Bearing life prediction method based on the improved FIDES reliability model
Author:
Publisher
Elsevier BV
Subject
Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality
Reference35 articles.
1. Remaining useful life prediction of bearings under different working conditions using a deep feature disentanglement-based transfer learning method;Hu;Reliab Eng Syst Safe,2022
2. Fault prediction of bearings based on LSTM and statistical process analysis;Liu;Reliab Eng Syst Safe,2021
3. A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings;Cao;Reliab Eng Syst Safe,2021
4. An improved Wiener process model with adaptive drift and diffusion for online remaining useful life prediction;Wang;Mech Syst Signal Proc,2019
5. Inverse Gaussian process models for degradation analysis: a Bayesian perspective;Peng;Reliab Eng Syst Safe,2014
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1. Degradation modeling under time-varying operating conditions: Inference and prognosis with particle filter;Reliability Engineering & System Safety;2024-05
2. An Online Fault Detection and Remaining Life Prediction Method Based on SVDD for Rolling Bearings;IEEE Transactions on Instrumentation and Measurement;2024
3. Time-variant reliability analysis of angular contact ball bearing considering the coupled effect of rolling contact fatigue damage and wear;Reliability Engineering & System Safety;2024-01
4. Probabilistic rolling contact fatigue approaches with a loading level relevance;International Journal of Fatigue;2023-12
5. Research on Remaining Useful Life Prediction of Bearings Based on MBCNN-BiLSTM;Applied Sciences;2023-06-29
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