A simulated experimental system and risk prediction method for ignition caused by overhead lines short-circuit

In windy weather, overhead lines swing and collide with each other, often resulting in short-circuits and arc faults. The line is partially molten and produces numerous hot metal particles, which fall and may ignite the fuels on the ground. This paper developed an experimental system to obtain hot particle dimensions at different short-circuit current levels. Based on the results of this experiment, an ignition prediction method was developed. The particle parameters from the experiments were used as a bridge that to complete the prediction from short-circuit current to ignition risk. A neural network was trained according to the experimental and calculated results, then used to predict the risk of ignition. The overhead lines in a forest were used as an example application to perform thte investigation. The results show that copper lines in a forest with needles on the ground create a high risk of ignition hazard.