Volume 35 Issue 9
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XU Lingtian, SHEN Xuejin, JIANG Shuang. Reliability assessment of bearings with incomplete performance degradation data under small and non-failure samples[J]. Journal of Aerospace Power, 2020, 35(9): 1977-1987. doi: 10.13224/j.cnki.jasp.2020.09.020
Citation: XU Lingtian, SHEN Xuejin, JIANG Shuang. Reliability assessment of bearings with incomplete performance degradation data under small and non-failure samples[J]. Journal of Aerospace Power, 2020, 35(9): 1977-1987. doi: 10.13224/j.cnki.jasp.2020.09.020
shu

Reliability assessment of bearings with incomplete performance degradation data under small and non-failure samples

doi: 10.13224/j.cnki.jasp.2020.09.020
  • 1.

    School of Mechanical and Electrical Engineering and Automation,Shanghai University,Shanghai 200444,China

  • 2.

    Technology Center,Shanghai Tianan Bearing Corporation Limited,Shanghai 201108,China

  • Received Date: 2020-03-09
  • Publish Date: 2020-09-28
    Abstract
  • A reliability assessment with incomplete performance degradation data under small and non-failure samples was made. A data-based random number simulation method proposed by Taylor and Thompson was used to complete the missing sample degradation data,the Bootstrap method was used to expand the sample size,and the reliability assessment of the bearings was analyzed based on the degradation trajectory-based method. The vibration degradation of 7 groups of tested bearings was selected and analyzed under the conditions of complete and incomplete performance degradation data,respectively. It was found that the method proposed can obtain accurate reliability assessment and the absolute value difference between two results was controlled within 01. The above results were compared with the results obtained by analyzing the lifetime data through the weighted E-Bayes method and the maximum likelihood estimation. It was found that the results obtained by the method were better,and the actual error was within 10% compared with the actual test,showing positive practical significance for improving the evaluation accuracy and reducing the test cost.

     

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