FAULT IDENTIFICATION USING NEURAL NETWORKS

Rangisetti, Praveen

dc.contributor.author	Rangisetti, Praveen
dc.date.accessioned	2014-12-05T06:09:14Z
dc.date.available	2014-12-05T06:09:14Z
dc.date.issued	2007
dc.identifier	M.Tech	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/13142
dc.guide	Pillai, G. N.
dc.description.abstract	In this thesis the aim is to detect the high impedance fault occurring on radial electrical distribution systems using neural network based relaying scheme. A multilayer perceptron is used for distinguishing the linear and nonlinear High Impedance Faults by taking the Feature vector as input. R.M.S values of third and fifth harmonic components of feeder voltage and feeder current are used as the feature vector obtained by applying the Fast Fourier Transform on the Feeder voltage and Feeder current	en_US
dc.language.iso	en	en_US
dc.subject	ELECTRICAL ENGINEERINGe	en_US
dc.subject	ELECTRICAL ENGINEERING	en_US
dc.subject	ELECTRICAL ENGINEERING	en_US
dc.subject	ELECTRICAL ENGINEERING	en_US
dc.title	FAULT IDENTIFICATION USING NEURAL NETWORKS	en_US
dc.type	M.Tech Dessertation	en_US
dc.accession.number	G13071	en_US