Research on electric power aerial work recognition model based on deep learning

Electric power operation is an important component to ensure the continuous supply of electric power. However, electric power operation involves a wide range, complicated process, high risk factor, and serious accidents such as personal injury often occur. Although the rules and regulations of power safety production are gradually improved and the operation management mode is gradually optimized, the low degree of digitalization and intelligence still makes the power operation face a high risk of major accidents. In this paper, deep learning framework PyTorch and YOLOv3 algorithm are used to construct a digital and intelligent situation element extraction method for the feature extraction process of image data, build a high-altitude work identification model for electric power construction to learn and train the judgment of high-altitude work, detect workers and safety belts as targets, and accurately send out early warning signals. The results provide the data basis for predicting the risk situation of electric power operation.