基于改进SHIPP模型的大型原油库区事故风险预测

隐患、未遂事故及无伤亡事故等异常事件是重大事故的早期预警和征兆,此类事件发生频率高,通过建立事故模型识别及纠正事件中的不安全因素能够有效预防重大事故发生。结合油库工艺特点和事故特征,对系统危害辨识、预测及预防(System Hazard Identification,Prediction and Prevention,SHIPP)模型改进,建立基于安全屏障的油库事故模型。采用故障树和事件树相结合的方式构建原因-后果关系模型,将故障树和事件树映射为贝叶斯网络以表征不确定性和条件依赖性。针对新的证据信息,通过贝叶斯网络更新机制实施概率更新;基于贝叶斯理论对现场异常事件数据进行经验学习,降低先验概率的不确定性,实现对油库事故的动态风险预测。对某油库算例分析结果表明,库区发生物质和能量释放的概率较大,整体安全性能趋于退化,应加强安全检查和隐患排查的力度。研究成果可为大型油库风险预测和事故预防提供科学指导和决策支持。

Accident risk prediction of large crude oil tank area based on improved SHIPP model

Abnormal events involving hidden dangers,near misses and non-casualty accidents are the early warning and signs of serious accidents.Considering the high frequency of such incidents,the accident model was established to identify and correct unsafe factors in such incidents so as to effectively prevent serious accidents.According to the process features and accident characteristics of the tank area,the System Hazard Identification,Prediction and Prevention(SHIPP)model was improved,and the tank area accident model based on safety barriers was built.The cause-consequence relationship model was constructed by combining fault tree and event tree,which were mapped into Bayesian network to characterize uncertainty and conditional dependence.As for new evidence information,probability updating was implemented through Bayesian network update mechanism.Though the empirically learning on the field abnormal event data based on Bayesian theory,the uncertainty of prior probability can be reduced and the dynamic risk prediction of accidents in oil tank area can be implemented.A tank area case was analyzed and the results show that,the probability of material and energy release in the tank area is high,the overall safety performance tends to deteriorate,and the safety inspection and hidden danger investigation should be strengthened.The research results can provide scientific guidance and decision support for risk prediction and accident prevention of large oil tank area.