Research on Electrical Equipment’s Fault Diagnosis Based on the Improved Support Vector Machine and Fuzzy Clustering

Abstract

In this paper, the author research on electrical equipment’s fault diagnosis based on the improved support vector machine and fuzzy clustering. Combining the support vector combined fuzzy sets and neural network to carry on the fault diagnosis is a most prosperous diagnosis method. This article put forward a sample processing method using fuzzy clustering and studied the application of fuzzy competition classification method in extracting contradiction samples, then advanced the diagnosis method of neural network based on fuzzy clustering, finally carried on the simulation research. The calculation results show that all the above- mentioned methods are quite practical. It is a better and prosperous way to combine neural network theory and fuzzy clustering to carry on insulation diagnosis. The experiment result shows the proposed method is effective.