Laser-based cross-section measurement of cold-formed steel members: Model reconstruction and application

The objective of this paper is to present procedures for processing three-dimensional point clouds that are generated from laser-based scanning of a cold-formed steel member into useful measurements of cross-section dimensions and imperfections, as well as for use in finite element simulations of the as-measured geometry. The measurement data comes from a unique laser-based scanning platform developed by the authors. Multiple passes on the target cold-formed steel specimen using a line laser are registered with an iterative closest point algorithm to develop the initial three-dimensional point cloud. A novel feature recognition method is proposed to distinguish and extract geometric characteristics such as corners and flats in the targeted specimen. Three different applications are demonstrated herein for the three-dimensional point cloud: feature recognition for determination of nominal dimensions, deviation from nominal configuration for determination of simplified imperfection patterns, and re-mapping of the three-dimensional point cloud onto regularized grids appropriate for subsequent shell finite element modeling. The high fidelity of the measured data provides potential for new insights across all three application areas. Extensions of the algorithms to other cold-formed steel cross-sections, as well as built-up cold-formed steel cross-sections, are currently being pursued.