A two-stage approach based on Bayesian deep learning for predicting remaining useful life of rolling element bearings - researchr publication related

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Kaijian Chen, Jingna Liu, Wenwu Guo, Xizhao Wang. A two-stage approach based on Bayesian deep learning for predicting remaining useful life of rolling element bearings. Computers & Electrical Engineering, 109(Part B):108745, August 2023. [doi]

The following publications are possibly variants of this publication:

A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element BearingsBiao Wang, Yaguo Lei, Naipeng Li, Ningbo Li. tr, 69(1):401-412, 2020. [doi]

An Adaptive Sparse Graph Learning Method Based on Digital Twin Dictionary for Remaining Useful Life Prediction of Rolling Element BearingsLingli Cui, Xin Wang 0052, Dongdong Liu, Huaqing Wang. tii, 20(9):10892-10900, September 2024. [doi]

A Regularized LSTM Method for Predicting Remaining Useful Life of Rolling BearingsZhao-Hua Liu, Xudong Meng, Hua-Liang Wei, Liang Chen, Bi-Liang Lu, Zhenheng Wang, Lei Chen. ijautcomp, 18(4):581-593, 2021. [doi]

Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman FilterLingli Cui, Xin Wang 0052, Huaqing Wang, Jianfeng Ma. tim, 69(6):2858-2867, 2020. [doi]

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