Study on fault diagnosis for power transformer based on cloud matter element analysis principle and DGA

Abstract

Dissolved gas-in-oil analysis (DGA) is an important method to find the hidden or incipient insulation faults of oil-immersed power transformer. Matter element theory was employed to research the fault diagnosis of transformer with qualitative and quantity advantages. However, the method did not consider the uncertain essence of the fault diagnosis of transformer. And in the fact, there were two uncertain characteristic in it, random and fuzzy. Hence a new fault diagnosis method is presented in this paper. The method has two advantages of considering two uncertain characteristic and realizing fault diagnosis qualitatively and quantitatively based on cloud model and matter element theory. By building the cloud matter element models of transformer fault diagnosis and calculating the correlation function of feature matter element models and standard ones, fault modes of transformer are identified effectively. Then, the results of examples research indicate the method is effective.