Power transformer fault diagnosis based on dissolved gas analysis by artificial neural network

2012 1st International Conference on Renewable Energies and Vehicular Technology, REVET 2012

Volumn , Issue , 2012, Pages 230-236

  Seifeddine, Souahlia ^a   Khmais, Bacha ^a   Abdelkader, Chaari ^a  

^a C3S ^*  (Tunisia)

Author keywords

Dissolved gas analysis; Multi Layer Perceptron; Radial Basis Function; transformer fault diagnosis

Indexed keywords

DISSOLVED GAS ANALYSIS; EXPERIMENTAL DATA; FAULT CLASSIFICATION; FAULT TYPES; HIGH DIMENSIONS; MULTI LAYER PERCEPTRON; NORMAL STATE; POWER TRANSFORMER FAULT DIAGNOSIS; RADIAL BASIS FUNCTIONS; RBF CLASSIFIERS; SMALL SAMPLING; TRAINING SAMPLE; TRANSFORMER FAULT DIAGNOSIS; TRANSFORMER FAULTS;

FAULT DETECTION; GAS CHROMATOGRAPHY; LEAD ACID BATTERIES; NEURAL NETWORKS; POWER QUALITY; RADIAL BASIS FUNCTION NETWORKS;

POWER TRANSFORMERS;

EID: 84862093111     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/REVET.2012.6195276     Document Type: Conference Paper

References (8)

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7. Standard IEC 60599, "Guide for the interpretation of dissolved gas analysis and gas-free", 2007.
8. Z. Moravej, D.N. Vishwakarma, S.P. Singh, "Application of radial basis function neural network for differential relaying of a power transformer", Computers and Electrical Engineering 29, pp. 421-434, 2003.