Abstract

In the lifetime test of rolling bearings under type I censoring with a small sample, the confidence interval of reliability needs to be evaluated to ensure safe and reliable operation of a system like an aerospace system. Thus the probability density function of Weibull distribution parameters must be attained. Owing to very few test data and for lack of prior knowledge, it is difficult to take it out for prevailing methods like the moment method, the maximum likelihood method and the Harris method. For this end, the bootstrap likelihood maximum-entropy method is proposed by fusing the bootstrap method, the maximum likelihood method and the Harris method. The lifetime test data with the small sample are made into the simulated parameter data with the large sample to obtain the probability density function on the parameters. The confidence intervals of the Weibull distribution parameters are estimated and the confidence interval of reliability is calculated. The tests of the complete large-sample data, the complete small-sample data and the incomplete small-sample data are produced to prove effectiveness of the proposed method. Results show that the proposed method can assess the confidence interval of the reliability without any prior information on the Weibull distribution parameters.

Keywords:

Bearing failure, fatigue testing, life assessment, probability, reliability analysis,

References

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.