Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 188, Issue -, Pages 515-522Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2019.04.002
Keywords
Accelerated life tests; Bootstrap; Change-point analysis; Coefficient of variation; Empirical likelihood; Reliability
Funding
- National Natural Science Foundation of China
- NSFC [11501162, NSAF U1430125]
- Natural Science Foundation of Hebei Province of China [A2018208058]
- Department of Education of Hebei Province [QN2018077]
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In the accelerated life tests, the common failure mechanism is considered as a necessary condition for the extrapolated procedure. The traditional extrapolation model may become unreliable if the failure mechanisms under the accelerated stress levels are different from that under the normal operating condition. In this paper, we propose a change-point model for the coefficients of variation to fit the abrupt change behavior of the failure mechanisms with a nonparametric empirical likelihood approach. The related statistical inferences of the proposed model are studied to test whether there exists a change and estimate the corresponding location of the change. Monte Carlo simulations are conducted to investigate the performance of the proposed change-point test model. For the small sample data, a bootstrapping method is presented as an alternative detecting procedure. The detailed calculation process is illustrated by the lifetime data of the metal oxide semiconductor transistors in the power distribution system of Chinese Tiangong aircrafts.
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