Quantifying Steel Deck Imperfections Using Lidar and Photogrammetry

Abstract Geometric imperfections affect the buckling capacity of thin‐walled structural steel members. Conventional methods to measure geometric imperfections include using hand tools and laser scanning at specific locations around the cross‐section. This paper presents a study to quantify geometric imperfections of three different profiled steel decks using a handheld LiDAR scanner and photogrammetry. Four measurement methods were assessed: (1) traditional hand measurements, (2) highdensity point cloud scanning (using the Artec Leo, up to 0.1 mm precision), (3) lowdensity point cloud data (up to 1 cm precision), and (4) photogrammetry using an Apple iPad Pro with the Scaniverse app. The three decks included a 9/16‐inch (1.4 cm) floor form deck, a 1.5‐inch‐(3.8 cm) wide rib roof deck, and a 3‐inch (7.6 cm) composite floor deck. Key parameters included top and bottom flange widths, the angle and radius between flanges, and thickness. Geometric imperfections were quantified using high‐density point cloud scans in Artec Studio software, which were accurate but required significant post‐processing and could not capture thickness. The Scaniverse app produced detailed deck visualizations through photogrammetry and matched manual measurements; however, its low‐density point cloud lacked sufficient detail to measure key geometric characteristics. The comparison of results aims to improve imperfection scanning and analysis.