Research on Swing Prediction of Overhead Line Robot Inspection Arm

Abstract

Abstract Overhead lines and various fittings on the lines are prone to damage when exposed to the outdoor environment for a long time. Therefore, overhead line inspection work is required. The use of overhead line robots instead of manual inspections can reduce the labor intensity of personnel and protect their personal safety. The current overhead line robots have the problem of low intelligence and less consideration of the robot swinging with the wire. In this regard, the paper focuses on the swing prediction technology for the large-angle swing of the robot platform, and proposes a method based on real-time variance statistics. The large-angle swing prediction model. Finally, a comparative experiment was conducted with the combined model of empirical mode decomposition and support vector regression based on time series forecasting, and real experimental data were used to verify the rationality and effectiveness of the proposed algorithm and model.