Open AccessFault location in underground cables using ANFIS nets and discrete wavelet transform
Author(s) -
Shimaa Barakat,
Magdy B. Eteiba,
Wael Ismael Wahba
Publication year - 2014
Publication title -
journal of electrical systems and information technology
Language(s) - English
Resource type - Journals
ISSN - 2314-7172
DOI - 10.1016/j.jesit.2014.12.003
Subject(s) - adaptive neuro fuzzy inference system , fault (geology) , engineering , wavelet , energy (signal processing) , algorithm , fuzzy logic , control theory (sociology) , computer science , fuzzy control system , artificial intelligence , mathematics , statistics , geology , seismology , control (management)
This paper presents an accurate algorithm for locating faults in a medium voltage underground power cable using a combination of Adaptive Network-Based Fuzzy Inference System (ANFIS) and discrete wavelet transform (DWT). 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