Grey clustering analysis for incipient fault diagnosis in oil-immersed transformers

Expert Systems with Applications

Volumn 36, Issue 2 PART 1, 2009, Pages 1371-1379

  Lin, Chia Hung ^a   Wu, Chien Hsien ^b   Huang, Ping Zan ^a  

^a KAO YUAN UNIVERSITY   (Taiwan)

^b YUNG TA INSTITUTE OF TECHNOLOGY AND COMMERCE   (Taiwan)

Author keywords

Artificial intelligent (AI); Dissolved gas analysis (DGA); Grey clustering analysis (GCA); Oil immersed transformer

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECOMPOSITION; ELECTRIC FAULT CURRENTS; FAILURE ANALYSIS; MOLECULES; OIL FILLED TRANSFORMERS; POWER TRANSFORMERS; THERMAL INSULATION;

ARTIFICIAL INTELLIGENT; DIAGNOSTIC TECHNIQUES; DISSOLVED GAS ANALYSES (DGA); GREY CLUSTERING ANALYSIS; HYDROCARBON MOLECULES; INCIPIENT FAULT DIAGNOSIS; OIL IMMERSED TRANSFORMERS; TRANSFORMER FAULT DIAGNOSIS;

FAULT DETECTION;

ARTIFICIAL INTELLIGENCE; CELLULOSE DERIVATIVES; DECAY; DISSOLVING; HYDROCARBONS; ORGANIC COMPOUNDS; PYROLYSIS; THERMAL INSULATION; TRANSFORMERS;

EID: 56349108734     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.11.019     Document Type: Article

References (14)

1. Chang W.-Y., Lin H.-D., Chen Y.-W., Tuan C.-H., Wu K.-C., and Lai J.-H. Expert system for transformer faults diagnosis. Monthly Journal of Taipower's Engineering 551 (1994) 71-86
2. Cheng, C.-C. (2000). Diagnosing an abnormal transformer conditions by using dissolved gas analysis. Master thesis. Department of Electrical Engineering, National Sun Yat-Sen University.
3. Deng J.-L. Introduction to grey system theory. Journal of Grey System 1 1 (1989) 1-24
4. Huang Y.-C. A new data mining approach to dissolved gas analysis of oil-insulated power appatatus. IEEE Transactions on Power Delivery 18 4 (2003) 126-1257
5. Huang Y.-C., Yang H.-T., and Huang C.-L. Developing a new transformer fault diagnosis system through evolutionary fuzzy logic. IEEE Transactions on Power Delivery 12 2 (1997) 761-767
6. IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformer (1992). ANSI/IEEE Stand. C57. 104-1991.
7. Islam S.M., Wu T., and Ledwich G. A novel fuzzy logic approach to transformer fault diagnosis. IEEE Transactions on Dielectrics and Electrical Insulation 7 2 (2000) 177-186
8. Lin, C.-H., Huang, P.-Z., Wu, C.-H., & He, C.-Z (2006). Window based assistant tool for oil-immersed transformer fault diagnosis using grey clustering analysis. In Proceedings of the 27th symposium on electrical power engineering. Tsing Hua University, Taiwan, December 22-23, PD2.20.
9. Lin W.-M., Lin C.-H., and Tasy M.-X. 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
10. Thang K.F., Aggarwal R.K., McGrail A.J., and Esp D.G. Analysis of power transformer dissolved gas data using the self-organizing map. IEEE Transaction on Power Delivery 18 4 (2003) 1241-1248
11. Seng, T. L., Khalid, M., & Tusof, R. (2002). Adaptive GRNN for the modeling of dynamic plants. In Proceedings of the 2002 IEEE international symposium on intelligent control (pp. 217-222), Vancouver, Canada, October 27-30.
12. Wang Z., Liu Y., and Griffin P.J. A combined ANN and expert system tool for transformer fault diagnosis. IEEE Transactions on Power Delivery 13 4 (1998) 1224-1229
13. Yager R.R. A unified approach to aggregation based upon MOM and MAM operators. International Journal of Intelligent Systems 10 (1995) 809-855
14. Zhang Y., Ding X., Liu Y., and Griffin P.J. An artificial neural network approach to transformer fault diagnosis. IEEE Transactions on Power Delivery 11 4 (1996) 1836-1841