Data Analysis for Imploving Diagnostic Accuracy in Partial Discharge Monitoring Systems Using Power Line Communication

This study presents the development and validation of a partial discharge (PD) monitoring system (PLC-PDMS) using power line communication (PLC) and ferrite cores (FC). Unlike conventional approaches that analyze signals based on the physical layer rate (PHY rate), this study explores the feasibility of defect type identification by examining PD signals thorough the carrier-to-interference-and-noise ratio (CINR). Specifically, a needle-plane electrode system and twisted pairs were employed as PD sources, and CINR data of PLC were analyzed across different quadrants. The results revealed distinct frequency characteristics depending on the PD source, demonstrating the potential of this method as a more effective alternative to conventional phase-resolved partial discharge (PRPD) pattern analysis.