Belief Universal Generating Function Analysis of Multi-State Systems Under Epistemic Uncertainty and Common Cause Failures


Because of the complexity of engineering systems, and the fact that insufficient knowledge are solely offered to obtain the precise state probability of components, an extended universal generating perform (UGF) based on belief function theory is introduced during this paper to conduct the reliability analysis of multi-state systems (MSSs) with epistemic uncertainty. The behavior of common cause failures (CCFs) is any incorporated, and also the prevalence probability of CCFs is evaluated using a weighted impact vector technique. A numerical example is employed to illustrate how the proposed methodology works. In addition, a international optimization method is used to get the reality interval of the system reliability, and therefore the results are compared with those obtained by using some existing strategies. The case study shows that the belief UGF method will effectively avoid the interval enlargement drawback and the overestimation problem involved within the interval UGF technique, and therefore the proposed technique will be used to provide a reliable way to judge the reliability of MSSs with interval knowledge and CCFs.

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