摘要
针对传统动态故障树马尔可夫链分析方法的不足,提出了一种故障树模块化分析系统可靠性的方法。首先利用线性时间算法将系统故障树分成各自独立的子树,静态子树采用二元决策图分析,动态子树采用离散时间贝叶斯网络方法来分析;同时研究了动态逻辑门向离散时间贝叶斯网络的转化方法,最后以城市轨道交通制动系统为例进行分析,实验结果表明此方法简单实用,不仅能克服马尔可夫链分析方法的缺点,而且能降低系统分析的复杂度,提高系统分析效率,特别适合对大型复杂系统进行可靠性分析。
According to the deficiency of traditional Markov chain method in dynamic fault tree（DFT） analysis,a new modular method for system reliability analysis is proposed.This paper focuses on dividing the fault tree of system into independent subtrees using the linear time algorithm,and the processing method of subtrees：Binary Decision Diagram solution for static subtrees and Bayesian Networks solution dynamic subtrees,respectively.The converting of dynamic logic gates to discrete-time Bayesian networks is also illustrated.Finally,the modular method has been applied to the DFT modeling of braking system for rail transit and the results show that the proposed method can overcome the state explosion problem,improve the analysis efficiency and is useful for assessing the reliability of large and complex systems.
出处
《微计算机信息》
2010年第34期278-280,236,共4页
Control & Automation
基金
基金申请人:欧冬秀
卢滢
项目名称:轨道交通重大运营事件应急联动研究
基金颁发部门:上海市科委自然科学基金项目资助(10ZR1432200)
关键词
动态故障树
可靠性评估
二元决策图
贝叶斯网络
dynamic fault tree
reliability assessment
Binary Decision Diagram
Bayesian Networks
