A Comparative Study of Wavelet Based De-Noising Signal Based on Transmission System

Power system fault identification using information conveyed by the wavelet analysis of power system transients is proposed for detecting types of transmission line faults. In this paper, a comparative study of wavelet based de-noising signal based on wavelet thresholding is proposed. Discrete Wavelet Transform (DWT) analysis of the transient disturbance caused as a result of occurrence some of faults is performed in the transmission system. With conventional methods we cannot find the location, whereas wavelet makes the location detection very easy. Certain faults like open, short may be detected using simple electronic circuitry, but the location of fault can be analyzed only with wavelet transform Wavelet Toolbox for use with MATLAB for find out the location of the fault. In this we find out the result and compare it to the MATLAB result. Through analysis of the experiment, considering MSE, SNR and smoothness, it can be a good way to evaluate the equality of wavelet threshold de-noising. The results show that the wavelet transform can achieve excellent results in signal de-noising. Threshold rule are “rigsure”, “heursure” “sqtwolog”, “minimaxi” wavelet decomposition level and wavelet function all impact the de-noising performances. MATLAB software is used to be carried out the simulation where the different wavelet and different threshold of the same wavelet for signal de-noising are applied.