A deep feature enhanced reinforcement learning method for rolling bearing fault diagnosis

Author:

Wang Ruixin,Jiang HongkaiORCID,Zhu Ke,Wang Yanfeng,Liu Chaoqiang

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems,Building and Construction

Reference41 articles.

1. An improved eemd with multiwavelet packet for rotating machinery multi-fault diagnosis;Jiang;Mech. Syst. Sig. Process.,2013

2. Feature Enhanced Using Hierarchical Dispersion Entropy for Rolling Bearing Fault Diagnosis[J];Xue;IEEE Trans. Instrum. Measur.,2021

3. Adaptive feature extraction using sparse coding for machinery fault diagnosis[J];Liu;Mech. Syst. Sig. Process.,2011

4. Guoan, Chen, Gongbo, et al. Fault diagnosis of rotating machinery with a novel statistical feature extraction and evaluation method, Mech. Syst. Signal Process., 2015.

5. Time-Varying and Multiresolution Envelope Analysis and Discriminative Feature Analysis for Bearing Fault Diagnosis;Kang;IEEE Trans. Ind. Electron.,2015

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