Fault Classification and Faulted Phases Selection using Traveling Wave Theory and Fuzzy System

A traveling wave based algorithm for fault classification and faulted phases selection is presented in this paper. The proposed algorithm is composed of two major stages. In the first stage, after extraction of modal components from three phase signals and by means of Teager energy operator (TEO), traveling waves are extracted from modal signals. Then ratios of initial traveling wave in different modal components are used for the fault classification and faulted phases selection purpose. TEO is a very simple method which can extract traveling waves with very high speed and resolution. In the second stage, fault classification and faulted phases selection is performed based on the information extracted from the previous stage. Intelligent methods are the best choice to be used in the second stage and for the first time are utilized in this paper. Fuzzy system, which is used in this paper as a classifier, is able to classify the faulted signal with a high accuracy. Simulation results show that the proposed algorithm has an efficient and accurate performance in terms of close-in faults, high impedance faults and faults with very low inception angle.