Research on monitoring tower crane subtle deformation characteristics based on LiDAR data

Pengjun Bai; Chenghui Wan; Shuo Qian; Yue Liu

doi:10.1117/12.2599117

6 June 2021 Research on monitoring tower crane subtle deformation characteristics based on LiDAR data

Pengjun Bai, Chenghui Wan, Shuo Qian, Yue Liu

Proceedings Volume 11849, Fourth International Symposium on High Power Laser Science and Engineering (HPLSE 2021); 1184918 (2021) https://doi.org/10.1117/12.2599117
Event: Fourth International Symposium on High Power Laser Science and Engineering (HPLSE 2021), 2021, Suzhou, China

Abstract

In order to solve the problem of small deformation monitoring of tower cranes that cannot be achieved by traditional monitoring methods, the study of small deformation monitoring technology based on LiDAR data to establish a threedimensional visualization model has been carried out. Use a three-dimensional laser scanner to obtain the point cloud data of the tower crane. Based on the RANSANC algorithm and the optimized ICP algorithm, the point cloud data is processed to establish a three-dimensional visualization model, and the amount of tilt of the tower crane during the work process is compared through the comparison of the results of the two scans. Therefore, it is concluded that this method has greater advantages than traditional deformation monitoring methods. It realizes the deformation monitoring of small feature points and can calculate the deformation results faster and more accurately, which reflects the intuitiveness and real-time of 3D laser scanning. It is possible to eliminate potential safety hazards as much as possible. It will provide a favorable basis for future research on subtle deformation characteristics in buildings and other fields

Citation Download Citation

Pengjun Bai, Chenghui Wan, Shuo Qian, and Yue Liu "Research on monitoring tower crane subtle deformation characteristics based on LiDAR data", Proc. SPIE 11849, Fourth International Symposium on High Power Laser Science and Engineering (HPLSE 2021), 1184918 (6 June 2021); https://doi.org/10.1117/12.2599117

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