Application of Chaos Synchronization Technique and Pattern Clustering for Diagnosis Analysis of Partial Discharge in Power Cables

Abstract

This paper primarily discusses the measurement of partial discharge (PD) phenomena and clustering in the defect pattern of a cross-linked polyethylene power cable joint. First, a high-speed data acquisition and pretreatment were performed for PD electrical signals at a sampling rate of 20 MS/s. The crucial characteristic signals were reversed to reduce the calculated amount of noise. A characteristic matrix was created according to the resulting dynamic error of chaos synchronization. The characteristic parameters were extracted using the fractal theory. Finally, the extension theory was used to develop a diagnostic system and anti-interference test. A comparison with the existing Hilbert-Huang transform (HHT) method revealed that the two characteristics extracted from the chaos synchronization results using the fractal theory were recognized at a higher pattern recognition rate by employing the extension theory. The proposed method can extract crucial information concerning PD as a defect in power cable joints.

Keywords

• Chaos synchronization
• extension
• fractal
• Hilbert–Huang transform
• partial discharge