A Novelty Model for Reliability Assessment of Complex System

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Abstract:

Aiming at the difficulty in reliability assessment of complex system. A novelty model based on Bayesian method and GO methodology is proposed. Bayesian method is adopted for multi-source information fusion to build the component reliability model, and then GO methodology is utilized to integrate the component reliability parameters and form the reliability model of the system. At last, an instance of reliability assessment for complex electronic equipment is given to show the effectiveness of the model. Result shows that, this method take advantage of Bayesian method and GO methodology, it provide useful reference for relative applications.

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118-123

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] C.A. Clarotti, F. Spizzichino. The Bayes Predictive Approach in Reliability Theory[J]. IEEE Transactions on Reliability, 1989, 38(3): 379-382.

DOI: 10.1109/24.44186

Google Scholar

[2] Jing FENG. Research on Methods and Applications of Reliability Information Fusion for Complex System with Small Sample test[D]. National University of Defense Techonology, (2004).

Google Scholar

[3] Roy E. Rice, Albert H. Moore. A Monte Carlo technique for estimating lower confidence limits on system reliability using pass-failing data[J]. IEEE Trans on Reliability, 1983, 366-369.

DOI: 10.1109/tr.1983.5221686

Google Scholar

[4] Weimin YANG. Digital Simulation of System Reliability[M]. Beijing University of aeronautics&astronautics Press, (1980).

Google Scholar

[5] Jingzhou XU, Yang LI. Reliability Assessment of Complex Distribution System Using GO Method. Transaction of China Electronical Society. Vol. 22, No. 1, pp: 149-153, (2007).

Google Scholar

[6] Matsuoka T, Kobayashi M. GO-FLOW: A system reliability analysis methodology[A]. Apostolakis G. Probabilistic Safety Assessment and Management[C]. Amsterdam: Elsevier, (1991).

Google Scholar

[7] Guili WANG. System Reilability Analysis GO Methodology and Research on the Application[D]. Harbin Institute of Technology, (2006).

Google Scholar

[8] Xing JIN. Monte Carlo Method of MTTF Evaluation for Large Complex System[J]. Journal of System Simulation, 2005, 17(1): 66-68.

Google Scholar