Research on Transmission Line Fault Location Based on the Fusion of Machine Learning and Artificial Intelligence

After a transmission line fails, quickly and accurately find the fault point deal with it, which is of great significance to maintaining normal operation power system. Aiming at problems low accuracy traditional traveling wave location methods many affected factors, this paper relies on distributed monitoring points arranged lines study improve lines. First, when signal that moves both ends will be generated transmitted along line. We use Radon transform algorithm process signal. Then, uses ant colony analyze verify extent faults then optimizes high-precision collection processing. Finally, simulation distance measurement carried out double-terminal multiterminal (T-shaped lines) branches. The results show that, for double-ended lines, increases speed matrix calculations same time makes error grid still maintain improved effect.