Using partial discharge as sample signal source to identify contamination moisture pattern in power transformer insulating oil

The properly behavior of power transformers is highly dependent of the insulation health. So, the insulation condition assessment can provide information to a system of diagnosis and prognosis, allowing for planning interventions at the appropriate time to avoid unexpected interruptions. This paper presents a technique that can detect moisture contamination in the insulating oil using acoustic signals of partial discharge. In this work, a piezoelectric sensor is mounted in a reservoir with insulating oils with different levels of moisture. A device to simulate partial discharges is immersed in those oils. The detected signals are processed using Discrete Wavelet Transform to extract time-frequency characteristics which are processing using the Principal Component Analysis in order to identify patterns of water content in insulating oil. The results are presented and the methodology has shown a very good technique to be implemented as on line monitoring system.