基于多态模糊贝叶斯网络的城市燃气管道事故风险预测与诊断研究  

Risk prediction and diagnosis of urban gas pipeline accidents based on polymorphic fuzzy Bayesian network

作　　者：瞿英[1,2] 王旭茗 王玉恒[2] 张静怡 QU Ying;WANG Xuming;WANG Yuheng;ZHANG Jingyi(Data Science and Intelligent Computing Research Center,Hebei University of Science and Technology,Shijiazhuang,Hebei 050018,China;School of Economics and Management,Hebei University of Science and Technology,Shijiazhuang,Hebei 050018,China;School of Social Sciences,Mokwon University,Daejeon Gwangyeoks 340-934,Korea)

机构地区：[1]河北科技大学数据科学与智能计算研究中心,河北石家庄050018 [2]河北科技大学经济管理学院,河北石家庄050018 [3]韩国牧园大学社会科学学院,大田广域340-934

出　　处：《河北科技大学学报》2023年第4期411-420,共10页Journal of Hebei University of Science and Technology

基　　金：河北省教育厅人文社科重大课题攻关项目(ZD202208);河北省自然科学基金(G2021208004)。

摘　　要：为了评估城市燃气管道系统的风险程度,给后续预防工作提供参考,提出了基于多态模糊贝叶斯网络的燃气管道事故风险定量分析方法。首先,基于对86份事故调查报告风险因素的梳理,建立故障树模型,寻求风险隐患和事故之间的映射,并将其转换为贝叶斯网络结构;其次,引入模糊集理论与概率分配计算方法,分别得出根节点的先验概率和中间节点的条件概率,根据贝叶斯网络的证据推理原理预测事故发生概率,分析风险重要程度,并反向诊断关键致因要素;最后,将此方法应用于沈阳市“10·21”较大燃气管道事故风险分析。实例验证结果表明,事故一定发生的先验概率为68.8%,验证了风险体系的有效性,且预测与诊断得出的重要风险集合与事故调查报告中分析的直接原因一致。多态模糊贝叶斯网络能够准确评价燃气管道事故风险,并确定关键致险因子,可为城市燃气管道安全管理提供决策参考。In order to evaluate the risk level of the urban gas pipeline system,and provide the reference for follow-up prevention efforts,a quantitative analysis method of gas pipeline accident risk was proposed based on polymorphic fuzzy Bayesian network.Firstly,risk factors were sorted out from 86 accident investigation reports,so that the city gas pipeline risk element system was established.Subsequently,the fault tree model was built to seek the match between risk hazards and accidents,which can convert into the Bayesian network structure.After that,fuzzy set theory and probability distribution method were introduced to calculate the prior probability of the root node and the conditional probability of the intermediate nodes,evidence-based inference of Bayesian network was used to predict the probability of accidents,analyze the importance of risk elements,and reverse diagnose key causal factors.Finally,this method was applied to the risk analysis of the“10·21”large pipeline gas leakage accident in Shenyang.The results of the case validation show the a priori probability of the accident is 68.8%,which verifies the effectiveness of the risk system.Besides,important risk elements derived from prediction and backward diagnosis are consistent with the direct causes analyzed in the accident investigation report.The polymorphic fuzzy Bayesian network approach for gas pipeline system risk can evaluate gas pipeline accident risk accurately and identify key risk-causing factors,which provides some reference for decision making in the safety management of city gas pipelines.

关 键 词：风险评价与失效分析 燃气管道系统 模糊集理论 多态模糊贝叶斯网络 概率分配 

分 类 号：X928.7[环境科学与工程—安全科学]