Remaining lifetime prediction for nonlinear degradation device with random effect

doi:10.21629/JSEE.2018.05.20

Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (5): 1101-1110.doi: 10.21629/JSEE.2018.05.20

• Reliability • Previous Articles

Remaining lifetime prediction for nonlinear degradation device with random effect

Zhongyi CAI^1,*(), Yunxiang CHEN¹(), Jiansheng GUO¹(), Qiang ZHANG²(), Huachun XIANG¹()

¹ Equipment Management and Unmanned Aerial Vehicle Engineering College, Air Force Engineering University, Xi’an 710051, China
² Defense Technology Academy, China Aerospace Science and Industry Corporation Limited, Beijing 100854, China

Received:2017-06-17 Online:2018-10-26 Published:2018-11-14
Contact: Zhongyi CAI E-mail:afeuczy@163.com;cyx87793@163.com;amisc@163.com;afzhangq@163.com;xhc09260926@163.com
About author:CAI Zhongyi was born in 1988. He received his B.S. degree of management engineering in 2010, M.S. degree of management science and engineering in 2012 and Ph.D. degree of management science and engineering in 2016 from Air Force Engineering University. Now he is a lecturer of Device Management & UAV Engineering College, Air Force Engineering University. His research interests are reliability assessment and remaining lifetime prediction. He has published more than 20 research papers. E-mail: afeuczy@163.com|CHEN Yunxiang was born in 1962. He received his M.S. degree from Air Force Engineering College in 1989 and Ph.D. degree from Northwestern Polytechnical University in 2005. Now he is a professor of Device Management & UAV Engineering College, Air Force Engineering University. His research interests are reliability assessment, materiel maintenance support and materiel development & demonstration. He has published five books and more than 50 research papers. He is an expert of the Air Force in reliability, maintenance and support. E-mail: cyx87793@163.com|GUO Jiansheng was born in 1965. He received his M.S. degree from Air Force Engineering College in 1991 and Ph.D. degree from Northwestern Polytechnical University in 2009. Now he is a professor of Device Management & UAV Engineering College, Air Force Engineering University. His research interests are system engineering and complex system modeling. He has published three books and more than 20 research papers. E-mail: amisc@163.com|ZHANG Qiang was born in 1983. He received his B.S. degree of communication and information system from Wuhan University in 2006 and M.S. degree from Air Force Engineering University in 2009. Now he is the industrial development director of Defense Technology Academy, China Aerospace Science and Industry Corporation Limited. His research interests are reliability assessment and project management. He has published five research papers. He is a senior engineer. E-mail: afzhangq@163.com|XIANG Huachun was born in 1980. He received his M.S. degree of management science and engineering in 2005 and Ph.D. degree of system engineering in 2009 from Air Force Engineering University. Now he is a vice professor and director of Device Management & UAV Engineering College, Air Force Engineering University. His research interests are reliability design, reliability assessment and system engineering. He has published two books and ten research papers. E-mail: xhc09260926@163.com
Supported by:
the National Defense Foundation of China(71601183);the China Postdoctoral Science Foundation(2017M623415);This work was supported by the National Defense Foundation of China (71601183) and the China Postdoctoral Science Foundation (2017M623415)

Abstract

Abstract:

For the large number of nonlinear degradation devices existing in a project, the existing methods have not systematically studied the effects of random effect on the remaining lifetime (RL), the accuracy and efficiency of the parameters estimation are not high, and the current degradation state of the target device is not accurately estimated. In this paper, a nonlinear Wiener degradation model with random effect is proposed and the corresponding probability density function (PDF) of the first hitting time (FHT) is deduced. A parameter estimation method based on modified expectation maximum (EM) algorithm is proposed to obtain the estimated value of fixed coefficient and the priori value of random coefficient in the model. The posterior value of the random coefficient and the current degradation state of target device are updated synchronously by the state space model (SSM) and the Kalman filter algorithm. The PDF of RL with random effect is deduced. A simulation example is analyzed to verify that the proposed method has the obvious advantage over the existing methods in parameter estimation error and RL prediction accuracy.

Key words: remaining lifetime (RL) prediction, nonlinear degradation model, Wiener process, random coefficient, Kalman filter algorithm

Zhongyi CAI, Yunxiang CHEN, Jiansheng GUO, Qiang ZHANG, Huachun XIANG. Remaining lifetime prediction for nonlinear degradation device with random effect[J]. Journal of Systems Engineering and Electronics, 2018, 29(5): 1101-1110.

Figures/Tables 9

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References 35

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Method	$\mu _\lambda $	$\sigma _\lambda ^2 $	$\sigma _B^2 $	b	Lg-LF	AIC	MSE
Real value	1	0.0625	0.04	1.5	–	–	–
M1	0.931	0.068 2	0.088	1.521	– 25.641	59.282	0.950
M2	0.951	0.121 0	0.176	1.000	– 29.310	64.620	2.321
M3	1.854	0	0.101	1.534	– 33.672	73.344	7.319

Algorithm	$\mu _\lambda $	$\sigma _\lambda ^2 $	$\sigma _B^2 $	b
Modified EM	0.931	0.068 2	0.088	1.521
EM	0.931	0.089 1	0.102	1.521
TSMLE	0.976	0.225	0.390	1.580

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Remaining lifetime prediction for nonlinear degradation device with random effect

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