基于事故数据的轨道交通运行安全风险辨识方法
作者:
作者单位:

1.同济大学 道路与交通工程教育部重点实验室,上海 201804;2.兰州交通大学 自动化与电气工程学院,甘肃 兰州 730070;3.香港城市大学 计算机科学系,香港 999077;4.上海大学 悉尼工商学院,上海201800;5.贝尔福‒蒙贝利亚技术大学 信息学院,贝尔福 法国 90000;6.上海轨道交通十四号线发展有限公司,上海 201103

作者简介:

曾小清(1969—),女,教授,博士生导师,工学博士,主要研究方向为轨道交通控制与安全。 E-mail: zengxq@tongji.edu.cn

通讯作者:

何 乔(1997—),男,硕士生,主要研究方向为交通控制信息分析。 E-mail: 834066747@qq.com

中图分类号:

U284;X951

基金项目:

上海市科学技术委员会科研计划项目(20DZ1202900,19DZ1204200);上海市住建委科研项目(JS-KY18R022-7)


Safety Risk Identification of Rail Transit Signaling System Based on Accident Data
Author:
Affiliation:

1.Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;2.School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070,China;3.Department of Computer Science, City University of Hong Kong, Hong Kong 999077, China;4.SHU-UTS SILC Business School,Shanghai University,Shanghai 201800,China;5.School of Information, University of Technology of Belfort-Montbéliard , Belfort 90000, France;6.Shanghai Metro Line 14 Development Co. Ltd.,Shanghai 201103,China

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    摘要:

    针对轨道交通运行信号系统安全风险定量化辨识问题,首先将原始的信号事故按照海因里希法则分为不同类型事故数据,再考虑事故多因素影响,在一般统计法、统计识别法基础上,提出Management?Machine?Man?Media?Mission factor,即管理?设备?人员?环境?功能 5M要素模型的因子分析安全风险辨识方法,分别辨识254件较大伤亡事故和220件较小伤亡事故的主因素。实验结果表明,自然灾害、材质不良、施工管理不善、防护不力造成电务人员伤亡是导致轨道交通信号系统事故的最主要因素。基于5M的因子分析法可在多尺度综合计量下计算得到事故因素重要性排序,与一般统计法和统计识别法相比,基于5M的因子分析法辨识效果最优,覆盖率适中,影响率提高了106%。

    Abstract:

    To quantitatively identify the safety risk factors in rail transit signaling system accidents, an accident data mining method is presented. First, the original accidents were divided into different types of accident data in accordance with the law of Heinrich. Then, a 5M(management-machine-man-media-mission factor) based factor analysis identification method was adopted to identify respectively the 254 larger-casualty accidents and the 220 minor-casualty accidents considering the accident causation multi-factors after the general-statistic method and the statistic identification method analysis. The results indicate that the natural disaster, the signal equipment material fault, the poor construction management, and the inadequate staff protection are the most important major factors leading to the signaling system accident. The 5M based factor analysis method can be used to sort quantitatively the importance ranking of accident causation factors under multi-scale comprehensive measurement. A comparison of the general-statistic method and the statistic identification method suggests that the 5M based factor analysis method has the best identification effect, with a relatively higher influencing rate of 106% increase and moderate coverage rate.

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曾小清,林海香,王奕曾,袁腾飞,何乔,黄继成.基于事故数据的轨道交通运行安全风险辨识方法[J].同济大学学报(自然科学版),2022,50(3):418~424

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  • 收稿日期:2021-04-06
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  • 在线发布日期: 2022-04-11
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