Open Science Research Excellence
%0 Journal Article
%A K.Gayathri and  N. Kumarappan
%D 2008 
%J  International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 17, 2008
%T Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN
%U http://waset.org/publications/885
%V 17
%X An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.

%P 846 - 855