Health evaluation method for degrading systems subject to dependent competing risks

doi:10.21629/JSEE.2018.02.23

Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (2): 436-444.doi: 10.21629/JSEE.2018.02.23

• Reliability • Previous Articles

Health evaluation method for degrading systems subject to dependent competing risks

Shuai ZHAO^1,²(), Viliam MAKIS^2,*(), Shaowei CHEN¹(), Yong LI¹()

¹ School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
² Department of Mechanical and Industrial Engineering, University of Toronto, Toronto M5S 3G8, Canada

Received:2017-01-18 Online:2018-04-26 Published:2018-04-27
Contact: Viliam MAKIS E-mail:shuaiz@mie.utoronto.ca;makis@mie.utoronto.ca;cgong@nwpu.edu.cn;ruikel@nwpu.edu.cn
About author:ZHAO Shuai was born in 1989. He received his B.E. degree in communication engineering, and M.E. degree in communication and information engineering from Northwestern Polytechnical University, Xi'an, China, in 2011 and 2013, respectively, where he is currently working toward his Ph.D. degree. From 2014 to 2016, he was also a visiting Ph.D. student in the Department of Mechanical and Industrial Engineering at the University of Toronto. He is the recipient of the provincial science and technology progress award and has four patents. His research interests include residual life prediction, reliability modeling, health assessment, and fault diagnosis of electronic systems. E-mail: shuaiz@mie.utoronto.ca|MAKIS Viliam was born in 1953. He is a professor in the Department of Mechanical and Industrial Engineering, University of Toronto. His research interests are modeling and optimization of partially observable stochastic systems with a special focus on investigating structural properties of the optimal operating policies for such systems, off-line and online model parameter estimation and filtering. His research is driven by practical problems such as the development of fault detection and diagnostic schemes for condition-based maintenance, optimal joint production and maintenance control, the optimal multivariate quality control for both short and long production runs, and the development of optimal sampling schemes for monitoring partially observable stochastic processes. He is a Fellow of the International Society of Engineering Asset Management, a Senior Member of the Institute of Industrial Engineers of the American Society for Quality, and a member of INFORMS and CORS. E-mail: makis@mie.utoronto.ca|CHEN Shaowei was born in 1970. He is currently an associate professor in the School of Electronics and Information at Northwestern Polytechnical University, where he is also the director of Signal Processing and Control Technology Laboratory. He is the principal investigator of several projects supported by Aeronautical Science Foundation of China. He is selected to receive several provincial and ministerial science and technology awards and has five patents. His research expertise is in the area of the fault diagnosis, sensors, condition monitoring, and prognosis of electronic systems. He is the senior member of the Chinese Institute of Electronics. E-mail: cgong@nwpu.edu.cn|LI Yong was born in 1962. He received his B.E. degree in electronic engineering, M.E. degree in signal and circuit system, and Ph.D. degree in circuit and system engineering from Northwestern Polytechnical University, Xi'an, China, in 1983, 1988, and 2005, respectively. He is currently a professor in the School of Electronics and Information at Northwestern Polytechnical University. He was a visiting scholar at the University of Texas at Arlington in 2009. His funding is from National Defense Advance Research, Aeronautical Science Foundation of China, Civil Aircraft Advance Research, etc. His research interests include the real-time signal measurement, high-speed signal processing, conditional monitoring, health assessment, and communication for electronic systems. E-mail: ruikel@nwpu.edu.cn
Supported by:
the Aeronautical Science Foundation of China(20155553039);the Natural Sciences and Engineering Research Council of Canada(RGPIN 121384-11);This work was supported by the Aeronautical Science Foundation of China (20155553039) and the Natural Sciences and Engineering Research Council of Canada (RGPIN 121384-11)

Abstract

Abstract:

This paper proposes a health evaluation method for degrading systems subject to competing risks of dependent soft and hard failures. To characterize the time-varying degradation rate, the degradation process is determined by a non-stationary Gamma process and the soft failure is encountered when it exceeds a predefined critical level. For the hard failure, a Cox's proportional hazard model is applied to describe the hazard rate of the time to system failure. The dependent relationship is modeled by incorporating the degradation process as a time-varying covariate into the Cox's proportional hazard model. To facilitate the health characteristics evaluation, a discretization technique is applied both to the degradation process and the monitoring time. All health characteristics can be obtained in the explicit form using the transition probability matrix, which is computationally attractive for practical applications. Finally, a numerical analysis is carried out to show the effectiveness and the performance of the proposed health evaluation method.

Key words: competing risk, conditional mean residual life, health evaluation, non-stationary Gamma process, proportional hazards model

Shuai ZHAO, Viliam MAKIS, Shaowei CHEN, Yong LI. Health evaluation method for degrading systems subject to dependent competing risks[J]. Journal of Systems Engineering and Electronics, 2018, 29(2): 436-444.

Figures/Tables 7

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References 23

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Monitoring	Degradation state
time	0	3	6	9
0.6	0.992 6	0.985 3	0.964 3	0.846 5
1.1	0.915 5	0.850 3	0.706 7	0.315 5
1.6	0.759 6	0.627 0	0.410 9	0.094 9
2.1	0.546 6	0.383 6	0.189 3	0.023 7
2.6	0.333 0	0.192 4	0.069 9	0.005 0
3.1	0.169 7	0.079 0	0.020 9	0.000 9

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Health evaluation method for degrading systems subject to dependent competing risks

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