A neural network approach to power transformer fault diagnosis

Diagnosis of power transformer abnormality is important for power system reliability. This paper introduces the dissolved gas-in-oil analysis (DGA) according to the characteristic of transformer fault diagnosis, based on fuzzy set theory and adaptive genetic algorithm, a neural network model for tra...

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Main Authors: Fu Yang, Jin Xi, Lan Zhida
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Dissolved gas analysis
Fault diagnosis
Fuzzy set theory
Genetic algorithms
Neural networks
Power system modeling
Power system reliability
Power transformers
Testing
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creator Fu Yang
Jin Xi
Lan Zhida
description Diagnosis of power transformer abnormality is important for power system reliability. This paper introduces the dissolved gas-in-oil analysis (DGA) according to the characteristic of transformer fault diagnosis, based on fuzzy set theory and adaptive genetic algorithm, a neural network model for transformer fault diagnosis is built by using modular back-propagation (BP). The results of training and testing show that the method is effective and available.
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This paper introduces the dissolved gas-in-oil analysis (DGA) according to the characteristic of transformer fault diagnosis, based on fuzzy set theory and adaptive genetic algorithm, a neural network model for transformer fault diagnosis is built by using modular back-propagation (BP). The results of training and testing show that the method is effective and available.</description><identifier>ISBN: 750626210X</identifier><identifier>ISBN: 9787506262101</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Dissolved gas analysis ; Fault diagnosis ; Fuzzy set theory ; Genetic algorithms ; Neural networks ; Power system modeling ; Power system reliability ; Power transformers ; Testing</subject><ispartof>Sixth International Conference on Electrical Machines and Systems, 2003. 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The results of training and testing show that the method is effective and available.</description><subject>Algorithm design and analysis</subject><subject>Dissolved gas analysis</subject><subject>Fault diagnosis</subject><subject>Fuzzy set theory</subject><subject>Genetic algorithms</subject><subject>Neural networks</subject><subject>Power system modeling</subject><subject>Power system reliability</subject><subject>Power transformers</subject><subject>Testing</subject><isbn>750626210X</isbn><isbn>9787506262101</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjM1qAyEURoVSSJvmCbrxBQYc9eq4KYTQPwhkk0B34cbR1GQyDmoIffsK7bc5Z3H47sijBqa44i37mpFFzidWJ4wU0D2QlyUd3TXhUFFuMZ0pTlOKaL9piXSKN5doSThmH9OlusfrUGgf8DjGHPITufc4ZLf455zs3l63q49mvXn_XC3XTWg1lAa4MQ7Qo-qNUko6NAztwYKxKGTrpOygrwLcGqWtYsKiFjVX4A8AKObk-e83OOf2UwoXTD_7lmvRdSB-AYUCQh4</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Fu Yang</creator><creator>Jin Xi</creator><creator>Lan Zhida</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>A neural network approach to power transformer fault diagnosis</title><author>Fu Yang ; Jin Xi ; Lan Zhida</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-5299e5afa6d96664ea90acbc59ca341e4485d34152c967c603ca73fa665fb55a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Algorithm design and analysis</topic><topic>Dissolved gas analysis</topic><topic>Fault diagnosis</topic><topic>Fuzzy set theory</topic><topic>Genetic algorithms</topic><topic>Neural networks</topic><topic>Power system modeling</topic><topic>Power system reliability</topic><topic>Power transformers</topic><topic>Testing</topic><toplevel>online_resources</toplevel><creatorcontrib>Fu Yang</creatorcontrib><creatorcontrib>Jin Xi</creatorcontrib><creatorcontrib>Lan Zhida</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Fu Yang</au><au>Jin Xi</au><au>Lan Zhida</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A neural network approach to power transformer fault diagnosis</atitle><btitle>Sixth International Conference on Electrical Machines and Systems, 2003. 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ispartof Sixth International Conference on Electrical Machines and Systems, 2003. ICEMS 2003, 2003, Vol.1, p.351-354 vol.1
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subjects Algorithm design and analysis
Dissolved gas analysis
Fault diagnosis
Fuzzy set theory
Genetic algorithms
Neural networks
Power system modeling
Power system reliability
Power transformers
Testing
title A neural network approach to power transformer fault diagnosis
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