Wavelet based de-noising for on-site partial discharge measurement signal

Abstract

This paper presents, wavelet based de-noising technique for on-site partial discharge (PD) measurement signal. The signal is measured from medium voltage power cable at 11 kV distribution substation. The best mother wavelet, decomposition level and the type of threshold for the de-noising technique are selected based on the signal to noise ratio (SNR) aggregation. The SNR aggregation is determined based on the minimum, maximum, mean and standard deviation parameters.   The same standard de-noising procedure is applied for two different PD signals and the selection parameters are done based on the accuracy of de-noising analysis. The analysis is performed in MATLAB software environment and Daubechies 2 (db2) is found as the best mother wavelet at tenth decomposition levels with soft threshold type. This study is specifically performed to develop the de-noising procedure for on-site PD measurement. Overall results indicate that the right selection of the de-noising procedure will help to improve the PD signal detection from on–site measurement.