Abstract
Partial discharge (PD) pattern recognition is an important tool in HV insulation diagnosis. A PD pattern recognition approach of HV power transformers based on a neural network is proposed in this paper. A commercial PD detector is firstly used to measure the 3-D PD patterns of epoxy resin power transformers. Then, two fractal features (fractal dimension and lacunarity) extracted from the raw 3-D PD patterns are presented for the neural- network-based (NN-based) recognition system. The system can quickly and stably learn to categorize input patterns and permit adaptive processes to access significant new information. To demonstrate the effectiveness of the proposed method, the recognition ability is investigated on 150 sets of field tested PD patterns of epoxy resin power transformers. Different types of PD within power transformers are identified with rather encouraged results.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Feinberg, R.: Modern Power Transformer Practice. John Wiley & Sons, New York (1979)
Krivda, A.: Automated Recognition of Partial Discharge. IEEE Trans. on Dielectrics and Electrical Insulation 2, 796–821 (1995)
Satish, L., Gururaj, B.I.: Application of Expert System to Partial Discharge Pattern Recognition. In: CIGRE Study Committee 33 Colloquium, Leningrad, Russia, Paper GIGRE SC 33.91 (1991)
Tomsovic, K., Tapper, M., Ingvarsson, T.T.: A Fuzzy Information Approach to Integrating Different Transformer Diagnostic Methods. IEEE Trans. on Power Delivery 8, 1638–1643 (1993)
Cho, K.B., Oh, J.Y.: An Overview of Application of Artificial Neural Network to Partial Discharge Pattern Classification. In: Proc. of the 5th International Conference on Properties and Applications of Dielectric Materials, vol. 1, pp. 326–330 (1997)
Zhang, H., Lee, W.J., Kwan, C., Ren, Z., Chen, H., Sheeley, J.: Artificial Neural Network Based On-Line Partial Discharge Monitoring System for Motors. In: IEEE Conference of Industrial and Commercial Power Systems Technical, pp. 125–132 (2005)
Salama, M.M.A., Bartnikas, R.: Determination of Neural Network Topology for Partial Discharge Pulse Pattern Recognition. IEEE Trans. on Neural Networks 13, 446–456 (2002)
Satish, L., Zaengl, W.S.: Can Fractal Features Be Used for Recognizing 3-D Partial Discharge Patterns. IEEE Trans. on Dielectrics and Electrical Insulation 3, 352–359 (1995)
Voss, R.F.: Random Fractal: Characterization and Measurement. Plenum Press, New York (1985)
Mandelbrot, B.B.: The Fractal Geometry of Nature. Freeman, New York (1983)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, HC., Chen, PH., Chou, CM. (2006). 3-D Partial Discharge Patterns Recognition of Power Transformers Using Neural Networks. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_192
Download citation
DOI: https://doi.org/10.1007/11760023_192
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
Online ISBN: 978-3-540-34438-4
eBook Packages: Computer ScienceComputer Science (R0)