Application of Fuzzy Logic in Fault Diagnosis in Transformers using Dissolved Gas based on Different Standards
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Application of Fuzzy Logic in Fault Diagnosis in Transformers using Dissolved Gas based on Different Standards

Authors: Rahmatollah Hooshmand, Mahdi Banejad

Abstract:

One of the problems in fault diagnosis of transformer based on dissolved gas, is lack of matching the result of fault diagnosis of different standards with the real world. In this paper, the result of the different standards is analyzed using fuzzy and the result is compared with the empirical test. The comparison between the suggested method and existing methods indicate the capability of the suggested method in on-line fault diagnosis of the transformers. In addition, in some cases the existing standards are not able to diagnose the fault. In theses cases, the presented method has the potential of diagnosing the fault. The information of three transformers is used to the show the capability of the suggested method in diagnosing the fault. The results validate the capability of the presented method in fault diagnosis of the transformer.

Keywords: Fault Diagnosis of Transformer, Dissolved Gas, Fuzzy Logic.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076352

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References:


[1] M. B. Ahmad, Z. B. Yaacod, "Dissolved Gas Analysis Using Expert System", in proc. conference of research and Development. Shah Alam, Malaysia, pp. 313-316, 2002.
[2] C. E. Lin, J. M . Ling, C. L. Huang, "An Expert System for Transformer Fault Diagnosis Using Dissolved Gas Analysis", IEEE Trans. on power Delivery, Vol. 8, No . 1, pp. 231-238, January 1993.
[3] J. L. Guardado, J. L. Naredo, "A Comparative Study of Neural Network Efficiency in Power Transformers diagnosis using Dissolved Gas Analysis", IEEE Trans. on Power Delivery, Vol. 16, No. 4, pp. 643-647, October 2001.
[4] T. Yanming and Q. Zheng, "DGA Based Insulation Diagnosis of Power Transformer via ANN", Proceeding of the 6th International Conference on Properties and Applications of Dielectric Materials, China, June 21- 26 2001.
[5] W.P. Hu, X.G. Yin, Z. Zhang and D.S. Chen, "Fault Diagnosis of Transformer Insulation Based on Compensated Fuzzy Neural Network", Annual Report Conference on Electrical Insulation and Dielectric Phenomena, 0-7803-7910-1/03, pp. 273-276, 2003.
[6] I.N. Dasilva, M.M. Imamura and A.N. Desouza, "The Application of Neural Networks to the Analysis of Dissolved Gases in Insulating Oil Used in Transformers", IEEE Conference, 0-7803-6583-6/00, pp. 2643- 2648, , 2000.
[7] C. Mi, L.L. Lai, P. Austin, "A Fuzzy Dissolved Gas Analysis Method for the Diagnosis of Multiple Incipient Faults in a Transformer", IEEE trans. on power systems, Vol. 15, No. 2 , pp. 593-598, May 2000.
[8] G. Zhang, S. Ibuka and K. Yasuoka, "Application of Fuzzy Data Processing for Fault Diagnosis of Power Transformers", Proceeding of IEE Conference Publication, High Voltage Engineering Symposium, No. 467, pp. 22-27, 1999.
[9] Y. C. Huang, H. T. Yang, C. L. Huang, "Developing a New Transformer Fault Diagnosis System Through Evolutionary Fuzzy Logic", IEEE Trans. on Power Delivery, Vol. 12, No. 2, pp. 761-767, April 1997.
[10] Utility Testing Laboratory 40 west louise Avenue, P.O.BOX 65621, Salt Lake City, VT. 84165-0621.
[11] J. Yang and et. all, "Belief Network Classifier for Evaluation of DGA Data of Transformers", conference Record of the 2004 IEEE, International Symposium of Electrical Insulation, Indianapolis In USA, pp. 78-80, September 2004.
[12] L. Zadeh, "Fuzzy Sets, Information and Control", New York: Academic Press, Vol. 8, pp. 338-353, 1965.