摘要
为帮助火灾调查人员快速准确地确定起火点位置、完善事故调查证据链,进而探明火灾原因,综述基于火灾痕迹的起火点判定研究现状。首先,介绍火灾痕迹分类,包括燃烧痕迹、烟熏痕迹、倒塌痕迹及电器线路痕迹,着重介绍烟熏痕迹的研究现状及不足;然后,综述当前国内外多种起火点判定方法,将其分为利用经验、数值重构技术以及机器学习算法等3种,并分别分析3种方法的优势和不足;最后,展望未来起火点判定技术的研究趋势。结果表明:利用烟熏痕迹数值模拟结合机器学习进行起火点判定具有良好的应用前景。
In order to help fire investigators determine the location of the fire origin,improve the chain of evidence in accident investigations and identify the cause of the fire quickly and accurately,the researches on fire origin determination based on fire traces were reviewed in present paper.First,fire traces were classified,including burn marks,smoke marks,collapse marks and electrical wiring marks,with emphasis on soot deposition traces.Then,multiple fire origin determination methods at home and abroad were reviewed and classified into three categories:determining the fire origin directly using experience,determining the fire origin using numerical reconstruction techniques,and determining the fire origin using machine learning algorithms.The advantages and limitations of each method were analyzed respectively.Finally,the future research tendency of fire origin determination technology was prospected.The results show that numerical simulation of soot deposition traces combined with machine learning for fire origin determination has a good perspective for application.
作者
牛甜辉
耿佃桥
苑轶
赵亮
董辉
王柏
NIU Tianhui;GENG Dianqiao;YUAN Yi;ZHAO Liang;DONG Hui;WANG Bai(Key Laboratory of Electromagnetic Processing of Materials,Ministry of Education,Northeastern University,Shenyang Liaoning 110819,China;School of Metallurgy,Northeastern University,Shenyang Liaoning 110819,China;Shenyang Fire Science and Technology Research Institute of MEM,Shenyang Liaoning 110034,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2024年第1期238-246,共9页
China Safety Science Journal
基金
沈阳市科技计划项目(21-108-9-16)。
关键词
起火点
火灾痕迹
数值重构
机器学习
烟熏痕迹
fire origin
fire traces
numerical reconstruction
machine learning
soot deposition traces
