Multi-Sensor Fusion-Based High-Voltage Proximity Early Warning for Autocrane in Complex Electromagnetic Environments

With the increasing number of construction machinery operations near high-voltage power facilities, determining how to improve operational safety has become an urgent issue that needs to be addressed. To address safety hazards when autocranes operate near live high-voltage power lines, this study proposes a high-voltage proximity safety early warning method for autocranes. The method collects the electric field signals of high-voltage power lines in real time via an electromagnetic sensor array, calculates the azimuth angle of the live conductor using the MUSIC algorithm, and acquires the 3D point cloud data of the high-voltage power lines through high-density scanning with a LiDAR. By achieving time synchronization and coordinate registration of the electromagnetic sensor data and LiDAR data, a 3D spatial model of the high-voltage power lines is established, and the minimum distance between the crane boom and the live conductor is calculated. It identifies the voltage level, computes the basic safety distance, modifies the distance with environmental factors, and then multiplies it by a safety factor to obtain the dynamic safety threshold. Finally, based on the real-time distance between the crane boom and the live conductor, hierarchical early warnings and control actions are triggered.