Rolling bearing fault diagnosis using optimal ensemble deep transfer network-Reference-Cited by-同舟云学术

Rolling bearing fault diagnosis using optimal ensemble deep transfer network

Published:2021-02 Issue: Volume:213 Page:106695
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Li Xingqiu,Jiang Hongkai,Wang Ruixin,Niu Maogui

Funder

National Natural Science Foundation of China

Synergy Innovation Foundation of the University and Enterprise for Graduate Students in Northwestern Polytechnical University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference45 articles.

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3. Deep learning and its applications to machine health monitoring;Zhao;Mech. Syst. Signal Process.,2019

4. Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization;Jia;Mech. Syst. Signal Process.,2018

5. Deep residual networks with dynamically weighted wavelet coefficients for fault diagnosis of planetary gearboxes;Zhao;IEEE Trans. Ind. Electron.,2018

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