基于知识图谱和故障树的高速铁路事故致因分析  

Causal analysis of high-speed railway accidents based on knowledge graph and fault tree

作　　者：张丁荣 王恪铭[2,3] 冯心妍 ZHANG Dingrong;WANG Keming;FENG Xinyan(School of Information Science and Technology,Southwest Jiaotong University,Chengdu 610031,China;School of Computer and Artificial Intelligence,Southwest Jiaotong University,Chengdu 610031,China;National-Local Joint Engineering Laboratory of System Creditability Automatic Verification,Southwest Jiaotong University,Chengdu 610031,China)

机构地区：[1]西南交通大学信息科学与技术学院,成都610031 [2]西南交通大学计算机与人工智能学院,成都610031 [3]西南交通大学系统可信性自动验证国家地方联合工程实验室,成都610031

出　　处：《铁路计算机应用》2023年第7期14-18,共5页Railway Computer Application

基　　金：四川省自然科学基金(2022NSFSC0464)。

摘　　要：针对高速铁路(简称:高铁)事故开放共享程度不高,数据条块化、垂直化,信息碎片化等问题,基于知识图谱构建高铁事故的本体层及数据层,实现事故数据的资源整合,使用图数据库表达事故致因逻辑关系,通过Python编程生成高铁事故致因故障树,完成对高铁事故的致因分析。分析结果表明,人为因素中的“违规作业”“监管不力”及环境因素中的“恶劣天气”导致了更多高铁事故的发生。据此结果,为铁路相关部门防范重大事故发生提出了切实可行的建议。In view of the problems such as the low degree of opening and sharing of high-speed railway accidents,data fragmentation,verticalization and fragmentation of information,this paper constructed the ontology layer and data layer of high-speed railway accidents based on the knowledge graph to implement the resource integration of accident data,used the graph database to express the logical relationship of accident causes,generated the fault tree of high-speed railway accident causes through Python programming,and completed the cause analysis of high-speed railway accidents.The analysis results indicate that"illegal operations"and"inadequate supervision"in human factors,as well as"adverse weather"in environmental factors,have led to more high-speed rail accidents.Based on these results,the paper provides practical and feasible suggestions for railway departments to prevent major accidents from occurring.

关 键 词：高速铁路 事故致因 知识图谱 故障树 事故分析 

分 类 号：U238[交通运输工程—道路与铁道工程] U298.5[自动化与计算机技术—计算机应用技术] TP39[自动化与计算机技术—计算机科学与技术]