3D deformation monitoring method for temporary structures based on multi-thread LiDAR point cloud

Aiming at visual deformation monitoring for construction scaffold temporary structures, a 3D deformation measurement method based on multi-threaded LiDAR point cloud is proposed. The method consists of two parts, which are point cloud alignment and Scaffold tube axes modeling. Point cloud alignment is performed based on the spatial geometry of the normal vectors and intersection points of homologous feature planes in the scene. The scaffold tube point clouds are extracted using the random sampling consistent principle (RANSAC), and the scaffold tube axes model is further obtained by segmental noise reduction and least-squares fitting. Finally, the 3D deformation monitoring of the scaffold is realized by comparing the tube axes models at different times. The maximum relative error of scaffold deformation is 9.09%. The method provides a new technique for the daily monitoring of construction scaffold groups and can be extended to vehicle-mounted LiDAR applications. • Research on point cloud alignment algorithm based on planar features. • A 3D deformation virtualization monitoring model of scaffolds was developed. • The maximum error in the measurement experiment was 9.09%.