基于改进的WBS-RBS识别铁路危险品运输风险

Improved WBS-RBS based identification of risks in railway transportation of dangerous goods

为预防铁路危险品运输安全事故,提出一种基于改进工作分解结构-风险分解结构（WBS-RBS）的风险识别方法。首先,通过专家打分的区间数耦合判断矩阵改进WBS-RBS风险矩阵;然后,采用区间数中点值和区间半宽对WBS-RBS耦合判断矩阵进行全过程全系统整体风险识别并排序,同时采用可能度排序向量进行分过程分风险识别并排序;最后,以锂电池运输为例进行方法有效性验证。结果表明：货运检查时相关人员失职、未经培训人员装卸货物、检修不当的列车运行过程中产生的风险最大;列车运行过程中存在的风险因素最多;相关人员失职、机车车辆检修不当、锂电池燃爆等3类风险在各运输过程中出现的频率最高。使用区间数有助于减小风险识别过程中的主观性和不确定性。

In order to prevent the safety accidents in railway dangerous goods transportation,an improved WBS-RBS method was worked out for identifying the risks in it. Firstly,the interval numbers coupled judgment matrix of expert scoring was proposed to improve the WBS-RBS risk matrix. Following this,the midpoints and the half-width of the interval numbers were used for identifying and sorting the whole system WBS-RBS interval numbers,and the probability degree ranking vectors were used for identifying and sorting the unit system interval numbers. Finally,the lithium battery transportation is given as a numerical example to verify the method. The results show that related personnel＇s dereliction of duty during cargo inspection,personnel＇s without training during cargo handlings and improper maintenance of rolling stock during the operation of the train generate ultimate risks,that the risk factors in operation of the train are more than those in other operations,that three risks including related personnel＇s derelictionof duty,improper maintenance of rolling stock and combustion and explosion of lithium batteries have the highest frequency during transportation,and that the interval numbers are helpful in reducing subjectivity and uncertainty in risk identification.