A new method based on fuzzy TOPSIS for transformer dissolved gas analysis

This paper presents a new classifier based on fuzzy technique of order preference by sunilarity to ideal solution (TOPSIS) for power transformer fault diagnosis in dealing with the dissolved gas analysis(DGA) problem, which is treated as the collision between lowering complex process of the analysis and increasing quantity of monitoring informations. Two methods are employed to ameliorate the diagnosis condition. Firstly, the essential concept of fuzzy set using semantic variables is introduced. And this classification approach is then combined with the TOPSIS considering the efficiency in managing imperfect and incorrect data, and the multiple attribute decision matrix is deduced by fuzzy mapping. Secondly, the vector interval is calculated, which fixes the relative similarity of the possible fault types on the evidence of various gas ratios. Finally, contrasted with IEC three-ratio method, the new method has been proved rapid and exact in judging the operation states, and therefore the safety, stability and economy of transformer are improved.