A modular approach for classification and location of arcing and non-arcing faults on transmission lines

This paper presents a modular approach for detection, classification and location of transmission line faults using wavelet transform along with intelligent techniques. By using wavelet Multiresolution Analysis (MRA), summation of detail coefficients is extracted for three-phase fault currents. These detail coefficients constitute the edifice for classification and location of faults. The classification of different types of faults is done using Fuzzy Inference System (FIS). The algorithm proceeds with classification of arcing and non-arcing faults, and then locates the fault on the transmission line using Modular Artificial Neural Networks (MANNs). The results indicate that such a modular approach can be used for supporting high-speed protective relaying systems during both arcing and non-arcing faults.

Keywords: DWT, discrete wavelet transform, MRA, multiresolution analysis, FIS, fuzzy inference systems, MANNs, modular ANNs, artificial neural networks, fault classification, fault location, transmission line faults, transmission lines