Genetic algorithm in location identification of AEPD source: Some aspects

Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/8140

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DC Field	Value	Language
dc.contributor.author	Punekar, G.S.
dc.contributor.author	Antony, D.
dc.contributor.author	Bhavanishanker, T.
dc.contributor.author	Nagamani, H.N.
dc.contributor.author	Kishore, N.K.
dc.date.accessioned	2020-03-30T10:18:07Z	-
dc.date.available	2020-03-30T10:18:07Z	-
dc.date.issued	2013
dc.identifier.citation	2013 IEEE 1st International Conference on Condition Assessment Techniques in Electrical Systems, IEEE CATCON 2013 - Proceedings, 2013, Vol., , pp.386-390	en_US
dc.identifier.uri	http://idr.nitk.ac.in/jspui/handle/123456789/8140	-
dc.description.abstract	Using the experimental data obtained from an Acoustic Emission Partial Discharge (AEPD) system, efforts are made to locate the source of Partial discharge (PD) with a transformer tank. The AEPD data with 8 sensors (available in the literature) is numerically experimented with a Genetic Algorithm, although minimum of 4 sensors only are necessary for identifying the location. With eight sensors, four sensors considered at a time, form 70 ( 8C4) combination of sensors. The effect, implication and usage of superfluous sensor data in identifying the location with GA is analyzed and reported. Results are compared with Newton's method. � 2013 IEEE.	en_US
dc.title	Genetic algorithm in location identification of AEPD source: Some aspects	en_US
dc.type	Book chapter	en_US
Appears in Collections:	2. Conference Papers

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