Transformer Partial Discharge Pattern Recognition Based on Random Forest

Abstract

As the deficiencies of the classifier algorithm commonly used in the partial discharge pattern recognition, this paper studied the application of RF in transformer partial discharge pattern recognition. Firstly, extracting the statistical characteristics from partial discharge test data to establish the discharge samples; Then, using ten folds method to judge the algorithm performance and compare the recognition accuracy of BP neural network, support vector machine, KNN, CART and RF algorithm. The results showed that the accuracy of the discharging pattern classifier basic on RF algorithm was the highest. The main differences between the different discharge modes were discussed by CART algorithm which composes RF.