Transmission Line Faults Classification Based on Alienation Coefficients of Current and Voltage Waveform and SVM

In order to further improve the speed and accuracy of transmission line fault classification, a new method based on alienation coefficients of the combination of fault current and voltage waveform is proposed in this paper, which uses the support vector machine(SVM) as the classification tool. This method analyzes the current and voltage waveforms simultaneously of a quarter cycle after a fault occurs, and calculates the waveform alienation coefficients on the total 8 signal channels of the threephase and neutral lines of the current and voltage respectively, then composes them as input features vector, finally completes the fault classification by using SVM model. The experiments compare the classification effect when different signal types are used, and test the robustness and applicability of the model by changing the sampling rate and adding noise interference. Simulation results show that the method can quickly classify faults after transmission line faults occur with a classification accuracy rate reaches 99.94%, which has great practical application potential.