Free webinar by Dr. Hui Ma and Professor Tapan Saha, University of Queensland, Australia

Thursday, June 2, 2016 | 4:00pm – 5:00pm ET

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Partial discharge (PD) is a localized breakdown in the insulation system of high voltage (HV) apparatus. PD measurement has been adopted for online condition monitoring and diagnosis of HV apparatus. However, PD is a complicated phenomenon and stochastic in nature. It is still a challenging task to de-noise the measured PD signals, extract representative features from measurement data, and identify PD sources (i.e. insulation defects) that cause discharge inside HV apparatus.

In this webinar we present a general framework of applying signal processing and pattern recognition techniques to PD signal analysis. Within this framework, we discuss a number of representative algorithms for PD signal de-noising, dimensionality reduction and feature extraction, multiple PD source separation, and PD source classification in the context of online PD measurement. Case studies using datasets collected from PD measurements in laboratory and at field are presented to demonstrate the applicability of various signal processing techniques in PD signal analysis.

There is also a certificate of completion available following the webinar.