Reliability analysis of phased-mission system with common cause failure based on discrete-time Bayesian network

Discrete-time Bayesian networks (DTBN), as an extension of Bayesian networks, is an effective tool for analyzing the reliability of phased mission systems (PMS). Currently, the reliability analysis of phased-mission system (PMS) with common cause failures (CCF) based on discrete-time Bayesian networks (DTBN) is mostly implemented by adding events or nodes to represent the influence of CCF, which increases the complexity of system analysis to a certain extent. Therefore, in this paper, a new algorithm combining PMS-DTBN with Efficient Decomposition and Aggregation (EDA) method is proposed to simplify the process of system reliability analysis under CCF by reducing the size of the DTBN model. The model is applied to a concrete example about the first re-orbiting process of a geosynchronous orbit satellite to verify the practical applicability of the developed approach. Meanwhile, by comparing the calculation results with those of the Monte Carlo method, under the same equipment, the proposed method can ensure higher solution accuracy and computational efficiency, with the relative error constrained to less than 0.001%.