A novel partial discharge signal detection and estimation method: Mycielski algorithm

This study presents a novel approach to detecting and estimating partial discharge (PD) signals using a pattern recognition-based Mycielski algorithm. An experimental setup is first built in the high-voltage laboratory of Afyon Kocatepe University to test the proposed approach’s performance on PD detection and estimation in medium voltage XLPE cables. PD signals used in this study are measured from this experimental setup. In addition, a low-cost phase-resolved partial discharge analysis is realized, and PD measurement results are strengthened with a portable device with HFCT. Three different PD types are classified using the Mycielski assumption during the detection process, achieving an accuracy of 94.44%. The Mycielski algorithm is adopted to predict the PD signal’s future data in the estimation part, with the failure localization achieving an accuracy of 87.78%. The proposed method is feasible and may be applied in this field since it gives successful results for detecting and estimating PD signals. On the other hand, the accuracy of detection and estimation is open for development.