Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32759
Pattern Recognition of Partial Discharge by Using Simplified Fuzzy ARTMAP

Authors: S. Boonpoke, B. Marungsri

Abstract:

This paper presents the effectiveness of artificial intelligent technique to apply for pattern recognition and classification of Partial Discharge (PD). Characteristics of PD signal for pattern recognition and classification are computed from the relation of the voltage phase angle, the discharge magnitude and the repeated existing of partial discharges by using statistical and fractal methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern recognition and classification as artificial intelligent technique. PDs quantities, 13 parameters from statistical method and fractal method results, are inputted to Simplified Fuzzy ARTMAP to train system for pattern recognition and classification. The results confirm the effectiveness of purpose technique.

Keywords: Partial discharges, PD Pattern recognition, PDClassification, Artificial intelligent, Simplified Fuzzy ARTMAP

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1083777

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3008

References:


[1] F.H. Kreuger, "Partial Discharge Detection in High - Voltage Equipment", Butterworth & Co. (Publishers) Ltd, 1989.
[2] E. Kuffel, W.S. Zaengl and J. Kuffel, "High Voltage Engineering: Fundamentals". 2nd, Butterworth - Heinemann, 2000.
[3] B. Marungsri, N. Meeboom and A. Oonsivilai, "Dynamic Model Identification of Induction Motors using Intelligent Search Techniques with taking Core Loss into Account", WSEAS TRANSACTIONS on POWER SYSTEMS, Vol. 1, No. 8, August 2006, pp. 1438 - 1445.
[4] A. Oonsivilai and B. Marungsri, "Optimal PID Tuning for AGC system using Adaptive Tabu Search", Proceedings of the 7th WSEAS International Conference on POWER SYSTEMS, Beijing, China, September 2007, pp. 42-47.
[5] A. Oonsivilai and B. Marungsri, "Stability Enhancement for Multimachine Power System by Optimal PID Tuning of Power System Stabilizer using Particle Swarm Optimization", WSEAS TRANSACTIONS on POWER SYSTEMS, Issue 5, Volume 3, May 2008, pp. 465 - 474.
[6] A. Oonsivilai and B. Marungsri, "Optimal PID Tuning for Power System Stabilizers Using Adaptive Particle Swarm Optimization Technique", INTERNATIONAL CONFERENCE ON POWER CONTROL AND OPTIMIZATION: Innovation in Power Control for Optimal Industry. AIP Conference Proceedings, Volume 1052, July 2008, pp. 116-123
[7] B. Marungsri and A. Oonsivilai, "Partial Discharges Localization in Oil Insulating Transformer using Adaptive Tabu Search", Proceedings of the 12th WSEAS International Conference on CIRCUITS, Heraklion, Greece, July 22-24, 2008, pp. 290 - 295.
[8] B. Marungsri and A. Oonsivilai , "Fuzzy ARTMAP Technique for Speech Noise Reduction," WSEAS International Conference on Signal, Speech and Image Processing, Beijing, China, pp 20-25, September 2007.
[9] E. Gulski, Computer - Aided Recognition of Partial Discharges using Statistical Tools. Delft University Press,1991.
[10] N.A. Muhamad, B.T. Phung and T.R. Blackburn, "Dissolved Gas Analysis (DGA) of Partial Discharge Fault in Bio-degradable Transformer Insulation Oil", Universities Power Engineering Conference 2007.AUPEC 2007, December 2007, pp 1-6.
[11] X. Wang, B. Li, H. T. Roman, O. L. Russo, K. Chin and K. R. Farmer, "Acousto- optical PD Detection for Transformers", IEEE Transactions on Power Delivery, Vol. 21, No. 3, July 2006, pp. 1068-1073.
[12] A. Oonsivilai and B. Marungsri, "Application of Artificial Intelligent Technique for Partial Discharges in Oil Insulating Transformer", WSEAS TRANSACTIONS on SYSTEMS, Vol.7 No.10, October 2008, pp.920-929.
[13] Y. Lu, X. Tan and X. Hu, "PD detection and localization by acoustic measurements in an oil-filled transformer", IEEE Science Measurement and Technology, Vol.147, No.2, March 2000, pp. 81-85.
[14] K. Vicetjindavat, "Pattern Recognition of Partial discharge in High Voltage Equipment", Master Degree Thesis, Chulalongkorn University, 2001.
[15] A. Wichmann, P. Gr├╝newald, and J. Weidner, "Early fault detection inelectrical machines by on-line RF monitoring," Cigré Symp., Vienna,Austria, 1987, pp. 05-87.
[16] J. T. Phillipson, "Experience with RF techniques in the petrochemical industry," Proc. 4th Int. Conf. Generator and Motor Partial Discharge Testing, Houston, TX, 1996.
[17] M. D. Judd, L. Yang, and I. B. B. Hunter, "Partial discharge monitoring for power transformers using UHF sensors. Part 1: Sensors and signal interpretation," IEEE Electr. Insul. Mag., Vol. 21, No. 1, Mar./Apr. 2005, pp. 5-14.
[18] S. Grossberg, "Adaptive pattern classification and universal recoding, II: feedback, expectation,olfaction and illusions", Biological Cybernetics, Vol. 23, 1976, pp. 187-202.
[19] G. A. Carpenter and S. Grossberg, "ART2: Self-organization of stable category recognition codes for analog input patterns", Applied Optics, vol. 26, No. 23, 1987, pp. 4919- 4930.
[20] G. A. Carpenter and S. Grossberg, "ART3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architecture, Neural Networks, Vol.3, 1990, pp. 129-152.
[21] G. A. Carpenter, G. S. Grossberg and J. H.Reynolds, "ARTMAP: Supervised real-time learning and classification of mon-stationary data by a self-organizing neural network", Neural Networks, Vol. 4, 1991, pp. 565-588.
[22] G. A. Carpenter, G. S. Grossberg and D. B. Rosen, "Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system", Neural Networks, Vol. 4, 1991, pp. 759-771.
[23] G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, and D. B. Rosen, "Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps", IEEE Trans. on Neural Networks, Vol.3, No. 5, 1992, pp. 698-713.
[24] T. Kasuba, "Simplified Fuzzy ARTMAP", AI Expert, Vol. 8, No. 11, 1993, pp.18-25.
[25] M. Vakil-Gahimisheh and N. Pave┼íić, "A Fast Simplified Fuzzy ARTMAP Network", Neural Processing Letters, Vol. 17, 2003, pp. 273-316.