Optical Partial Discharge Detection and Diagnosis Method Based on PHOG Features

Sensitive signal perception and accurate fault diagnosis are key to partial discharge (PD) optical detection. To improve the effectiveness of the PD optical detection and diagnosis, this article uses the optical sensing technology based on a light guide rod (LGR) to measure the typical PDs in SF6. The characteristics of optical PD signals are analyzed, and a fault diagnosis method for the PD signals detected by the LGR is proposed. An optical and electrical PD experimental platform is built, four different discharge defects are designed, the time-domain signal characteristics of PD optical signals are analyzed, and phase-resolved pulse sequence (PRPS) patterns are plotted. On this basis, a PD optical signal fault diagnosis model based on the pyramid histogram of oriented gradient (PHOG) and optimized support vector machine (SVM) algorithm is established. The results show that the accuracy of this model reaches 96.7%, which is about 10% higher than other algorithms, verifying the effectiveness of detecting PD with an LGR and the reliability of the optical signal diagnostic method based on PHOG features. The results of this study can provide references for PD optical detection and diagnosis in gas-insulated switchgear (GIS) with an LGR.