High impedance fault detection methodology using wavelet transform and artificial neural networks
- 23 February 2011
- journal article
- Published by Elsevier BV in Electric Power Systems Research
- Vol. 81 (7), 1325-1333
- https://doi.org/10.1016/j.epsr.2011.01.022
Abstract
No abstract availableKeywords
This publication has 28 references indexed in Scilit:
- High-impedance fault detection using multi-resolution signal decomposition and adaptive neural fuzzy inference systemIET Generation, Transmission & Distribution, 2008
- High-Impedance Fault Detection Using Discrete Wavelet Transform and Frequency Range and RMS ConversionIEEE Transactions on Power Delivery, 2005
- Directional ground-fault indicator for high-resistance grounded systemsIEEE Transactions on Industry Applications, 2003
- A novel approach to the classification of the transient phenomena in power transformers using combined wavelet transform and neural networkIEEE Transactions on Power Delivery, 2001
- The artificial neural-networks-based relay algorithm for the detection of stochastic high impedance faultsNeurocomputing, 1998
- A novel technique for high impedance fault identificationIEEE Transactions on Power Delivery, 1998
- Detecting arcing downed-wires using fault current flicker and half-cycle asymmetryIEEE Transactions on Power Delivery, 1994
- Detection of high impedance arcing faults using a multi-layer perceptronIEEE Transactions on Power Delivery, 1992
- Analysis of high-impedance fault generated signals using a Kalman filtering approachIEEE Transactions on Power Delivery, 1990
- An arcing fault detection technique using low frequency current components-performance evaluation using recorded field dataIEEE Transactions on Power Delivery, 1988