive data on fire ignition,development,and spread under real-world conditions,helping to improve wildfire emergency response by enhancing identification algorithms,situational analysis,and decision-making capabilities.This study aims to enhance the accuracy and scientific rigor of predisaster risk identification,disaster monitoring and early warning,in-disaster situational analysis,and postdisaster loss assessment.This study designs and develops a large-scale experimental platform for joint“sky–ground”sensing of power grid wildfires,capable of simulating wildfire ignition,development,and spread within power grid disaster scenarios.[Methods]During the design process of the experimental platform,accurate control is applied to factors such as combustible type,humidity,and density.By measuring multidimensional characteristic parameters from satellites,drones,overhead power lines,and the earth’s surface,this study gathers comprehensive experimental data,including remote sensing images,drone imagery,surface flame temperature,near-surface thermal radiation,airborne smoke temperature,meteorological parameters,and multiangle video recordings.Adhering to the principles of repeatability,controllable boundaries,scene authenticity,data validity,and full-process recording,the experimental combustion scale can reach tens of thousands of square meters,enabling comprehensive,multidimensional joint sensing.[Results]Preliminary experiments conducted on a scale of several thousand square meters demonstrate the following:1)The experimental platform could effectively capture the multidimensional characteristics of aerial and ground wildfire dynamics,including early ignition,development,and postdisaster burn sites.At an experimental scale of 2000 m2,a satellite visible light channel with a resolution of 0.75 m can distinguish flame and smoke patterns.Moreover,the ground visualization system,positioned at heights of 15,10,and 3 m,can capture fire and smoke images from multiple angles.2)During the development stage of a fire,the experimental platform can enable comprehensive recording of fire line movement and temperature evolution,with a spatial resolution of 5 m on the ground and 10 m in the air.Furthermore,the platform facilitates the collaborative analysis of multidimensional data by integrating satellite remote sensing,aerial visualization,thermal infrared imaging,and ground-based contact measurements.3)Through experiments,a method is proposed for recognizing initial fire point features,conducting multidimensional data collaborative fire assessments,and sensing fire intensity parameters.[Conclusions]This study establishes a large-scale experimental platform for joint“sky–ground”sensing of power grid wildfires.Through large-scale wildfire experiments in power grid facilities,this study clarifies the flame morphology characteristics of wildfires and proposes a multidimensional data collaborative fire dynamic analysis method.This study reveals the evolution patterns of key fire parameters,such as surface flame temperature and smoke temperature,enabling a comprehensive and detailed reconstruction of wildfire dynamics in power grids.These findings hold substantial theoretical value and practical applications for improving the scientific accuracy of wildfire prevention and control,enhancing fire monitoring and early warning systems,and strengthening situational analysis capabilities.
作者
刘畅
姬昆鹏
李军辉
杨知
李孟轩
汉京善
张思航
LIU Chang;JI Kunpeng;LI Junhui;YANG Zhi;LI Mengxuan;HAN Jingshan;ZHANG Sihang(China Electric Power Research Institute,Beijing 100192,China)
出处
《实验技术与管理》
北大核心
2025年第5期19-27,共9页
Experimental Technology and Management
基金
国家电网公司科技项目(5500-202255286A-2-0-QZ)。
关键词
电网设施
山火
大尺度实验
多维数据感测
情景重构
power grid facilities
wildfires
large-scale experiments
multidimensional data sensing
scenario reconstruction
