A methodology for identification and localization of partial discharge sources using optical sensors

The present work represents a methodology to detect the location of single as well as multiple Partial Discharge (PD) sources by optical method and to investigate the performance of optical sensors for this purpose. An experimental setup has been arranged in the laboratory for generation of PDs, optical sensing and analysis of the recorded signals obtained from multiple optical sensors. The analysis results prove the effectiveness of the methodology using optical sensors to find whether PD is occurring at single location or multiple locations. For identification of PD locations pattern recognition technique has been utilized by considering the received optical energy as a feature. For feature selection and classification two techniques have been evaluated, viz. Gaussian Mixture Model (GMM) and Support Vector Machine (SVM), and both have shown promising performance. SVM in regression mode was used for identification of unknown PD location/locations. In this case average accuracy obtained was 92.6% when PD is occurring at one location and 80.1% when PD is occurring at two locations. The obtained results indicate that, the proposed methodology can be used to locate partial discharges in high voltage equipment where the optical signals due to discharges find a path to get radiated towards the outer surface.