@inproceedings{26e161180a0b44538464102351b9ce6e,
title = "RMS percent of wavelet transform for the detection of stochastic high impedance faults",
abstract = "High impedance faults (HIF) are faults which are difficult to detect by overcurrent protection relays. This paper presents a practical pattern recognition based algorithm for electric distribution high impedance fault detection. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with HIF. The analysis using rms ratios of Discrete Wavelet Transform (DWT) yields three phase voltage and current in the low frequency range which are fed to a classifier for pattern recognition. The classifier is based on the algorithm using artificial neural network (ANN) approach. A HIF model was also developed, where the random nature of the arc was simulated using MATLAB.",
keywords = "High Impedance Faults, Pattern Recognition, Wavelet Transforms",
author = "Lai, {T. M.} and Lo, {W. C.} and To, {W. M.} and Lam, {K. H.}",
year = "2012",
doi = "10.1109/ICHQP.2012.6381245",
language = "English",
isbn = "9781467319430",
series = "Proceedings of International Conference on Harmonics and Quality of Power, ICHQP",
pages = "823--828",
booktitle = "Proceedings of 2012 IEEE 15th International Conference on Harmonics and Quality of Power, ICHQP 2012",
note = "2012 IEEE 15th International Conference on Harmonics and Quality of Power, ICHQP 2012 ; Conference date: 17-06-2012 Through 20-06-2012",
}