Abstract:The traditional overhead transmission line project completion acceptance process relies on manual measurement and paper records. However, this method has the risk of human error and inaccurate information, with high labor and time cost, low efficiency and unsatisfactory effect. This paper proposes a digital completion acceptance mode, which uses lidar to scan the acceptance project, collect point cloud data and other flight data, and build the line ontology and channel point cloud model through data preprocessing, AI data segmentation and classification. The segmented point cloud data and the line design model data are compared and analyzed to determine whether they meet the relevant acceptance criteria Allowed values in. The digital completion acceptance mode can effectively reduce the risk of human error and inaccurate information, and improve the acceptance efficiency and effect. The digital acceptance platform developed based on this mode is tested in an engineering project, and the results show that the manual participation can be greatly reduced, and the acceptance time can be effectively shortened.