An Approach for Construction of Fault Trees Using Rough Set and Fuzzy Clustering Algorithm

Abstract:

This paper presents a novel methodology for the construction of fault tree using rough set and clustering algorithm. Taking advantage of the strong ability of RS theory in processing large data and eliminating redundant information, this method can remove irrelevant factors from the original fault data and reduce the dimension of processing data which helps to overcome fuzzy clustering algorithm's defect when process large database. The method is introduced and explained in details and its correctness and completeness is validated by Fault tree construction of oil-immersed traction transformers.

• Periodical: Applied Mechanics and Materials (Volumes 34-35)
• Pages: 186-191
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.34-35.186
• Online since: October 2010
• Authors: Ju Liang Tu, Rong Xing Duan, De Cun Dong
• Keywords: Fault Tree, Fuzzy Clustering Algorithm, Rough Set (RS), Traction Transformer

References

[1] G. Latif-Shabgahi,F. Tajarrod. A New Approach for the Construction of Fault Trees from System Simulink,. 2009 International Conference on Availability, Reliability and Security，vol. 48, No. 4, pp.712-716, (2009).

DOI: 10.1109/ares.2009.172

[2] J. B. Fussel, A Formal Methodology for Fault Tree Construction, Nuclear Science and Engineering, vol. 52, pp.421-432, (1973).

[3] J. R. Taylor, An Algorithm for Fault Tree Construction, IEEE Transactions on Reliability, R-31, pp.137-146, (1982).

[4] S. A. Lapp, G. J. Powers, Computer-Aided Synthesis of Fault-Trees, IEEE Trans. on Reliability, R-26, pp.2-13, (1977).

DOI: 10.1109/tr.1977.5215060

[5] Z. Pawlak, J. Grzymala-Busse, and R. Slowinski, et al, Rough sets, Communication of the ACM, vol. 38, no. 11, pp.89-95, (1995).

DOI: 10.1145/219717.219791

[6] Gao Xinbo and Xie Weixin, Research development of fuzzy clustering theory and applications, Chinese Science Bulletin(in Chinese), 21(44), 2241～2251(1999).

[7] Jun Zhang, Bing Yang, Xiaomao Liu, etc. Some properties of the fuzzy equivalence matrices, Proceedings of SPIE - The International Society for Optical Engineering, vol. 6788, (2007).

[8] A. Skowron, C. Rauszer, The discernibility matrices and functions in information system, Slowinski R. Intelligent Decision Support -Handbook of Applications and Advances of the Rough Sets Theory, Dordrecht: Kluwer Academic Publishers, 1992, pp.331-362.

DOI: 10.1007/978-94-015-7975-9_21

[9] Jianfeng Li, Yan Chen. Application of Fuzzy Clustering Method in Classifying Steel Companies., Second International Conference on Innovative Computing, Information and Control, ICICIC , (2007).

DOI: 10.1109/icicic.2007.175

[10] Liu Xun , Zhao Shimin , Dong Decun. Global Fault Diagnosis Method of Traction Transformer Based on Fuzzy Neural Network., China Railway Science, vol. 30, no. 1, pp.103-107, (2009).

[11] Huang Wentao, Wang Weijie, Meng Qingxin. Fault diagnosis method for power transformers based on rough set theory,. Chinese Control and Decision Conference, pp.468-472, (2000).

DOI: 10.1109/ccdc.2008.4597354