ABSTRACT Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to ensure an uninterrupted power supply. Due to information transmission mistakes as well as arisen errors while processing data in surveying and monitoring state information of transformer, uncertain and incomplete information may be produced. Based on these points, this paper presents an intelligent fault diagnosis method of power transformer using fuzzy fault tree analysis (FTA) and beta distribution for failure possibility estimation. By using the technique we proposed herein, the continuous attribute values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. Further, it explains a new approach based on Euclidean distance between fuzzy numbers, to rank the basic events in accordance with their Fuzzy Importance Index.
Cite this paper
nullS. Tyagi, D. Pandey and V. Kumar, "Fuzzy Fault Tree Analysis for Fault Diagnosis of Cannula Fault in Power Transformer," Applied Mathematics, Vol. 2 No. 11, 2011, pp. 1346-1355. doi: 10.4236/am.2011.211188.
 L. A. Zadeh, “Fuzzy Sets,” Information and Control, Vol. 8, No. 3, 1965, pp. 338-353.
 H. Tanaka, L. T. Fan, F. S. Lai and K. Toguchi, “Fault-Tree Analysis by Fuzzy Probability,” IEEE Transactions on Reliability, Vol. 32, No. 5, 1983, pp. 453-457.
 D. Singer, “A Fuzzy Set Approach to Fault Tree Analysis,” Fuzzy Sets and Systems, Vol. 34, No. 2, 1990, pp. 145-155. doi:10.1016/0165-0114(90)90154-X
 S. Chen, “Fuzzy System Reliability Analysis Using Fuzzy Number Arithmetic Operations,” Fuzzy Sets and Systems, Vol. 64, No. 1, 1994, pp. 31-38.
 Z.-X. Yang, K. Suzuki, Y. Shimada and H. Sayama, “Fuzzy Fault Diagnostic System Based on Fault Tree Analysis,” Proceedings of the International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, Yakohama, 20-24 March 1995, Vol. 1, pp. 165-170. doi:10.1109/FUZZY.1995.409676
 D. Pandey and S. K. Tyagi, “Profust Reliability of a Gracefully Degradable System,” Fuzzy Sets and Systems, Vol. 158, No. 7, 2007, pp. 794-803.
 D. Pandey, S. K. Tyagi and V. Kumar, “Failure Mode Screening Using Fuzzy Set Theory,” International Mathematical Forum, Vol. 4, No. 16, 2009, pp. 779-794
 Y.-S. Fu, F.-Z. Liu, W.-Z. Zhang, Q.-I. Zhang and G.-X. Zhang, “The Fault Diagnosis of Power Transformer Based on Rough Set Theory,” Proceedings of the China International Conference on Electricity Distribution, Guangzhou, 10-13 December 2008, pp. 1-5.
 Y. L. Chen and T. J. Zhang, “Research on Application of Fuzzy Fault Tree Analysis Method in the Machinery Equipment Fault Diagnosis,” Proceedings of 2nd International Conference on Informatics in Control, Automation and Robotics, Wuhan, 6-7 March 2010, pp. 84-87.
 T. Wu, G. Y. Tu, Z. Q. Bo and A. Klimek “Fuzzy Set Theory and Fault Tree Analysis Based Method Suitable for Fault Diagnosis of Power Transformer,” Proceedings of the 14th International Conference on the Intelligent System Applications to Power Systems, Kaohsiung, 5-8 November 2007, pp. 487-491.
 S. K. Tyagi, D. Pandey and R. Tyagi, “Fuzzy Set Theoretic Approach to Fault Tree Analysis,” International Journal of Engineering, Science and Technology, Vol. 2, No. 5, 2010, pp. 276-283.
 S. D. Moitra, “Skewness and the Beta Distribution,” Journal of Operational Research Society, Vol. 41, No. 10, 1990, pp. 953-961.
 H. Furuta and N. Shiraishi, “Fuzzy Importance in Fault Tree Analysis,” Fuzzy Sets and Systems, Vol. 12, No. 3, 1984, pp. 205-213. doi:10.1016/0165-0114(84)90068-X
 P. V. Suresh, A. K. Babar and V. V. Raj, “Uncertainty in Fault Tree Analysis: A Fuzzy Approach,” Fuzzy Sets and Systems, Vol. 83, No. 2, 1996, pp. 135-141.
 L. A. Zadeh “Fuzzy Sets as the Basis for a Theory of Possibility,” Fuzzy Sets and Systems, Vol. 1, No. 1, 1978, pp. 3-28. doi:10.1016/0165-0114(78)90029-5
 G. J. Klir and B. Yuan, “Fuzzy Sets and Fuzzy Logic: Theory and Applications,” Prentice-Hall, Upper Saddle River, 1995.