Reliability Assessment Method Based on Small Sample Accelerated Life Test Data

Aiming at the problems of small sample size, few test failure data and low reliability evaluation efficiency in accelerated life test of high-reliability and long-life products, an improved virtual augmentation Bootstrap-Bayes reliability evaluation method based on small sample accelerated life test data was proposed. Firstly, the test data under various stress conditions are augmented by virtual fusion. Secondly, the empirical distribution function and bootstrap sampling method are improved, and the kernel density estimation method is used to fit the density distribution of test data as prior information. Then, the parameter estimates of the test data are obtained by Gibbs sampling combined with Bayes formula. Finally, the reliability index under normal stress level is obtained by accelerating model extrapolation. The feasibility of the proposed method is verified by the accelerated life test data of a type of Ship communication equipment.