Fault diagnosis of power transformer based on multi-layer SVM classifier

Electric Power Systems Research

Volumn 75, Issue 1, 2005, Pages 9-15

  Lv, Ganyun ^a   Cheng, Haozhong ^a   Zhai, Haibao ^a   Dong, Lixin ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Fault diagnosis; Multi layer SVM classifier; Power transformer; Reliability

Indexed keywords

CLASSIFIERS; DATA PROCESSING; DATABASE SYSTEMS; ELECTRIC FAULT CURRENTS; ELECTRIC INSULATING MATERIALS; LEARNING SYSTEMS; MULTILAYERS;

DISSOLVED GAS ANALYSIS (DGA); FAULT DIAGNOSIS; MULTI-LAYER SUPPORT VECTOR MACHINES (SVM) CLASSIFIERS; POWER TRANSFORMERS;

ELECTRIC TRANSFORMERS;

EID: 18844362865     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.epsr.2004.07.013     Document Type: Article

References (24)

1. M.H. Wang A novel extension method for transformer fault diagnosis IEEE Trans. Power Del. 18 1 2003 164 169
2. T.K. Saha Review of modern diagnostic techniques for assessing insulation condition in aged transformers IEEE Trans. Dielectrics Electric. Insulat. 10 5 2003 903 917
3. R.R. Rogers IEEE and IEC codes to interpret faults in transformers using gas in oil analysis IEEE Trans Electron. Insulat. 13 5 1978 349 354
4. C.E. Lin, J.M. Ling, and C.L. Huang An expert system for transformer fault diagnosis using dissolved gas analysis IEEE Trans. Power Del. 8 1 1993 231 238
5. P. Purkait, S. Chakravorti, An expert system for fault diagnosis in transformers during impulse tests, Power Engineering Society Winter Meeting, vol.3, 23-27 January 2000, pp. 2181-2186.
6. Q. Su, C. Mi, L.L. Lai, and P. Austin A fuzzy dissolved gas analysis method for the diagnosis of multiple incipient faults in a transformer IEEE Trans. Power Syst. 15 2 2000 593 598
7. S.I. Mofizul, T. Wu, and G. Ledwich A novel fuzzy logic approach to transformer fault diagnosis IEEE Trans. Dielectric. Electric. Insulat. 7 2 2000 177 186
8. Y. Zhang, X. Ding, Y. Liu, and P.J. Griffin An artificial neural network approach to transformer fault diagnosis IEEE Trans. Power Del. 11 4 1996 1836 1841
9. Y.C. Huang, H.T. Yang, and C.L. Huang Developing a new transformer fault diagnosis system through evolutionary fuzzy logic IEEE Trans. Power Del. 12 2 1997 761 767
10. T.Y. Hong, and C.L. Chiung Adaptive fuzzy diagnosis system for dissolved gas analysis of power transformers IEEE Trans. Power Del. 14 4 1999 1342 1350
11. M.H. Wang Extension neural network for power transformer incipient fault diagnosis, IEE Proceedings-Generation Trans. Distrib. 150 6 2003 679 685
12. C.H. Yann A new data mining approach to dissolved gas analysis of oil-insulated power apparatus IEEE Trans. Power Del. 18 4 2003 1257 1261
13. J.J. Dukarm, Transformer oil diagnosis using fuzzy logic and neural networks, Canadian Conference on Electrical and Computer Engineering 1993, vol. 1, 14-17 September 1993, pp. 329-332.
14. Z.Y. Wang, Y.L. Liu, and P.J. Griffin A combined ANN and expert system tool for transformer fault diagnosis IEEE Trans. Power Del. 13 4 1998 1224 1229
15. K.F. Thang, R.K. Aggarwal, A.J. McGrail, and D.G. Esp Analysis of power transformer dissolved gas data using the self-organizing map IEEE Trans. Power Del. 18 4 2003 1241 1248
16. C.H. Yann Evolving neural nets for fault diagnosis of power transformers IEEE Trans. Power Del. 18 3 2003 843 848
17. M.H. Wang A novel extension method for transformer fault diagnosis IEEE Trans. Power Del. 18 1 2003 164 169
18. C. Cortes, and V. Vapnik Support-vector Networks Mach Learning 20 3 1995 273 295
19. J.W. Lu, K.N. Plataniotis, A.N. Venetsanopoulos, Face recognition using feature optimization and ν-support vector learning Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal, Processing Society Workshop, 10-12 September 2001, pp. 373-382.
20. F.E.H. Tay, L.J. Cao, Application of support vector machines in financial time series forecasting, Omega, August, 29 (4) (2001) 309-317.
21. W.W. Yan, H.H. Shao, Application of support vector machine nonlinear classifier to fault diagnoses, Proceedings of the Fourth World Congress Intelligent Control and Automation, 10-14 June 2002. Shanghai, China, pp. 2697-2670.
22. L.B. Jack, and A.K. Nandi Fault detection using support vector machines and artificial neural networks: augmented by genetic algorithms Mech. Syst. Signal Process. 16 2-3 2002 373 390
23. W.C. Chan, C.W. Chan, K.C. Cheung, and C.J. Harris On the modeling of nonlinear dynamic systems using support vector neural networks Eng. Appl. Artif. Intell. 14 2001 105 113
24. V.N. Vapnik The nature of Statistical Learning Theory 1995 Springer-Verlag New York