Bayesian networks based reliability analysis of phased-mission systems

The paper presents a Bayesian networks (BN) framework for the reliability analysis of phased-mission systems (PMS), named PMS-BN model. A PMS consists of consecutive and non-overlapping time periods, with system configuration, success criteria, and component behavior varying from phase to phase. Firstly, each phase is represented by a BN framework, named phase-BN. Then, in order to figure the dependences across the phases, all the phase-BN are combined by connecting the root nodes that represent the same component but belong to different phases, and connecting the leaf nodes of phase-BN with a new node representing the whole PMS mission. The new constructed BN is called PMS-BN. In PMS-BN model, each phase time is divided into m segment, and the reliability analysis of PMS is performed by a discrete-time BN model acting on PMS-BN. Two examples are used to expatiate on the proposed approach. The PMS-BN based method provides a new efficient way to analyze the reliability of PMS, especially for those with dynamic phases. Moreover, it is also applicable to system diagnosis and sensitivity analysis. If all the non-root nodes in constructed PMS-BN own not more than 2 father nodes, the computational complexity of evaluating the PMS reliability is O(Nm3), where N is the number of non-root nodes.