Abstract
Abstract With the continuous development of the power industry, the safety of power tower climbing operations is increasingly valued. This study focuses on the anti-fall safety protection of electric power tower climbing operations and proposes a study on the anti-fall safety protection of electric power tower climbing operations based on the Longhorn whisker algorithm. Firstly, real-time image acquisition of the climbing operation site is carried out through the camera equipment carried by the drone, ensuring clear and comprehensive information on the working environment is obtained. Secondly, extract hazardous features in climbing operations, such as abnormal worker posture, tool detachment, etc. These features are important indicators of potential fall risks. Finally, a fall hazard detection model is constructed and optimized using the Longhorn Whisker algorithm to identify and warn of impending fall events, thereby providing timely safety protection for climbing operators. The experimental results show that this method has shown significant effectiveness in improving job safety, providing strong technical support for the safety protection of power tower climbing operations.
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