Partial Discharge Localization Techniques: A Review of Recent Progress

Monitoring the partial discharge (PD) activity of power equipment insulation is crucial to ensure uninterrupted system operation. PD occurrence highly correlated weakened strength. If occurrences are left unchecked, unexpected breakdowns may occur. The comprehensive diagnostic process includes detection, localization, and classification PD. Accurate source localization necessary locate segment. As a result, rapid precise has become primary focus diagnosis for insulation. This paper presents review different approaches including conventional, machine learning (ML), deep (DL) as subset ML approaches. focuses on DL developed in past five years, which have shown promising results over conventional Additionally, detection using unconventional, PCB antenna designed based UHF techniques presented discussed. Important benchmarks, such sensors used, algorithms employed, compared, performances, summarized detail. Finally, suitability applications discussed their strengths limitations.