Partial Discharge Detection and Diagnosis of Transformer Bushing Based on UHF Method

Bushings are essential components in a power transformer where incipient partial discharge (PD) activities and its detection and diagnosis cannot be ignorant. In this paper, an oil-impregnated paper (OIP) bushing is modeled to investigate that the oil gaps between the flange and condenser body in a typical OIP bushing provide a feasible path to trace the electromagnetic signal. As a non-destructive method, UHF (Ultra High Frequency) is proposed to detect 4 typical inside and outside PD defects of 110 kV bushings. To analyze the parameters of different defects, not only phase-resolved partial discharge (PRPD) is presented, but also 16 detailed time-domain and frequency-domain parameters of UHF signal are involved. Then feature extraction and selection are conducted through comparative principal component analysis (PCA) and extremely randomized trees (ET) algorithms. It is revealed that the selected features are representative and ET greatly reduces the amount of data whilst ensuring high accuracy. Fault diagnosis for bushing is finally achieved via support vector machine (SVM) with the selected features. The presented work of bushing PD detection based on UHF sensors provides a complete solution for the bushing diagnosis in potential field application and maintenance.