Fault Location in Underground Cables using ANFIS Nets and Discrete Wavelet Transform

Barakat S, Eteiba MB and Wa

Abstract

This paper presents an accurate algorithm for locating faults in a medium voltage underground power cable using Adaptive Network-Based Fuzzy Inference System (ANFIS). The proposed method uses five ANFIS networks and consists of 2 stages, including fault type classification and exact fault location. In the first part, an ANFIS is used to determine the fault type, applying four inputs, i.e., the maximum detailed energy of three phase and zero sequence currents. Other four ANFIS networks are utilized to pinpoint the faults (one for each fault type). Four inputs, i.e., the maximum detailed energy of three phase and zero sequence currents, are used to train the Neuro-fuzzy inference systems in order to accurately locate the faults on the cable. The proposed method is evaluated under different fault conditions such as different fault locations, different fault inception angles and different fault resistances.

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