Transactions of China Electrotechnical Society  2022, Vol. 37 Issue (16): 4250-4258    DOI: 10.19595/j.cnki.1000-6753.tces.210229
Current Issue| Next Issue| Archive| Adv Search |
Reliability Evaluation of Electronic Residual Current Operated Circuit Breakers Based on Improved Bootstrap-Bayes
Liu Guojin, Wang Ze, Li Xiang, Zhao Xingzhou, Miao Jianhua
State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300130 China

Download: PDF (972 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  

As a kind of high reliability and long-life product, the electronic residual current operated circuit breaker has few test data. In order to evaluate its reliability, a reliability evaluation method based on improved Bootstrap-Bayes was proposed. Firstly, with temperature as the accelerated stress, the accelerated degradation test for the residual current operated circuit breaker was carried out. The pseudo failure life was obtained by extrapolating the degradation data, and it was verified to obey the two-parameter Weibull distribution. Then, the GM(1, 1) model was used to expand the experimental data as the prior information, and the parameter estimates were obtained by Gibbs sampling in the Markov Chain Monte Carlo (MCMC) algorithm combined with Bayes formula. Finally, the Arrhenius acceleration model was used to evaluate the reliability of the residual current operated circuit breaker under normal use environment.

Key wordsElectronic residual current operated circuit breaker      GM(1,1) model      Bootstrap sampling      Bayes      Markov Chain Monte Carlo (MCMC)      reliability evaluation     
Received: 24 February 2021     
PACS: TM506  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Liu Guojin
Wang Ze
Li Xiang
Zhao Xingzhou
Miao Jianhua
Cite this article:   
Liu Guojin,Wang Ze,Li Xiang等. Reliability Evaluation of Electronic Residual Current Operated Circuit Breakers Based on Improved Bootstrap-Bayes[J]. Transactions of China Electrotechnical Society, 2022, 37(16): 4250-4258.
URL:  
https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.210229     OR     https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I16/4250
Copyright © Transactions of China Electrotechnical Society
Supported by: Beijing Magtech