A new technique for extracting partial discharge signals in transformer winding by application of wavelet analysis

Wavelet transform analysis method is a powerful tool for processing transients and non-stationary or time varying signals. As the wavelet transform possesses the properties of multi-scale analysis and time-frequency domain localization, it is also particularly suitable to process the partialdischarge (PD) signals. In this paper a newtechnique for extracting Partial Discharge signals is introduced, which is implementedfor evaluating electrical measured partial discharges on a 66 kV / 25 MVA fully interleavedwinding of a power transformer. Applying wavelet transform to a signal produces a wavelet detail coefficient distribution throughout the time-scale, which depends on the mother wavelet chosen. This technique is based onthe capability of the chosen mother wavelet for generating coefficients with maximum values. The paper demonstrates that the wavelet based de-noising method proposed inthe paper can be employed in extracting the PD pulses from the measured signal successfully to provide enhanced information and furtherinfer the original site of the PD pulse through capacitive ratio method. In fact, the basic idea of this technique is described and applications to partial discharge studies are explored. The results are employed to improve the accuracy of the PD locationand its propagation studies.