基于动态贝叶斯网络的动态故障树分析

Dynamic fault tree analysis based on dynamic Bayesian networks

针对传统的动态故障树Markov链分析方法的不足,研究了优先或门、顺序相关门、功能相关门、存在公共备件的备件门和层叠功能相关门向动态贝叶斯网络的转化方法以及基于动态贝叶斯网络的顶事件概率、重要度等计算方法.用该方法对心脏辅助装置进行了分析,通过与Markov链、离散时间贝叶斯网络分析的结果比较表明,基于动态贝叶斯网络的建模分析方法可以有效地避免组合爆炸,而且能够保证较高的求解精度.

According to the deficiency of traditional Markov chain method in dynamic fault tree analysis, a new method based on dynamic Bayesian networks is studied, This paper is aimed at converting dynamic logic gates, including priority or gate, sequence enforcing gate, functional dependency gate, multiple spare gates sharing spare pools and cascading functional dependency gates, to dynamic Bayesian networks and the calculation methods of top event probability and importance measures. The comparison with Markov chain and discrete-time Bayesian networks is carried out by means of the example of cardiac assist device in the end, and the results show that the proposed method could overcome the state explosion problem and guarantee high accuracy.