摘要
为了系统化地分析斜巷轨道运输事故,提出了在贝叶斯网络的基础上融合预先危险性分析-保护层分析(PHA-LOPA)、蝴蝶结分析于一体的复合模型风险分析方法.首先,借助于Ge NIe软件实现贝叶斯网络的双向推理能力,辨识出风险贝叶斯事故节点;然后,对事故节点进行PHA-LOPA研究,确定引起事故的原因、造成的结果,设置独立保护层降低事故节点的危险性等级;最后,对剩余危险性等级仍然较高的事故节点进行蝴蝶结分析,设置安全屏障,进一步控制事故的发生.以某矿斜巷轨道运输事故为例,应用该复合模型风险分析方法,结果验证了所提方法的正确性和可行性.
A composite risk analysis model was put forward to analyze the rail haulage accident in inclined tunnel systematically. The model combines preliminary hazard analysis-layer of protection analysis（ PHA-LOPA） with bow-tie analysis together based on Bayesian network.First,taking advantage of two-way reasoning ability of Bayesian network identified the risk Bayesian accident nodes with the help of GeNIe software. Second,the accident nodes was studied using PHA-LOPA to determine the causes and results of the accident,and to set independent protection layer to reduce the risk level of the accident nodes. Third,bow-tie analysis was performed on the accident node where the residual risk level was still high,safety barriers were set and the occurrence of the accident was further controlled. The proposed composite risk analysis model was applied to a rail haulage accident in inclined tunnel in a mine,and the validity and feasibility was verified by the results.
作者
徐青伟
许开立
XU Qing-wei;XU Kai-li(School of Resources ＆ Civil Engineering,Northeastern University,Shenyang 110819,China.)
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2018年第7期1048-1052,共5页
Journal of Northeastern University(Natural Science)
基金
国家重点研发计划项目(2017YFC0805100)
关键词
贝叶斯网络
预先危险性分析
保护层分析
蝴蝶结分析
轨道运输事故
Bayesian network
preliminary hazard analysis
layer of protection analysis
bow-tie analysis
rail haulage accident
