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At present, electric shock accidents are still the main safety issue for distribution workers. In recent years, the promotion of video AI applications has made it possible to detect whether the human body has crossed the safety line, and how to detect the actual height of the workers and the actual spatial distance between them and live equipment and live lines has become a challenge for researchers. Therefore, this article proposes to use LiDAR, edge processing module, and warning module to build a pre control device for safe operation behavior in power distribution scenarios, scan the power distribution operation scene in real time, use deep learning methods to identify objects such as distribution stations, human bodies, high-voltage equipment, and transmission lines in the point cloud, and calculate the spatial distance between operators and high-voltage equipment and lines in the station area through the edge point coordinates of object point cloud aggregation. When the spatial distance approaches or exceeds the voltage safety distance, the warning module sends voice reminders to achieve the pre control effect of safe operation behavior. The experimental results show that the device can significantly reduce the false alarm rate compared to the video scheme, accurately detect the actual distance between operators and high-voltage live equipment and high-voltage transmission lines in the substation area, and provide timely and effective alarm prompts. Therefore, this scheme can be applied in power distribution operation scenarios to protect the personal safety of workers.