证据理论与贝叶斯网络相结合的可靠性分析方法

Reliability analysis based on evidence theory and Bayesian networks method

针对可靠性分析中存在的认知不确定性问题,将证据理论引入到贝叶斯网络。给出了存在认知不确定性时故障树向贝叶斯网络的转换方法,以及基于信任测度和似然测度求解顶事件发生概率的方法。研究了三种重要度的求解方法,同时提出了一个重要概念———认知重要度,给出了其实际意义和计算方法。最后,运用所提出方法对某导弹发动机进行了可靠性分析,结果表明,该方法增强了贝叶斯网络处理不确定性信息的能力,简单有效且可以得到更丰富的信息。

To deal with epistemic uncertainties in reliability analysis, the implementation of evidence theory in Bayesian networks is studied. The method to convert fault trees to Bayesian networks in epistemic uncertainty condition is proposed, and the probability of top event is calculated by belief measure and plausibility measure of evidence theory. Three importances are solved, and a key concept, epistemic importance, is proposed, which definition and algorithm are given. Finally, with a numerical example, it is shown that the proposed method could enhance the ability of Bayesian networks to deal with uncertainty information in reliability analysis, and could obtain additional information.