中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (S1): 150-157.doi: 10.16265/j.cnki.issn1003-3033.2019.S1.027

• 公共安全 • 上一篇    下一篇

高铁列车客运安全评价及风险管控*

邬春兰1 高级工程师, 宋雨欣2, 李晨3   

  1. 1 中国铁路南昌局集团有限公司 客运部,江西 南昌 330000;
    2 中国铁路北京局集团有限公司 北京西站,北京 100073;
    3 北京交通大学 交通运输学院,北京 100044
  • 收稿日期:2018-02-22 修回日期:2019-04-15 出版日期:2019-06-30 发布日期:2020-10-28
  • 作者简介:邬春兰 (1970—),女,江西丰城人,本科,高级工程师,主要从事铁路运输方面研究。E-mail:747971420@qq.com。

Safety assessment and risk control of high-speed trains passenger transportation

WU Chunlan1, SONG Yuxin2, LI Chen3   

  1. 1 China Railway Nanchang Bureau Group Co., Ltd., Passenger transport department, Nanchang Jiangxi 330000, China;
    2 China Railway Nanchang Bureau Group Co., Ltd,Beijing West Railway Station, Beijing 100073, China;
    3 School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044
  • Received:2018-02-22 Revised:2019-04-15 Online:2019-06-30 Published:2020-10-28

摘要: 为提升高铁列车系统安全性、保障列车安全运行,在分析高铁列车安全事故的基础上,利用事故树分析得到高铁列车安全风险指标体系,并转化为贝叶斯网络;结合云模型的模糊处理方法,将专家对各列车评价指标的定性自然评价语言转化为对应的模糊数;并对传统逼近理想解排序(TOPSIS)模型进行改进,综合考虑主观权重与客观权重,得到最优组合赋权的TOPSIS模型,据此对高铁列车安全进行评价;基于梯形模糊数和Buckley方法标定网络节点的相对先验概率,并通过Netica软件计算事故发生时各节点的相对后验概率。对比前后数据得出京沪高速铁路北京南-济南西区段列车主要安全风险为火灾爆炸,分析得到其主要潜在风险源并提出管控措施,可实现对高铁列车的安全管控。

关键词: 高铁列车, 安全评价, 管控, 逼近理想解排序(TOPSIS), 贝叶斯网络

Abstract: In order to systematically promote and guarantee the safety of high-speed trains, based on the safety accidents of high-speed trains, the safety risk index system of high-speed trains is obtained by using fault tree analysis and transformed into Bayesian network. Combining with the fuzzy processing method of cloud model, the qualitative natural evaluation language of experts on each station evaluation index was transformed into corresponding fuzzy numbers and the traditional TOPSIS model was improved. Considering subjective and objective weights comprehensively, the TOPSIS model with optimal combination weights was obtained, and the safety of high-speed railway trains was evaluated accordingly. Based on trapezoidal fuzzy number and Buckley method, the relative prior probability of network nodes was calibrated, and the relative posterior probability of each node was calculated by Netica software when the accident occurred. By comparing the data before and after the analysis, the results show that the main safety risk of Beijing-Shanghai high-speed railway train in the section from Beijing south to Jinan West was fire and explosion. By analyzing the main potential risk sources and proposing the control measures, the safety control of high-speed railway train can come true.

Key words: high-speed railway train, safety evaluation, management and control, technique for order preference by similarity to ideal solution(TOPSIS), Bayesian network

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