Motor Fault Diagnosis Based on Convolutional Neural Networks

Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis

Volumn 37, Issue 6, 2017, Pages

  Wang, Lihua ^a   Xie, Yangyang ^a   Zhou, Zixian ^a   Zhang, Yonghong ^a   Zhao, Xiaoping ^a  

^a NANJING UNIVERSITY OF INFORMATION SCIENCE AND TECHNOLOGY   (China)

Author keywords

Convolutional neural networks; Motor; Short time Fourier transform; Vibration signal

Indexed keywords

CONVOLUTION; FAILURE ANALYSIS; INDUCTION MOTORS; MOTORS; NEURAL NETWORKS; PATTERN RECOGNITION; SIGNAL PROCESSING;

CONVOLUTIONAL NEURAL NETWORK; DENOISING AUTOENCODER; FAULT DIAGNOSIS METHOD; NON-LINEAR RELATIONSHIPS; PRACTICAL EXPERIENCE; SHORT TIME FOURIER TRANSFORMS; SIGNAL PROCESSING THEORY; VIBRATION SIGNAL;

FAULT DETECTION;

EID: 85044172793     PISSN: 10046801     EISSN: None     Source Type: Journal    
DOI: 10.16450/j.cnki.issn.1004-6801.2017.06.021     Document Type: Article

References (17)

1. Mehrjou M R, Mariun N, Marhaban M H, et al. Rotor fault condition monitoring techniques for squirrel-cage induction machine-A review[J]. Mechanical Systems and Signal Processing, 2011, 25(8): 2827-2848.
2. Cruz Z M A, Cardoso A J M, Carvalho J F S, et al. Rotor cage fault diagnosis in three-phase induction motors by Park's vector approach[C]//Coference Record of The IEEE Industry Applications Society Annual Meeting. Orland Florida, USA: [s.n.], 1955: 642-646.
3. Cruz Z M A, Cardoso A J M. Rotor cage fault diagnosis in three-phase induction motors by extend Park's vector approach[J]. Electric Machines and Power Systems, 2000, 28(3): 289-299.
4. Cruz Z M A, Cardoso A J M. Stator winding fault diagnosis in three-phase synchronous and asynchronous motors by the extend Park's vector approach[J]. IEEE Trans on Industry Applications, 2001, 37(5): 1227-1233.
5. Liu Zhenxing, Yin Xianggen, Zhang Zhe. Online monitoring and diagnosis way based on spectrum analysis of Hilbert modulus in induction motors[J]. Proceedings of the CSEE, 2003, 23(7): 158-161.(in Chinese)
6. Fang Ruiming, Zheng Lixin, Ma Hongzhong, et al. Fault diagnosis for rotor of induction machine based on MCSA and SVM[J]. Chinese Journal of Scientific Instrument, 2007, 28(2): 252-257. (in Chinese)
7. Yang Jiangtian, Zhao Mingyuan. Fault diagnosis of traction motor bearings using modified bispectrum and empirical mode decomposition[J]. Proceedings of the CSEE, 2012, 32(18): 176-122. (in Chinese)
8. Qian Huaming, Wang Wensheng. Improved wavelet neural network based on genetic algorithm and its application in fault diagnosis of motor[J]. Journal of Electronic Measurement and Instrument, 2009, 23(3): 81-86. (in Chinese)
9. Li Xuejun, Li Ping, Jiang Lingli, et al. Fault diagnosis method of asynchronous motor based on heterogeneous information feature fusion[J]. Chinese Journal of Scientific Instrument, 2013, 34(1): 227-233. (in Chinese)
10. LeCun Y, Boser B, Denker J S, et al. Handwritten digit recognition with a back-propagation network[C]//Advance in Neural Information Processing Systems. San Francisco, CA: Morgan Kaufmanu Publishers, 1990: 396-404.
11. Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural network[C]//Advances in Neural Information Processing System. Red Hook, NY: Curran Associates, 2012: 1097-1105.
12. Wang Haibo, Chen Yanxiang, Li Yanqiu. Face recognition method based on principal component analysis and Softmax regression model[J]. Journal of Hefei University of Technology, 2015, 38(6): 759-763.(in Chinese)
13. Zeiler M D, Fergus R. Visualizing and understanding convolutional neural networks[C]//Computer Vision-ECCV 2014. [S. L.]: Spring Internatinal Publishing, 2014: 818-833.
14. Wang Lihua, Tao Runzhe, Zhang Yonghong. Feature extraction of rolling bearing based on CEEMD-WPT[J]. Journal of Vibration, Measurement & Diagnosis, 2017, 37(1): 181-188. (in Chinese)
15. Hao Yan, Wang Taiyong, Wan Jian, et al. Mechanical fault diagnosis based on empirical mode decomposition and generalized dimension[J]. Journal of Jilin University: Engineering and Technology Edition, 2012, 42(2): 392-396. (in Chinese)
16. Sun Weixiang, Chen Jin, Wu Liwei, et al. Rotor fault diagnosis based on PCA and decision tree[J]. Journal of Vibration and Shock, 2007, 26(3): 72-74. (in Chinese)
17. Vapnik V N. The nature of statistical learning theory[M]. New York: Springer-Verlag, 1995: 988-999.