Synthetic diagnostic method for insulation fault of oil-immersed power transformer

A diagnostic method considering the information of dissolved gas analysis (DGA) and electrical items synthetically is presented. A neural network using the DGA results is applied to achieve the initial conclusion. Then, several fuzzy equations are established to realize the detailed diagnosis. As many sorts of electrical data and relevant DGA information are selected in different fuzzy equations, the accuracy of the detailed diagnosis will be higher. With the advantage that the results of DGA and electrical items are combined in the diagnostic method, the accuracy should be increased significantly.