Decomposition method for belief reliability analysis of complex uncertain random systems

Belief reliability is a new proposed reliability metric considering both aleatory and epistemic uncertainty. In belief reliability theory, system reliability analysis is a key component. Traditional system belief reliability theory for systems with random and uncertain components is based on a complex belief reliability formula, which is not understandable and efficient enough in engineering practise. In this paper, we put forward a novel system belief reliability analysis method, called decomposition method to cope with the problem. An algorithm of this method is proposed according to the properties of the cut sets of systems and the complexity of the algorithm is analyzed and compared with that of the reliability formula method. Finally, the effectiveness and efficiency of this method is further illustrated with a comparative case study.