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Residual useful life estimation for products with two performance characteristics based on a bivariate Wiener process

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  • Tianyu Liu
  • Zhengqiang Pan
  • Quan Sun
  • Jing Feng
  • Yanzhen Tang

Abstract

Residual useful life estimation plays an important role in the field of prognostics and health management, and condition-based maintenance. This article concerns the issue of residual useful life estimation for degraded components with two performance characteristics. A bivariate Wiener process with random effects is used to model the evolution of two performance characteristics, which are dependent on each other. A bootstrap method is used to estimate the initial parameters with history of degradation data. Once the new degradation information for an individual component is available, the hyper-parameters of the random effects in the model are first updated by the Bayesian theorem. And then, we use a Monte Carlo simulation method to estimate the posterior distribution of residual useful life approximately. Via a simulation study and a case study on Lithium-ion batteries, the effectiveness and validity of the proposed approach are demonstrated.

Suggested Citation

  • Tianyu Liu & Zhengqiang Pan & Quan Sun & Jing Feng & Yanzhen Tang, 2017. "Residual useful life estimation for products with two performance characteristics based on a bivariate Wiener process," Journal of Risk and Reliability, , vol. 231(1), pages 69-80, February.
    • Handle: RePEc:sae:risrel:v:231:y:2017:i:1:p:69-80
    DOI: 10.1177/1748006X16683317
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    References listed on IDEAS

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