Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery

Author:

Wang Biao,Lei Yaguo,Yan Tao,Li Naipeng,Guo LiangORCID

Funder

National Key R&D Program

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference38 articles.

1. Machinery health prognostics: a systematic review from data acquisition to rul prediction;Lei;Mech. Syst. Signal Process.,2018

2. Ensemble of optimized echo state networks for remaining useful life prediction;Rigamonti;Neurocomputing,2018

3. Finite-horizon fault estimation under imperfect measurements and stochastic communication protocol: dealing with finite-time boundedness;Dong;Int. J. Robust Nonlinear Control,2019

4. Set-membership filtering for state-saturated systems with mixed time-delays under weighted try-once-discard protocol;Li;IEEE Trans. Circuits Syst. II: Express Briefs,2019

5. A hybrid prognostics approach for estimating remaining useful life of rolling element bearings;Wang;IEEE Trans. Reliab.,2018

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