Testing the measurability of steel sections with terrestrial laser scanners

Abstract

When assessing the health of steel structures, capturing, and modelling the geometry is especially important. Point cloud-based technologies have special requirements; previous studies revealed certain challenges that are to be resolved. In this paper, we aimed to develop a method to investigate the effects that the surface reflectance, incidence angle, and distance have on the quality of the point cloud of steel sections. A controlled environment was established for the research, where three terrestrial laser scanners were used to measure four different steel specimens. For validation, we also made reference measurements with a structured light scanner. Due to a large amount of data, a workflow with own routines has been developed for processing the prepared measurement datasets. For standard steel sections, the comparative study clearly showed a significant influence of the section shape, resulting in occlusion and unfavorable incidence angles. Of the devices tested, the one de-signed for high-precision measurements showed the intensity highlighting phenomenon for highly reflective surfaces, however, the measurements demonstrate that with careful selection of measurement conditions and a few pre-processing steps, the technology is well suited for the assessment of steel structures.

Automating Scan to BIM Operations Using Grasshopper

“…The earlier method uses computer vision techniques e.g., Structure from Motion to capture still pictures or video sequences and convert them into 3D point clouds. In contrast, the latter approach uses a range-based method to determine the 3D coordinates of the target object or scene and produce a 3D point cloud as an output [1,11]. To improve efficiency, research should focus on developing more efficient scanning processes, automating the re-orienting, finding, and labeling of targets, and creating a dynamic registration that removes the need for manual registration.…”