Title :
Application of wavelet transform and MLP neural network for Ferroresonance identification
Author :
Mokryani, G. ; Haghifam, M.-R.
Author_Institution :
Islamic Azad Univ., Ilkhchi
Abstract :
In this paper an efficient method for detection of ferroresonance in distribution transformer based on wavelet transform is presented. Using this method ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Multi Layer Perceptron (MLP) neural network used for classification. Ferroresonance data and other transients are obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying ferroresonance from other transients.
Keywords :
ferroresonant circuits; multilayer perceptrons; neural nets; power engineering computing; power transformers; wavelet transforms; EMTP program; MLP neural network; capacitor switching; distribution transformer; ferroresonance identification; load switching; multilayer perceptron neural network; transformer switching; wavelet transform; Capacitance; Capacitors; Ferroresonance; Frequency; Hidden Markov models; Inductance; Multiresolution analysis; Neural networks; Voltage control; Wavelet transforms; EMTP program; Ferroresonance; MLP neural network; Wavelet transform;
Conference_Titel :
Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4244-1905-0
Electronic_ISBN :
1932-5517
DOI :
10.1109/PES.2008.4596061