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Detection and classification of faults on 220 KV transmission line using wavelet transform and neural network

Author(s): R. P. Hasabe*, A. P. Vaidya
Electrical Engineering Department, Walchand College of Engineering Sangli, Maharasht,. India
International Journal of Smart Grid and Clean Energy, vol. 3, no. 3, July 2014: pp. 283-290
ISSN: 2315-4462 (Print)
ISSN: 2373-3594 (Online)
Digital Object Identifier: 10.12720/sgce.3.3.283-290

Abstract: This paper presents a discrete wavelet transform and neural network approach to fault detection and classification in transmission lines. The detection and classification is carried out by using energy of the detail coefficients of the phase signals, used as input to neural network to classify the faults on transmission lines. Neural network perform well when faced with different fault conditions and system parameters.
Keywords: Fault detection, fault classification, wavelet transform, neural networks

Full Paper.pdf

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