Fuzzy TOPSIS and BPANN Based Fault Diagnosis Method for Power Transformer

Aiming at the problem of diagnosing the structure of model and collecting the data of failure sample being very complicated in the traditional diagnosis technology,this paper extendes the method of TOPSIS on vague sets.The basic concepts of vague sets,similarity measurement and the usage of semanteme variable set expressed by vague value are introduced.Hereby the original sample data can be distinguished and clustered so to reduce the quantity of sample data enough to somehow balance the fault feature information and the mapping space complexity.Furthermore,a BP neural diagnosing network is constructed for diagnosis of all kinds of transformer faults.The cases analysis indicate that the proposed method has obvious advantage than the conventional diagnosis methods for transformer faults.