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In this paper an efficient method for detection of inrush current in distribution transformer based on wavelet transform is presented. This method uses Wavelet Transform (WT) and Probabilistic Neural Network (PNN) to discriminate inrush current from other transients such as capacitor switching, load switching and single phase to ground fault. WT is used for decomposition of signals and PNN for classification...
This paper presents S-Transform based Competitive Neural Network (CNN) 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 CNN is used for classification. Inrush current data and other transients are obtained...
Transformer inrush currents are high magnitude, harmonic-rich currents generated when transformer cores are driven into saturation during energization. In this paper an efficient method for detection of inrush current in distribution transformer based on wavelet transform is presented. Using this method inrush current can be discriminate from other transients such as capacitor switching, load switching...
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...
Ferroresonance has more damaging effects on transformers and other equipments in distribution networks such as oscillating over voltages and over currents, distortion in voltage and current waveforms, transformer heating, loud noise due to magnetostriction and mal-operation of the protective devices. In this paper the factors that affect the ferroresonance over-voltages are checked to find the method...
This paper presents a Wavelet Kernel Fisher Classifier (WKFC) for ferroresonance detection. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching and transformer switching. Wavelet transform is used for decomposition of signals, feature selection is done by Kernel Principal Component Analysis (KPCA). The Fisher classifier is applied...
In this paper an efficient method for detection of ferroresonance in distribution transformer based on wavelet transform is presented. Using this method ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Multi Layer Perceptron (MLP) neural network used for classification...
A novel method for Ferroresonance detection is presented in this paper. Using this method Ferroresonance can he discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and competitive neural network used for classification. Ferroresonance data and other transients are obtained by simulation using...
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