Neural network filtration for arc faults location on power transmission lines

This paper presents filtration using neural network for arc fault location, which allows to determine the distance to a fault, as a result of considering natural fault loops. It is assumed that three-phase voltages and currents from both ends of the line are the input signals of the fault locator and naturally of the neutral network applied for filtering the input signals. In addition to natural fault loop signals also use of symmetrical components (positive and negative or incremental positive sequence components) to fault location were considered as well. Results of evaluation study have been included, analyzed and discussed. Influence of filtration has been also considered.