Bayesian Networks Based Reliability Analysis of Phased-Mission Systems

Abstract

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.