Abstract:

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.