Redundancy alarm algorithm for hidden danger points in transmission lines under unmanned aerial vehicle three-dimensional ranging

In the process of inspecting transmission lines, it is difficult to accurately identify and eliminate redundant hidden points that are close or overlapping in spatial location when facing different scales and complex power grids. Therefore, a redundant alarm algorithm for hidden danger points in transmission lines based on unmanned aerial vehicle 3D ranging technology is proposed. Extract representative point information from the original drone 3D ranging point cloud data and write it into a new file in LAS format. Simplifying point cloud data through voxel grid partitioning can effectively reduce redundant information. Process and match point cloud data to obtain hidden points. Take three steps to eliminate redundancy: spatial location, time interval, and type merging. Based on the degree of threat, compare the shape of the cluster with known hidden point shape templates to determine whether the cluster is a hidden point. The experimental results show that the proposed method has a high processing efficiency, above 0.9, and can maintain an accuracy of above 0.8.