Bayesian networks based reliability analysis of phased-mission systems

被引：0

作者：

School of Computer, National University of Defense Technology, Changsha 410073, China ^{[1
]}

不详 ^{[2
]}

不详 ^{[3
]}

机构：

[1] School of Computer, National University of Defense Technology

[2] Key Laboratory of National Defense Technology, Academy of Equipment Command and Technology

[3] China Huayin Ordnance Test Center

来源：

Jisuanji Xuebao | 2008年 / 10卷 / 1814-1825期

关键词：

Bayesian networks; Computational complexity; Phased-mission systems; Reliability analysis; Sensitivity analysis;

D O I：

10.3724/sp.j.1016.2008.01814

中图分类号：

学科分类号：

摘要：

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.

引用

页码：1814 / 1825

页数：11

共 21 条

[1]

Esary J.D., Ziehms H., Reliability analysis of phased missions, Proceedings of the Conference of Reliability and Fault Tree Analysis, pp. 213-236, (1975)

[2]

Ma Y., Trivedi K.S., An algorithm for reliability analysis of phased-mission systems, Reliability Engineering and System Safety, 66, 2, pp. 157-170, (1999)

[3]

Somani A.K., Trivedi K.S., Phased-mission system analysis using Boolean algebraic methods, Proceedings of the ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, pp. 98-107, (1994)

[4]

Zang X., Sun N., Trivedi K.S., A BDD-based algorithm for reliability analysis of phased-mission systems, IEEE Transactions on Reliability, 48, 1, pp. 50-60, (1999)

[5]

Xing L., Dugan J.B., Analysis of generalized phased-mission system reliability, performance, and sensitivity, IEEE Transactions on Reliability, 51, 2, pp. 199-211, (2002)

[6]

Tang Z., Dugan J.B., BDD-based reliability analysis of phased-mission systems with multimode failures, IEEE Transactions on Reliability, 55, 2, pp. 350-360, (2006)

[7]

Tang Z., Xu H., Dugan J.B., Reliability analysis of phased mission systems with common cause failures, Proceedings of the Reliability and Maintainability Symposium, pp. 313-318, (2005)

[8]

Kim K., Park K.S., Phased-mission system reliability under Markov environment, IEEE Transactions on Reliability, 43, 2, pp. 301-309, (1994)

[9]

Dugan J.B., Analysis of a hybrid voting algorithm for replicated file systems, Information and Software Technology, 33, 4, pp. 273-280, (1991)

[10]

Ou Y., Meshkat L., Dugan J.B., Multi-phase reliability analysis for dynamic and static phases, Proceedings of the Reliability and Maintainability Symposium, pp. 404-410, (2002)

← 1 2 3 →