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A degradation-shock dependent competing failure processes based method for remaining useful life prediction of drill bit considering time-shifting sudden failure threshold

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  • Feng, Tingting
  • Li, Shichao
  • Guo, Liang
  • Gao, Hongli
  • Chen, Tao
  • Yu, Yaoxiang

Abstract

Accurate remaining useful life (RUL) prediction of the drill bit is central to ensuring the processing quality of products and enhancing processing safety and reliability. However, the majority of current methods are confined to considering the wear degradation during the drilling and ignore the combined effect of wear degradation and random shock on RUL. Therefore, it is difficult to the sudden failure prediction of the drill bit. To address this limitation, a degradation-shock dependent competing failure processes (DCFPs) based method considering time-shifting sudden failure threshold is proposed in this paper for RUL prediction. First, a degradation-shock DCFPs model is established based on the processing characteristics of the drill bit. Further, the expressions of reliability function and useful life taking into account the time-shifting sudden failure threshold are derived. Then, based on the Bayesian method, a two-step maximum likelihood estimation (MLE) is designed for parameter estimation, and the crucial parameters are updated utilizing a local gaussian importance resampling particle filter. Finally, a carbon composite laminate drilling experiment is provided for demonstration. Experimental results demonstrate the superiority of the proposed method for drill bit RUL prediction, especially when the drill bit is chipped.

Suggested Citation

  • Feng, Tingting & Li, Shichao & Guo, Liang & Gao, Hongli & Chen, Tao & Yu, Yaoxiang, 2023. "A degradation-shock dependent competing failure processes based method for remaining useful life prediction of drill bit considering time-shifting sudden failure threshold," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:reensy:v:230:y:2023:i:c:s095183202200566x
    DOI: 10.1016/j.ress.2022.108951
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    References listed on IDEAS

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    1. Wang, Han & Liao, Haitao & Ma, Xiaobing & Bao, Rui, 2021. "Remaining Useful Life Prediction and Optimal Maintenance Time Determination for a Single Unit Using Isotonic Regression and Gamma Process Model," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
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    4. Yan, Tao & Lei, Yaguo & Li, Naipeng & Wang, Biao & Wang, Wenting, 2021. "Degradation modeling and remaining useful life prediction for dependent competing failure processes," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    5. Wu, Bei & Ding, Dong, 2022. "A gamma process based model for systems subject to multiple dependent competing failure processes under Markovian environments," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
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    Cited by:

    1. Kang, Fengming & Cui, Lirong & Ye, Zhisheng & Zhou, Yu, 2024. "Reliability analysis for systems with self-healing mechanism in degradation-shock dependence processes with changing degradation rate," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Hou, WanJun & Peng, Yizhen, 2023. "Adaptive ensemble gaussian process regression-driven degradation prognosis with applications to bearing degradation," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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