A new method of nonlinear feature extraction for multi-fault diagnosis of rotor systems

Noise and Vibration Worldwide

Volumn 41, Issue 10, 2010, Pages 29-37

  Li, Zhixiong ^a   Yan, Xinping ^a   Yuan, Chengqing ^a   Zhao, Jiangbin ^a   Peng, Zhongxiao ^b  

^a WUHAN UNIVERSITY OF TECHNOLOGY   (China)

^b JAMES COOK UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BREAK DOWN; CLASSIFICATION RATES; COUPLED ROTORS; DIAGNOSTIC SYSTEMS; ECONOMIC LOSS; FAULT DIAGNOSIS; FAULT FEATURE; FAULT IDENTIFICATIONS; FEATURE EXTRACTION AND SELECTION; FEATURE EXTRACTION METHODS; FEATURE SPACE; HIGH-DIMENSIONAL DATASET; INCIPIENT FAULT DIAGNOSIS; INTRINSIC STRUCTURES; LITERATURE REVIEWS; LOCALLY LINEAR EMBEDDING; MANIFOLD LEARNING ALGORITHM; MECHANICAL FAULT DIAGNOSIS; MULTI-FAULT DETECTION; MULTI-FAULT DIAGNOSIS; MULTIPLE DEFECTS; NEAREST NEIGHBOUR; NOISE AND VIBRATION; NONLINEAR FEATURE EXTRACTION; NONLINEAR FEATURES; NONLINEAR PROPERTIES; NORMAL OPERATIONS; OBSERVATION DATA; RECOVERED SIGNALS; ROTOR FAULT DIAGNOSIS; ROTOR SYSTEMS; ROTOR VIBRATIONS; STATISTICAL FEATURES; SUPERVISED LOCALLY LINEAR EMBEDDING; VIBRATION DATA;

ADAPTIVE ALGORITHMS; FAULT DETECTION; FREQUENCY BANDS; INDEPENDENT COMPONENT ANALYSIS; INDUSTRIAL APPLICATIONS; LEARNING ALGORITHMS; MACHINERY; MECHANICAL PROPERTIES; NONLINEAR ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; QUALITY ASSURANCE; RELIABILITY; ROTORS (WINDINGS); SIGNAL PROCESSING; VIBRATION ANALYSIS; WAVELET TRANSFORMS;

FEATURE EXTRACTION;

EID: 78650314445     PISSN: 09574565     EISSN: None     Source Type: Journal    
DOI: 10.1260/0957-4565.41.10.29     Document Type: Article

References (33)

1. C. Kral, T. Habetler, and R. Harley, "Detection of mechanical imbalances of induction machines without spectral analysis of time-domain signals," IEEE Trans. Ind. Appl., vol. 40, pp. 1101-1106, August 2004.
2. J. Cheng , D. Yu , J. Tang, and Y. Yang, "Local rub-impact fault diagnosis of the rotor systems based on EMD," Mech. Mach. Theory, vol. 44, pp. 784-791, April 2009.
3. R. F. Beatty, "Differentiating rotor response due to radial rubbing," J. Vib. Acoust. Stress. Reliab. Des., vol. 107, pp. 151-160, April 1985.
4. Y. Lei, Z. He, and Y. Zi, "Application of the EEMD method to rotor fault diagnosis of rotating machinery," Mech. Syst. Signal. Process., vol. 23, pp. 1327-1338, May 2009.
5. F. Wu and G. Meng, "Time-frequency feature extraction without cross-terms based on acoustic signal in rotor malfunctions," Key Eng. Mat., vol. 293-294, pp. 67-474, 2005.
6. S. Lee and Y. Choi, "Fault diagnosis of partial rub and looseness in rotating machinery using Hilbert-Huang transform," J. Mech. Sci. Technol., vol. 22, pp. 2151-2162, November 2008.
7. H. Ma, W. Sun, Z. Ren, and B. Wen, "Feature Extraction of Rotor Systems with Coupling Fault with Crack and Rub-impact," Proc. Int. Congr. Image Signal Process., CISP, vol. 2009, pp. 1-5, October 2009.
8. Z. Li, X. Yan, C. Yuan, and L. Li, "Gear Multi-Faults Diagnosis of a Rotating Machinery Based on Independent Component Analysis and Fuzzy K-Nearest Neighbor," Adv. Mater. Res., vol. 108-111, pp. 1033-1038, May 2010.
9. G. Gelle and M. Colas, "Blind source separation applied to rotating machine monitoring and fault detection," Noise Vib. Worldwide, vol. 32, pp. 11-16, October 2001. (Pubitemid 43063920)
10. A. Hyvärinen, P. Hoyer, and M. Inki, "Topographic independent component analysis," Neural Comput., vol. 13, pp. 1527-1558, January 2001.
11. D. P. Acharya and G. Panda, "A review of independent component analysis techniques and their applications," IETE Tech. Rev., vol. 25, pp. 320-332, November 2008.
12. Y. Guo and K. Tan, "Order-crossing removal in Gabor order tracking by independent component analysis," J. Sound Vib., vol. 325, pp. 471-488, August 2009.
13. Z. Li, Y. He, F. Chu, J. Han, and W. Hao, "Fault recognition method for speed-up and speed-down process of rotating machinery based on independent component analysis and Factorial Hidden Markov Model," J. Sound Vib., vol. 291, pp. 60-71, March 2006.
14. N. Li, M. Chen , Y. Fang, and H. Li, "Fault diagnose of rotating system based on ICA with reference and RBF networks," Proc. IEEE Int. Conf. Netw. Sensing Contr., ICNSC'06, vol. 2006, pp. 174-178, April 2006.
15. W. Jiao and Y. Chang, "ICA-MLP classifier for Fault diagnosis of Rotor System," Proc. IEEE Int. Conf. Autom. Logist., ICAL, vol. 2009, pp. 997-1001, August 2009.
16. H. Ma, et al., "Time-frequency features of two types of coupled rub-impact faults in rotor systems," J. Sound Vib., vol. 321, pp. 1109-1128, April 2009.
17. A. Widodo and B. Yang, "Wavelet support vector machine for induction machine fault diagnosis based on transient current signal," Expert Sys. Appl., vol. 35, pp. 307-316, August 2008.
18. M. Belkin and P. Niyogi, "Laplacian Eigenmaps for Dimensionality Reduction and Data Representation," Neural Comput., vol. 15, pp. 1373-1396, June 2003.
19. J. B. Tenenbaum, V. Silva, and J. C. Langford, "A global geometric framework for nonlinear dimensionality reduction," Science, vol. 290, pp. 2319-2323, December 2000.
20. S. Roweis and L. Saul, 'Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, pp. 2323-2326, December 2000.
21. Q. Jiang, M. Jia, J. Hu and F. Xu, "Machinery fault diagnosis using supervised manifold learning," Mech. Syst. Signal Proces., vol. 23, pp. 2301-2311, October 2009.
22. J. Yang, J. Xu, and D. Yang, "Noise reduction method for nonlinear time series based on principal manifold learning and its application to fault diagnosis," Chin. J. Mech. Eng Engl. Ed., vol. 42, pp. 154-158, August 2006.
23. D. Wang, H. Lin, "Feature extraction based on supervised kernel locality preserving projection algorithm and application to fault diagnosis," Proc. Int. Conf. Electron. Meas. Instrum., ICEMI, vol. 2009, pp. 1553-1557, August 2009.
24. M. Li, J. Xu, J. Yang, D. Yang, and D. Wang, "Multiple manifolds analysis and its application to fault diagnosis," Mech. Syst. Signal. Process., vol. 23, pp. 2500-2509, November 2009.
25. G. Wang, Y. Liu, and X. Zhao, "Fault diagnosis of rolling bearings based on LLE-KFDA," Mater. Sci. Forum, vol. 626-627, pp. 529-534, September 2009.
26. Y. Lei, M. J. Zuo, Z. He, and Y. Zi, "A multidimensional hybrid intelligent method for gear fault diagnosis," Expert Sys. Appl., vol. 37, pp. 1419-1430, March 2010.
27. Y. Pan, G. S. Sam, and A. M. Abdullah, "Weighted locally linear embedding for dimension reduction," Pattern Recogn., vol. 42, pp. 798-811, May 2009.
28. T. Hastie and R. Tibshirani, "Discriminant adaptive nearest neighbor classification," IEEE Trans. Pattern Anal. Mach. Intell., vol. 18, pp. 607-616, June 1996.
29. Y. Zhang, C. Zhang, and D. Zhang, "Distance metric learning by knowledge embedding," Pattern Recogn., vol. 37, pp. 161-163, January 2004.
30. J. Yu, J. Amores, N. Sebe, P. Radeva, and Q. Tian, "Distance learning for similarity estimation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, pp. 451-462, March 2008.
31. J. Jing and G. Meng, "A novel method for multi-fault diagnosis of rotor system," Mech. Mach. Theory, vol. 44, pp. 697-709, April 2009.
32. A. K. Jalan and A. R. Mohanty, "Model based fault diagnosis of a rotor-bearing system for misalignment and unbalance under steady-state condition," J. Sound Vib., vol. 327, pp. 604-622, November 13, 2009.
33. J. M. Keller, M. R. Gray and J. A. Givens, "Fuzzy K-Nearest Neighbor Algorithm," IEEE Trans. Syst. Man Cybern., vol. 15, pp. 580-585, 1985.