Reliability Analysis of Complex Multi-state System with Common Cause Failure Based on DS Evidence Theory and Bayesian Network

Jinhua Mi (), Yan-Feng Li (), Weiwen Peng () and Hong-Zhong Huang ()
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Jinhua Mi: University of Electronic Science and Technology of China
Yan-Feng Li: University of Electronic Science and Technology of China
Weiwen Peng: University of Electronic Science and Technology of China
Hong-Zhong Huang: University of Electronic Science and Technology of China

A chapter in Recent Advances in Multi-state Systems Reliability, 2018, pp 19-38 from Springer

Abstract: Abstract With the increasing complexity and larger size of modern advanced engineering systems, the traditional reliability theory cannot characterize and quantify the complex characteristics of complex systems, such as multi-state properties, epistemic uncertainties, common cause failures (CCFs), etc. This chapter focuses on the reliability analysis of complex multi-state system (MSS) with epistemic uncertainty and CCFs. Based on the Bayesian network (BN) method for reliability analysis of MSS, the DS evidence theory is used to express the epistemic uncertainty in system through the state space reconstruction of MSS. An uncertain state, which used to express the epistemic uncertainty is introduced in the new state space. The integration of evidence theory with BN is achieved by updating the conditional probability tables. When the multiple CCF groups (CCFGs) are considered in complex redundant systems, a modified factor parametric model is introduced to model the CCF in systems. An evidence theory based BN method is proposed for the reliability analysis and evaluation of complex MSSs in this chapter. The reliability analysis of servo feeding control system for CNC heavy-duty horizontal lathes (HDHLs) by this proposed method has shown that the presented method has high computational efficiency and strong practical value.

Keywords: Complex multi-state system; Multi-state bayesian network; DS evidence theory; Multiple common cause failure groups (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/978-3-319-63423-4_2

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