A New Method for Recognition of Arcing Faults in Transmission Lines using Wavelet Transform and Correlation Coefficient

Abstract

In this paper a novel method based on discrete wavelet transform and correlation coefficient is presented for distinguishing between arcing and permanent faults. The algorithm includes offline and online processing. In the offline, discrete wavelet transform is used to decompose typical faulted phase voltage waveforms during arcing faults. An index is then defined and computed. The index is based on the normalised energy of detail coefficients at resolution levels 1 to 14. The online processing consists of capturing the faulted phase voltage waveform using a 20 kHz sampling rate, and decomposing it by db4. Finally, arcing faults are distinguished from permanent faults based on correlation coefficient of the computed index of the pre-stored typical arcing faults and a recorded indistinct signal. The effectiveness of the approach has been tested for numerous arcing and permanent fault conditions on a transmission line using the Electromagnetic transient Program (EMTP) software tool. The simulation results show the capability of the proposed method in distinguishing between arcing faults from permanent faults.