The tension at the suspension point of transmission towers is an important parameter for line renovation and collapse accident warning. Although airborne LiDAR can provide high-precision spatial information for transmission line scenes-LiDAR point cloud data, lacks timely feedback on the operational status information of elements (such as tension of suspension points). A tension extraction method for tower suspension points based on LiDAR point clouds was proposed, and a new approach for studying micro physical parameters of transmission line spatial information was designed. Firstly, a three-dimensional spatial model of the transmission line was reconstructed from point cloud. Then, a mapping model between the spatial curve model and the horizontal stress of the transmission line was constructed. Finally, based on the tension vector relationship of adjacent transmission lines, the tension at the suspension point of the tower was extracted. This method reconstruct the three-dimensional model of transmission lines and extract the tension of tower suspension points in real-time operation based on LiDAR point cloud. Compared with finite element analysis method, the maximum relative error is 3.26%. The research can be extended and applied to the safety inspection and state parameter detection of large-scale transmission lines.