Artificial neural networks and genetic algorithm for transformer winding/insulation faults

This paper presents an application of Artificial Neural Network and Genetic Algorithm for transformer winding/insulation faults diagnosed using Dissolved Gas in Oil Analysis. A back propagation training method is applied in neural network to detect the faults without cellulose involvement. Genetic A...

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Main Authors: K.S.R., Rao, K.N., Nashruladin
Format: Conference or Workshop Item
Language:English
Published: 2008
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/479/
http://scholars.utp.edu.my/id/eprint/479/1/paper.pdf
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author K.S.R., Rao
K.N., Nashruladin
author_facet K.S.R., Rao
K.N., Nashruladin
author_sort K.S.R., Rao
building UTP Institutional Repository
collection Online Access
description This paper presents an application of Artificial Neural Network and Genetic Algorithm for transformer winding/insulation faults diagnosed using Dissolved Gas in Oil Analysis. A back propagation training method is applied in neural network to detect the faults without cellulose involvement. Genetic Algorithm is used to derive the optimal key gas ratios to enhance the accuracy of fault detection. The dissolved gas in oil analysis method is known to be an early fault detection method and enables to carry out diagnosis during online operation of the transformer. Besides, the condition of the transformer could be monitored continuously by time to time. The results are compared between the real and predicted faults to observe the accuracy rate of the system.
first_indexed 2025-11-13T07:23:26Z
format Conference or Workshop Item
id oai:scholars.utp.edu.my:479
institution Universiti Teknologi Petronas
institution_category Local University
language English
last_indexed 2025-11-13T07:23:26Z
publishDate 2008
recordtype eprints
repository_type Digital Repository
spelling oai:scholars.utp.edu.my:4792017-01-19T08:26:32Z http://scholars.utp.edu.my/id/eprint/479/ Artificial neural networks and genetic algorithm for transformer winding/insulation faults K.S.R., Rao K.N., Nashruladin TK Electrical engineering. Electronics Nuclear engineering This paper presents an application of Artificial Neural Network and Genetic Algorithm for transformer winding/insulation faults diagnosed using Dissolved Gas in Oil Analysis. A back propagation training method is applied in neural network to detect the faults without cellulose involvement. Genetic Algorithm is used to derive the optimal key gas ratios to enhance the accuracy of fault detection. The dissolved gas in oil analysis method is known to be an early fault detection method and enables to carry out diagnosis during online operation of the transformer. Besides, the condition of the transformer could be monitored continuously by time to time. The results are compared between the real and predicted faults to observe the accuracy rate of the system. 2008 Conference or Workshop Item NonPeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/479/1/paper.pdf K.S.R., Rao and K.N., Nashruladin (2008) Artificial neural networks and genetic algorithm for transformer winding/insulation faults. In: 4th IASTED Asian Conference on Power and Energy Systems, AsiaPES 2008, 2 April 2008 through 4 April 2008, Langkawi. http://www.scopus.com/inward/record.url?eid=2-s2.0-62449167627&partnerID=40&md5=d2e1f283b0ba197ba105a278ea3d021d
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
K.S.R., Rao
K.N., Nashruladin
Artificial neural networks and genetic algorithm for transformer winding/insulation faults
title Artificial neural networks and genetic algorithm for transformer winding/insulation faults
title_full Artificial neural networks and genetic algorithm for transformer winding/insulation faults
title_fullStr Artificial neural networks and genetic algorithm for transformer winding/insulation faults
title_full_unstemmed Artificial neural networks and genetic algorithm for transformer winding/insulation faults
title_short Artificial neural networks and genetic algorithm for transformer winding/insulation faults
title_sort artificial neural networks and genetic algorithm for transformer winding/insulation faults
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/479/
http://scholars.utp.edu.my/id/eprint/479/
http://scholars.utp.edu.my/id/eprint/479/1/paper.pdf