Time-frequency analysis of PD-induced UHF signal in GIS and feature extraction using invariant moments

The ultra-high-frequency (UHF) method is efficient in partial discharges (PDs) detection in gas-insulated switchgear (GIS). The features extraction of UHF signals is significant for propagation characteristics analysis and PD pattern classification. The PD-induced UHF signals are acquired by the internal UHF sensors in an actual 252 kV L-shaped GIS. The short-time Fourier transform method is applied to process UHF signals and describe the propagation characteristics in L-shaped GIS. Hu's invariant moments of energy density distribution are extracted as features in time-frequency plane. The features are utilised to discriminate different PD defect patterns in actual GIS model by the support vector machine classifier and achieve good results. Finally, a novel system of features extraction and classification of UHF signals is summarised.