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International Conference on Software Technology and Engineering, 3rd (ICSTE 2011)
Mohamed Othman
Mohamed Othman
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Raja Suzana Raja Kasim
Raja Suzana Raja Kasim
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ASME Press
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Power transformers were widely used in power system and the transformer fault diagnosis technology has great significance to improve the level of transformer operation and maintenance. Dissolved Gas Analysis (DGA) is one of the most useful techniques to detect the incipient faults of power transformer and fundamental of characteristic gas method and three ration method was presented. A power transformer fault diagnosis technique based on Radial Basis Function neural networks (RBFNN) was proposed to establish a large transformer fault diagnosis model and the hidden layer neurons was determined with Genetic Algorithm (GA), the simulation shows this comprehensive method was feasible and has good application prospects.

Key Words
1 Introduction
2 Neural Networks Model for Fault Diagnosis
3 Simulations and Conclusions
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