Comparison of Fault Classification Methods Based on Wavelet Analysis and ANN

Two methods for classification of transmission line faults are presented and compared, one based on a wavelet analysis and the other on an artificial neural network (ANN). While the wavelet analysis based approach requires consideration of wavelet multiresolution analysis (MRA) level-1 details of the three phase currents and delta currents, the ANN based approach requires the samples of three phase currents as inputs. Simulation studies using EMTP and MATLAB and considering wide variations in fault location, fault inception angle, and fault point resistance for different types of faults have shown that the wavelet analysis based method has an edge over the ANN based method.