Power transformer fault classification based on dissolved gas analysis by implementing bootstrap and genetic programming

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 39, Issue 1, 2009, Pages 69-79

  Shintemirov, A ^a   Tang, W ^a   Wu, Q H ^a  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

Author keywords

Bootstrap; Dissolved gas analysis (DGA); Fault classification; Feature extraction; Genetic programming; K nearest neighbor (KNN); Neural networks; Power transformer; Support vector machine (SVM)

Indexed keywords

BACKPROPAGATION; CLASSIFIERS; COMPUTER PROGRAMMING; DISSOLUTION; ELECTRIC INSTRUMENT TRANSFORMERS; ELECTRIC TRANSFORMER TESTING; FEATURE EXTRACTION; GAS CHROMATOGRAPHY; GASES; GENETIC PROGRAMMING; IMAGE RETRIEVAL; LEARNING SYSTEMS; NEURAL NETWORKS; PROGRAM INTERPRETERS; PROGRAMMING THEORY; SUPPORT VECTOR MACHINES; TRANSFORMER SUBSTATIONS;

BOOTSTRAP; DISSOLVED GAS ANALYSIS (DGA); FAULT CLASSIFICATION; K-NEAREST NEIGHBOR (KNN); POWER TRANSFORMER; SUPPORT VECTOR MACHINE (SVM);

POWER TRANSFORMERS;

EID: 58649122867     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCC.2008.2007253     Document Type: Article

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