Volume 45 Issue 11
Nov.  2019
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GAI Bingliang, TENG Kenan, WANG Haowei, et al. Reliability assessment for electronic components with bivariate accelerated degradation based on random correlation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(11): 2237-2246. doi: 10.13700/j.bh.1001-5965.2019.0130(in Chinese)
Citation: GAI Bingliang, TENG Kenan, WANG Haowei, et al. Reliability assessment for electronic components with bivariate accelerated degradation based on random correlation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(11): 2237-2246. doi: 10.13700/j.bh.1001-5965.2019.0130(in Chinese)

Reliability assessment for electronic components with bivariate accelerated degradation based on random correlation

doi: 10.13700/j.bh.1001-5965.2019.0130
Funds:

National Natural Science Foundation of China 51605487

More Information
  • Corresponding author: TENG Kenan, E-mail: Tengkn@sina.com
  • Received Date: 27 Mar 2019
  • Accepted Date: 28 May 2019
  • Publish Date: 20 Nov 2019
  • Targeting at the difficulty of reliability analysis for electronic components with bivariate correlation accelerated degradation data, a reliability assessment method based on random correlation is proposed. The Wiener process model with random effect is used to model the marginal degradation process considering the individual difference, and the relationship between model parameters and acceleration stress is established by using acceleration factor constant principle. Then, a bivariate degradation model with random correlation based on Copula function is established. A two-stage Bayesian method is introduced to facilitate the parameter estimation, and the scatter plots, deviance information criterion (DIC) and the non-parametric estimation of Kendall τ are used for random correlation model selection. The reliability calculation is carried out by Monte Carlo simulation method. Finally, an example is used to verify the effectiveness of the proposed method.The paper has significant meaning for the storage reliability assessment considering individual differences.

     

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