A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 8 Issue 11
Nov.  2021

IEEE/CAA Journal of Automatica Sinica

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J. D. Lin, Z. Lin, G. B. Liao, and H. P. Yin, "A Novel Product Remaining Useful Life Prediction Approach Considering Fault Effects," IEEE/CAA J. Autom. Sinica, vol. 8, no. 11, pp. 1762-1773, Nov. 2021. doi: 10.1109/JAS.2021.1004168
Citation: J. D. Lin, Z. Lin, G. B. Liao, and H. P. Yin, "A Novel Product Remaining Useful Life Prediction Approach Considering Fault Effects," IEEE/CAA J. Autom. Sinica, vol. 8, no. 11, pp. 1762-1773, Nov. 2021. doi: 10.1109/JAS.2021.1004168

A Novel Product Remaining Useful Life Prediction Approach Considering Fault Effects

doi: 10.1109/JAS.2021.1004168
Funds:  This work was supported by General Program of National Natural Science Foundation of China (61773080), China Central Universities Foundation (2019CDYGZD001), Scientific Reserve Talent Programs of Chongqing University (cqu2018CDHB1B04), and Graduate Research and Innovation Foundation of Chongqing (CYB20065)
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  • In this paper, a novel remaining useful life prediction approach considering fault effects is proposed. The Wiener process is used to construct the degradation process of single performance characteristic with the fault effects. The first passage time based remaining useful life distribution is calculated by assuming fault occurrence moment is a random variable and follows a certain distribution. Expectation maximization algorithm is employed to estimate model parameters, where the fault occurrence moment is considered as a missing data. Finally, a Copula function is used to describe the dependence between the multiple performance characteristics and derive joint remaining useful life (RUL) distribution of product with the fault effects. The effectiveness of the proposed approach is verified by the experiments of turbofan engines.


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    • A degradation model based on Wiener process is proposed considering the fault effects
    • Expectation maximization algorithm is employed to estimate model parameters
    • The Copula function is used to describe the dependence of characteristics
    • The joint RUL distribution of product considering the fault effects is derived


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