Abstract: Aiming at the galloping problem of iced overhead conductors, a three-dimensional dynamic model of iced conductors is established based on the finite element simulation method, and the mechanical and electrical characteristics of conductor galloping under different wind speeds, wind directions, and airflow attack angles are systematically analyzed. The study finds that ice thickness and wind speed are the most sensitive parameters affecting galloping. On this basis, a galloping early warning system integrating 5G communication, sensor monitoring, and intelligent classification algorithms is proposed. The system employs an support vector machine (SVM) model to predict meteorological conditions prone to galloping in the area and combines an AdaBoost classifier to achieve a graded early warning for transmission line galloping risk. This system, with its multi-source perception and intelligent decision-making capabilities, effectively enhances the accuracy in early warning and prevention and control levels of the power grid against galloping disasters.

Key words: overhead conductor, iced galloping characteristics, galloping early warning, finite element analysis, image processing