High impedance fault detection using wavelet transform

This paper proposes a smart method to detect High Impedance Fault (HIF) in distribution networks using Wavelet Transform (WT) and data mining based Decision Tree (DT) model. The proposed method uses WT to decompose the current signal and extracts significant features of the signal. The data mining model reduces the features of the signal and also frames a DT model for the classification of HIF and non-HIF cases. The current signal data for HIF and non-HIF events (Capacitance switching, Linear and Non-Linear load switching) have been acquired by an accurate model of an actual distribution system using MATLAB / SIMULINK. The simulation results show that the proposed method can provide a consistent and powerful protection for HIF.

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