Wavelet Packet Transform based Multi Resolution Analysis technique for classification of LC waveforms on polluted insulating surfaces

Abstract

This paper expose a novel algorithm to monitor and classify the pollution severity level of insulators based on Leakage Current (LC) waveforms investigation. For this purpose, LC waveforms acquisition is firstly carried out on a plane insulator model under various saline pollution conductivities. Then, LC is investigated and decomposed in five levels using the Wavelet Packet Transform (WPT). Two, four, eight, sixteen and thirty-two coefficients are obtained from the first level to the fifth one respectively. Next, Standard Deviation-Multi Resolution Analysis (STD-MRA) is used to extract features from WPT coefficients. It is noted that the higher the pollution severity, the higher the STD value. Finally, STD values are used as inputs to three well known classification methods (K-Nearest Neighbors, Naive Bayes and Support Vector Machines), while the sole output is the pollution conductivity value. Results announce that the higher the decomposition level, the better the classification performance. WPT methodology is presented as a highly efficient technique for LC investigation and classification.