Convolutional neural network based on attention mechanism and Bi-LSTM for bearing remaining life prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-02503-2.pdf
Reference42 articles.
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3. Zhu J, Chen N, Peng W (2019) Estimation of bearing remaining useful life based on multiscale convolutional neural network[J]. IEEE Trans Ind Electron 66(4):3208–3216
4. Liu R, Yang B, Hauptmann AG (2019) Simultaneous bearing fault recognition and remaining useful life prediction using joint loss convolutional neural network[J]. IEEE Trans Ind Inf PP(99):1–1
5. Qiu G, Gu Y, Chen J (2019) Selective health indicator for bearings ensemble remaining useful life prediction with genetic algorithm and Weibull proportional hazards model[J]. Measurement 150:107097
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