Bearing fault diagnosis based on speed signal and CNN model

Author:

Guo Ziran,Yang Ming,Huang Xu

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Energy

Reference15 articles.

1. Data-driven approaches for diagnosis of incipient faults in Dc motors;Munikoti;IEEE Trans Ind Inf Srinivasan,2019

2. Jin Woo Oh, Dogun Park, Jongpil Jeong, Fault Detection for Lubricant Bearing with Cnn, in: 2nd international conference on intelligent autonomous systems, 2019, pp. 142–145, (2019).

3. Ji-Hoon Han, Dong-Jin Choi, Sang-Uk Park, Kim, Hyeong-Seob, Motor Fault Diagnosis Using Cnn Based Deep Learning Algorithm Considering Motor Rotating Speed, in: IEEE 6th international conference on industrial engineering and applications, 2019, pp. 440–445, (2019).

4. A deep learning-based remaining useful life prediction approach for bearings;Cheng;IEEE/ASME Trans Mechatronics,2020

5. Ji-Hoon Han, Dong-Jin Choi, Sang-Uk Park, Sun-Ki Hong, Data Preprocessing Method in Motor Fault Diagnosis Using Unsupervised Learning, in: 19th international conference on control, automation and systems, 2019, pp. 1508–1511, (2019).

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