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Remaining useful life estimation based on Wiener degradation processes with random failure threshold

  • Mechanical Engineering, Control Science and Information Engineering
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Abstract

Remaining useful life (RUL) estimation based on condition monitoring data is central to condition based maintenance (CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold (RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization (EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.

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Authors and Affiliations

  1. High-Tech Institute of Xi’an, Xi’an, 710025, China

    Sheng-jin Tang  (唐圣金), Chuan-qiang Yu  (于传强), Yong-bao Feng  (冯永保), Jian Xie  (谢建), Qin-he Gao  (高钦和) & Xiao-sheng Si  (司小胜)

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  1. Sheng-jin Tang  (唐圣金)
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  2. Chuan-qiang Yu  (于传强)
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  3. Yong-bao Feng  (冯永保)
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  4. Jian Xie  (谢建)
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  5. Qin-he Gao  (高钦和)
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  6. Xiao-sheng Si  (司小胜)
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Corresponding author

Correspondence to Chuan-qiang Yu  (于传强).

Additional information

Foundation item: Projects(51475462, 61174030, 61473094, 61374126) supported by the National Natural Science Foundation of China

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Tang, Sj., Yu, Cq., Feng, Yb. et al. Remaining useful life estimation based on Wiener degradation processes with random failure threshold. J. Cent. South Univ. 23, 2230–2241 (2016). https://doi.org/10.1007/s11771-016-3281-z

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  • DOI: https://doi.org/10.1007/s11771-016-3281-z

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