Partial Discharges Classification Methods in XLPE Cable: A Review

Abstract

Partial discharge (PD) signal classification analysis on cross-linked polyethylene (XLPE) cables is complex, requiring a comprehensive understanding of the characteristics of PD patterns. In the realm of high-voltage electrical insulation, PD pattern characteristics, such as PD charge and inception voltage, are essential as assessment criteria in diagnostics systems using PD classifiers. This paper provides a review of the various PD patterns and classifiers used by previous researchers, specifically for XLPE cables. In addition, the differences of the studies on various sensor developments based on PD detection in the past 27 years are also discussed. The repeatability, recognition accuracy, recognition speed, and effect of feature sizes on each PD classification method are reviewed and explained. This review indicates that the pattern recognition for PD signal using artificial neural network (ANN) exhibits better performance than the other methods in terms of accuracy and repeatability, and the reduction of feature size does not affect the accuracy of ANN.

Keywords

• Partial discharge (PD)
• cross-linked polyethylene (XLPE) cable
• solid insulator
• pattern recognition
• feature extraction
• artificial neural network (ANN)