Most Suited Mother Wavelet For Localization Of Transmission Line Faults
Keywords: Transmission line, Fault localization, Discrete Wavelet Transform (DWT), Mother wavelet, Wavelet function, Artificial Neural Network (ANN), Alternate Transient Program (ATP).
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’ & ‘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.
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