Research on Reliability Modeling of Bivariate Correlation Degradation Based on Nonlinear Wiener Process

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The performance of a product tends to degrade gradually with the use process, thus affecting its service life. Therefore, the research on the degradation process is helpful to grasp the residual life of products. Based on nonlinear Wiener process, the paper conducts a bivariate correlation degradation reliability modeling research. Firstly, the overall and partial correlations between two degenerate variables are calculated using the cosine similarity measure. Then, according to the calculation results and the characteristics of each copula function, select the appropriate copula function. Finally, a bivariate degradation model based on nonlinear Wiener process is established. Through the example analysis, the degradation fitting curve and degradation test results of bivariate degraded products are obtained by using the model, which has a good fitting degree and verifies the effectiveness of the model.

Original languageEnglish
Title of host publication13th International Conference on Reliability, Maintainability, and Safety
Subtitle of host publicationReliability and Safety of Intelligent Systems, ICRMS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages223-227
Number of pages5
ISBN (Electronic)9781665486903
DOIs
StatePublished - 2022
Event13th International Conference on Reliability, Maintainability, and Safety, ICRMS 2022 - Hong Kong, China
Duration: 21 Aug 202224 Aug 2022

Publication series

Name13th International Conference on Reliability, Maintainability, and Safety: Reliability and Safety of Intelligent Systems, ICRMS 2022

Conference

Conference13th International Conference on Reliability, Maintainability, and Safety, ICRMS 2022
Country/TerritoryChina
CityHong Kong
Period21/08/2224/08/22

Keywords

  • bivariate correlation degradation
  • copula
  • nonlinear Wiener process
  • reliability modeling

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