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Research Papers

Reliability Analysis of Repairable System With Multiple Fault Modes Based on Goal-Oriented Methodology

[+] Author and Article Information
Xiao-Jian Yi

School of Mechanical Engineering,
Beijing Institute of Technology,
Beijing 100081, China
e-mail: yixiaojianbit@sina.cn

Jian Shi

Academy of Mathematics and Systems,
Science Chinese Academy of Sciences,
Beijing 100072, China
e-mail: jshi6674@sina.com

Hai-Ping Dong

School of Mechanical Engineering,
Beijing Institute of Technology,
Beijing 100081, China
e-mail: donghaipingphd@126.com

Yue-Hua Lai

School of Mechanical Engineering,
Beijing Institute of Technology,
Beijing 100081, China
e-mail: lyhlaibit@163.com

Manuscript received February 24, 2015; final manuscript received June 29, 2015; published online November 20, 2015. Assoc. Editor: Chimba Mkandawire.

ASME J. Risk Uncertainty Part B 2(1), 011003 (Nov 20, 2015) (9 pages) Paper No: RISK-15-1027; doi: 10.1115/1.4030971 History: Received February 24, 2015; Accepted July 01, 2015

This paper provides a new goal-oriented (GO) method for reliability analysis of repairable systems with multiple fault modes. First, formulas of operators describing components with multiple fault modes are derived based on Markov process theory. Second, qualitative reliability analysis of such a system is conducted by combining the existing GO method with the Fussell–Vesely method. Third, this new method is applied in reliability analysis of a hydraulic transmission oil supply system. Finally, comparing the study results with fault tree analysis (FTA) and Monte Carlo simulation shows that this new GO method is suitable for reliability analysis of repairable systems with multiple fault modes.

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References

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Figures

Grahic Jump Location
Fig. 1

State transition diagram of repairable components with multiple fault modes

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Fig. 3

GO model of HTOSS running at high-speed

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Fig. 4

Reliability block diagram of HTOSS running at high-speed

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Fig. 5

Fault tree of HTOSS running at high-speed

Grahic Jump Location
Fig. 6

Flowchart of Monte Carlo simulation

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