Motor Fault Diagnosis Based on Short-time Fourier Transform and Convolutional Neural Network-Reference-Cited by-同舟云学术

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Motor Fault Diagnosis Based on Short-time Fourier Transform and Convolutional Neural Network

Published:2017-11 Issue:6 Volume:30 Page:1357-1368
ISSN:1000-9345
Container-title:Chinese Journal of Mechanical Engineering
language:en
Short-container-title:Chin. J. Mech. Eng.

Author:

Wang Li-Hua,Zhao Xiao-Ping,Wu Jia-Xin,Xie Yang-Yang,Zhang Yong-Hong

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Link

http://link.springer.com/article/10.1007/s10033-017-0190-5/fulltext.html

Reference30 articles.

1. Chuan Li, R V Sanchez, G Zurita, et al. Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals. Mechanical Systems and Signal Processing, 2016, 76–77: 283–293.

2. Ya-Guo Lei, Nai-Peng Li, Jing Lin, et al. Two new features for condition monitoring and fault diagnosis of planetary gearboxes. Journal of Vibration & Control, 2013, 21(4): 755–764.

3. Jun-Jian Hou, Wei-Kang Jiang, Wen-Bo Lu. Application of a near-field acoustic holography-based diagnosis technique in gearbox fault diagnosis. Journal of Vibration & Control, 2013, 19(1): 3–13.

4. A M D Younus, B S Yang. Intelligent fault diagnosis of rotating machinery using infrared thermal image. Expert Systems with Applications, 2012, 39(2): 2082–2091.

5. J. R Ottewill, M Orkisz. Condition monitoring of gearboxes using synchronously averaged electric motor signals. Mechanical Systems & Signal Processing, 2013, 38(2): 482–498.

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