Power transformer fault diagnosis based on dissolved gas analysis by support vector machine

Electric Power Systems Research

Volumn 83, Issue 1, 2012, Pages 73-79

  Bacha, Khmais ^a   Souahlia, Seifeddine ^a   Gossa, Moncef ^a  

^a UNIVERSITY OF TUNIS   (Tunisia)

Author keywords

Dissolved gas analysis; Support vector machine; Transformer fault diagnosis

Indexed keywords

AI TECHNIQUES; DISSOLVED GAS ANALYSIS; EXPERIMENTAL DATA; FAULT CLASSIFICATION; FAULT TYPES; FAULTS DIAGNOSIS; GRAPHICAL REPRESENTATIONS; HIGH DIMENSIONS; INPUT DATAS; INPUT VECTOR; NORMAL STATE; POWER TRANSFORMER FAULT DIAGNOSIS; RBF NEURAL NETWORK; SMALL SAMPLING; SVM CLASSIFIERS; SVM MODEL; TRAINING DATA; TRAINING SAMPLE; TRANSFORMER FAULT DIAGNOSIS; TRANSFORMER FAULTS;

DISSOLUTION; ELECTRIC TRANSFORMER TESTING; FAULT DETECTION; FUZZY LOGIC; GAS CHROMATOGRAPHY; GASES; GRAPHIC METHODS; INPUT OUTPUT PROGRAMS; NEURAL NETWORKS; POWER QUALITY; SUPPORT VECTOR MACHINES; VECTORS;

POWER TRANSFORMERS;

EID: 80054682258     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.epsr.2011.09.012     Document Type: Article

References (17)

1. S.-w. Fei, and X.-b. Zhang Fault diagnosis of power transformer based on support vector machine with genetic algorithm Expert Systems with Applications 36 2009 11352 11357
2. A. Akbari, A. Setayeshmehr, H. Borsi, E. Gockenbach, and I. Fofana Intelligent agent-based system using dissolved gas analysis to detect incipient faults in power transformers IEEE Electrical Insulation Magazine 26 6 2010 27 40
3. A. Shintemirov, W. Tang, and Q.H. Wu 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 39 January (1) 2009 69 79
4. Y.-j. Sun, S. Zhang, C.-x. Miao, and J.-m. Li Improved BP neural network for transformer fault diagnosis Journal of China University of Mining & Technology 17 March (1) 2007 138 142
5. W.H. Tang, J.Y. Goulermas, Q.H. Wu, Z.J. Richardson, and J. Fitch A probabilistic classifier for transformer dissolved gas analysis with a particle swarm optimizer IEEE Transactions on Power Delivery 23 April (2) 2008 751 759 (Pubitemid 351546126)
6. C.-P. Hung, and M.-H. Wang Diagnosis of incipient faults in power transformers using CMAC neural network approach Electric Power Systems Research 71 2004 235 244
7. Michel Duval A review of faults detectable by gas-in-oil analysis in transformers IEEE Electrical Insulation Magazine 18 June (3) 2002 8 17 (Pubitemid 34808246)
8. Rahmatollah Hooshmand, and Mahdi Banejad Application of fuzzy logic in fault diagnosis in transformers using dissolved gas based on different standards World Academy of Science, Engineering and Technology 17 2006 157 161
9. V. Miranda, and A. Rosa Garcez Castro Improving the IEC table for transformer failure diagnosis with knowledge extraction from neural networks IEEE Transactions on Power Delivery 20 October (4) 2005 2509 2516 (Pubitemid 41638226)
10. S.-w. Fei, C.-l. Liu, and Y.-b. Miao Support vector machine with genetic algorithm for forecasting of key-gas ratios in oil-immersed transformer Expert Systems with Applications 36 2009 6326 6331
11. Standard IEC 60599, Guide for the interpretation of dissolved gas analysis and gas-free, 2007.
12. R.N. Afiqah, I. Musirin, D. Johari, M.M. Othman, T.K.A. Rahman, and Z. Othman Fuzzy logic application in DGA methods to classify fault type in power transformer Selected Topics in Power Systems and Remote Sensing, Malaysia 2008
13. Wilfredo C. Flores, Enrique E. Mombello, José. A. Jardini, Giuseppe Rattá, and Antonio M. Corvo Expert system for the assessment of power transformer insulation condition based on type-2 fuzzy logic systems Expert Systems with Applications 38 2011 8119 8127
14. R. Ziani, A. Felkaoui, and R. Zegadi Performances de la classification par les Séparateurs Vaste Marge (SVM): application au diagnostic vibratoire automatisé 4th International Conference on Computer Integrated Manufacturing CIP'2007 03-04 November 2007
15. L.V. Ganyun, H. Cheng, H. Zhai, and L. Dong Fault diagnosis of power transformer based on multi-layer SVM classifier Electric Power Systems Research 74 2005 1 7 (Pubitemid 40245117)
16. V.N. Vapnik The Nature of Statistical Learning Theory 1995 Springer-Verlag New York
17. W.-M. Lin, C.-H. Lin, and M.-X. Tasy Transformer-fault diagnosis by integrating field data and standard codes with training enhancible adaptive probabilistic network IEE Proceedings - Generation Transmission and Distribution 152 3 2005 335 341 (Pubitemid 40751383)