Detection of Inrush Current Using S-Transform and Probabilistic Neural Network

Transformer inrush currents are high magnitude, harmonic-rich currents generated when transformer cores are driven into saturation during energization. This paper presents an S-Transform based Probabilistic Neural Network (PNN) classifier for recognition of inrush current. Using this method inrush current can be discriminate from other transients such as capacitor switching, load switching and single phase to ground fault. S-transform is used for feature extraction and PNN is used for classification. Inrush current data and other transients are obtained by simulation using EMTP program. The simulation results reveal that the combination of S-Transform and PNN can effectively detect inrush current from other events.