An evolutionary computation based fuzzy fault diagnosis system for a power transformer

To improve the diagnosis accuracy of conventional dissolved gas analysis (DGA) approaches, this paper proposes an evolutionary programming (EP) based fuzzy system development technique to identify the incipient faults of the power transformers. In comparison to results of the conventional DGA and artificial neural network (ANN) classification methods, the proposed method has been verified to possess superior performance both in developing the diagnosis system and in identifying the practical transformer fault cases.