Most Suited Mother Wavelet For Localization Of Transmission Line Faults

Abstract This paper is a modest approach to determine the most suited mother wavelet for localization of transmission line faults. Discrete wavelet transform DWT and artificial neural network ANN based algorithm has been developed for this purpose. Extensive simulation studies were carried out in ATP for various types of fault conditions locations and fault resistances. DWT analysis of the sending end current signals was done using daubechies wavelets. Five wavelets db1 db2 db3 db4 26 db5 were selected associated with different centre frequency and period. The statistical features extracted from the DWT coefficients of the sending end current signals were used to train the ANN for identifying the fault locations. The results shows that the db3 mother wavelet is best suited for localization of transmission line faults because of its short period and more number of vanishing moments.