Fault classification of water hydraulic system by vibration analysis with support vector machine

Journal of Testing and Evaluation

Volumn 35, Issue 4, 2007, Pages 408-415

  Chen, H X ^a   Chua, Patrick S K ^a   Lim, G H ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Fault diagnosis; Feature extraction; Neural network; Support vector machine; Water hydraulic system; Wavelet transform

Indexed keywords

FAILURE ANALYSIS; FEATURE EXTRACTION; NEURAL NETWORKS; SUPPORT VECTOR MACHINES; VIBRATION ANALYSIS; WAVELET ANALYSIS; WAVELET TRANSFORMS; COMPUTER AIDED DIAGNOSIS; EXTRACTION; FAULT DETECTION; HYDRAULIC MACHINERY; HYDRAULIC MOTORS; TIME DOMAIN ANALYSIS;

FAULT CLASSIFICATION; WATER HYDRAULIC SYSTEMS;

HYDRAULIC MOTORS; SUPPORT VECTOR MACHINES;

FAULT CLASSIFICATION; FAULTS DIAGNOSIS; FEATURES EXTRACTION; NEURAL-NETWORKS; SUPPORT VECTORS MACHINE; VIBRATION SIGNAL; VIBRATIONS ANALYSIS; WATER HYDRAULIC SYSTEMS; WAVELET-ANALYSIS; WAVELETS TRANSFORM;

EID: 35348836785     PISSN: 00903973     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (30)

1. Danfoss, Inc. http://www.danfoss.com/Nessie/Introduction/index.asp.
2. Krutz, G. W. and Chua, P. S. K., "Water Hydraulics - Theory and Applications 2004," Workshop on Water Hydraulics, Agricultural Equipment Technology Conference (AETC'04), 2004.
3. Chen, H. X., Lim, G. H., and Chua, P. S. K., "Fault Detection in a Water Hydraulic Motor Using a Wavelet Transform," J. Test. Eval., Vol. 34, No. 4, 2006, pp. 342-350.
4. Sorensen, P., "News and Trends by the Industrial Application of Water Hydraulics," The 6th Scandinavian International Conference on Fluid Power, 1999, pp. 651-674.
5. Trostmann, E. and Clausen, P. M., "Hydraulic Components Using Tap Water as Pressure Medium," The 4th Scandinavian International Conference on Fluid Power, 1995, pp. 942-954.
6. Simon, U., "Water Hydraulic Power-The Technology Matures (Putting Water to Work)," National Fluid Power Association Technical Paper Series, 1996, pp. 7-13.
7. Tan, A. C. H., Chua, P. S. K., and Lim, G. H., "Condition Monitoring of a Water Hydraulic Cylinder by Vibration Analysis," J. Test. Eval., Vol. 28, No. 6, 2000, pp. 507-512.
8. Watton, J., Lucca-Negro, O., and Stewart, J. C., "On-line Approach to Fault Diagnosis of Fluid Power Cylinder Drive Systems," Proceedings of the Institution of Mechanical Engineers, Part I, Journal of System & Control Engineering, Vol. 208, No. 14, 1994, pp. 249-262.
9. Daley, S. and Wang, H., "Fault Diagnosis in Fluid Power Systems," Engineering Simulation, Vol. 13, No. 6, 1996, pp. 993-1008.
10. Stewart, C. and Watton, J., "Some Aspects of Rule-based Expert Systems Design for On-line Fault Diagnosis of Fluid Power Systems," American Society of Mechanical Engineers, Petroleum Division (Publication) PD, Design: Analysis, Synthesis, and Application, Vol. 64, 1994, pp. 457-461.
11. Gao, Q., Zhang, Q., and Kong, X., "Wavelet-based Pressure Analysis for Hydraulic Pump Health Diagnosis," Trans. ASAE, Vol. 46, No. 4, 2003, pp. 969-976.
12. Shiroishi, J., Li, Y., Liang, T., Kurfess, T., and Danyluk, S., "Bearing Condition Diagnostics Via Vibration and Acoustic Emission Measurements," Mech. Syst. Signal Process., Vol. 11, No. 5, 1997, pp. 693-705.
13. Lee, S. K. and White, P. R., "Enhancement of Impulsive Noise and Vibration Signals for Fault Detection in Rotating and Reciprocating Machinery," J Sound Vib., Vol. 217, No. 8, 1998, pp. 485-505.
14. Baydar, N. and Ball, A. A., "Comparative Study of Acoustic and Vibration Signals in Detection of Gear Failures Using Wigner-Ville Distribution," Mech. Syst. Signal Process., Vol. 15, No. 6, 2001, pp. 1091-1107.
15. Chen, Z. and Mechefske, C. K., "Machine Signature Identification by Analysis of Impulse Vibration Signals," J. Sound Vib., Vol. 244, No. 1, 2001, pp. 155-167.
16. Peng, Z., He, Y., Lu, Q., and Chu, F., "Feature Extraction of the Rub-impact Rotor System By Means of Wavelet Analysis," J. Sound Vib., Vol. 259, No. 4, 2003, pp. 1000-1010.
17. Chui, C. K., An Introduction to Wavelets, Academic Press, Boston, 1992.
18. Ruskai, M. B., Wavelets and Their Applications, Jones and Barlett, Boston, 1992.
19. Sekhar, S., "Crack Detection Through Wavelet Transform for a Run-up Motor," J Sound Vib., Vol. 259, No. 2, 2003, pp. 461-472.
20. Le, T. T., Watton, J., and Pham, D. T., "An Artificial Neural Network Based Approach to Fault Diagnosis and Classification of Fluid Power Systems," Proceedings of the I MECH E, Part I, Journal of Systems & Control, Engineering, Vol. 211, 1997, pp. 307-317.
21. Crowther, W. J., Edge, K. A., Burrows, C. R., Atkinson, R. M., and Woollons, D. J., "Fault Diagnosis of a Hydraulic Actuator Circuit Using Neural Networks - An Output Vector Space Classification Approach," Proceedings of I MECH E, Part I, Journal of Systems & Control Engineering, Vol. 212, 1998, pp. 57-68.
22. Le, T. T., Watton, J., and Pham, D. T., "Fault Classification of Fluid Power Systems Using a Dynamics Feature Extraction Technique and Neural Networks," Proceedings of the I MECH E, Part I, Journal of Systems & Control Engineering, Vol. 212, 1998, pp. 87-97.
23. Samanta, B. and Al-Balushi, K. R., "Use of Time Domain Features for the Neural Network Based Fault Diagnosis of a Machine Tool Coolant System," Proceedings of the I MECH E, Part I, Journal of Systems & Control Engineering, Vol. 215, 2001, pp. 199-207.
24. Lott, P. W. and Griffiths, A. J., "Fault Diagnosis of Pumping Machinery Using Artificial Neural Networks," Proceedings of the I MECH E, Part E, Journal of Process Mechanical Engineering, Vol. 211, 1997, pp. 185-194.
25. Vapnik, V., The Nature of Statistical Learning Theory, Springer, Berlin, 1995.
26. Nandi, A. K., "Advanced Digital Vibration Signal Processing for Condition Monitoring," Proceedings of COMADEM, Houston, TX, 2000, pp. 129-143.
27. Schlkopf, B., "SVMs - A Practical Consequence of Learning Theory,"IEEE Intell. Syst., Vol. 13, 1998, pp. 18-19.
28. Burges, C. J. C., "A Tutorial on Support Vector Machines for Pattern Recognition," Data Min. Knowl. Discov., Vol. 2, 1998, pp. 955-974.
29. Gunn, S. R., "Support Vector Machines for Classification and Regression," Technical report, University of Southampton, Department of Electrical and Computer Science, 1998.
30. Scholkopf, B. and Smola, A. J., Learning with Kernels, Support Vector Machines, Regularization, Optimization, and Beyond, MIT Press, New York.