Title :
Detection and classification of impulse faults in transformer using wavelet transform and artificial neural network
Author :
Vanamadevi, N. ; Arivamudhan, M. ; Santhi, S.
Author_Institution :
Dept. of Instrum. Eng., Annamalai Univ., Annamalainagar
Abstract :
This paper aims at describing a method for the detection and classification of impulse faults in a transformer winding using wavelet transform and an artificial neural network. The method is explained by considering the lumped parameter model of a winding. The WT decomposes the signal and RMS value of the detailed signal is extracted to train the ANN. The simulation results are satisfactory in detection and classification of faults.
Keywords :
fault diagnosis; neural nets; power engineering computing; power transformers; wavelet transforms; artificial neural network; impulse fault classification; impulse fault detection; lumped parameter model; transformer winding; wavelet transform; Artificial neural networks; Capacitance; Circuit faults; Electronic mail; Fault detection; Frequency domain analysis; Impulse testing; Instruments; Wavelet transforms; Windings; Impulse faults; Transformer; Wavelet transform ANN;
Conference_Titel :
Sustainable Energy Technologies, 2008. ICSET 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1887-9
Electronic_ISBN :
978-1-4244-1888-6
DOI :
10.1109/ICSET.2008.4746975
