%0 Journal Article
	%A Abhishek Bansal and  G. N. Pillai
	%D 2007
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 4, 2007
	%T High Impedance Fault Detection using LVQ Neural Networks 
	%U https://publications.waset.org/pdf/11210
	%V 4
	%X This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response. 
	%P 701 - 705