一种故障树结构缺陷检测算法研究

A Fault Tree Structure Defects Detection Algorithm Research

快速而准确的化工事故因果分析将有助于未来的事故防范。通过对大量历史事故案例的分析,化工领域专家构建了同类事故标准故障树,有效表达同类事故成因的不同演绎路径。提出一种案例事故分析的缺陷检测方法,将常见的事故分析缺陷映射为故障树结构冗余、缺失和逻辑门错误。基于隐马尔可夫模型,提出一种故障树结构缺陷检测算法,能够自动检测案例故障树是否匹配标准故障树及可能的结构缺陷,实践表明该方法大大降低了对事故分析人员经验的依赖,实现了事故快速而准确的分析。

Rapid and accurate causal analysis of chemical accidents helps in preventing future accidents.By the analysis of large number of historical accidents,the experts in the chemical industry have developed the fault tree for the same kind of accident and effectively expressed the different deductive paths of the similar cause.This paper presents a defect detection method for case analysis,which maps the common fault analysis defects into fault tree structure redundancy,missing and logic gate errors.Based on the Hidden Markov Model,a fault tree structure defect detection algorithm is proposed to test automatically whether the subject fault tree matches with the standard fault tree or not and the possible defect pattern.Practice has proved that the adopted method greatly reduces the dependence on the experience of the accident analysis and realizes the quick and accurate analysis of the accident