Abstract
Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a wide range of remote sensing technologies, among which mobile LiDAR is gaining increasing attention due to its ability to collect high-resolution data over a relatively large area in a short time. The quality of mobile LiDAR data depends not only on the grade of onboard LiDAR scanners but also on the accuracy of direct georeferencing information and system calibration. Consequently, millimeter-level accuracy is difficult to achieve. In this study, the performance of mapping-grade and surveying-grade mobile LiDAR systems for bridge monitoring is evaluated against static laser scanners. Field surveys were conducted over a concrete bridge where grinding was required to achieve desired smoothness. A semi-automated, feature-based fine registration strategy is proposed to compensate for the impact of georeferencing and system calibration errors on mobile LiDAR data. Bridge deck thickness is evaluated using surface segments to minimize the impact of inherent noise in the point cloud. The results show that the two grades of mobile LiDAR delivered thickness estimates that are in agreement with those derived from static laser scanning in the 1 cm range. The mobile LiDAR data acquisition took roughly five minutes without having a significant impact on traffic, while the static laser scanning required more than three hours.
Highlights
Academic Editor: Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA; Indiana Department of Transportation Research and Development, West Lafayette, IN 47907, USA; Abstract: Collecting precise as-built data is essential for tracking construction progress
This paper describes an assessment of alternative mobile light detection and ranging (LiDAR) systems for bridge monitoring
This paper presented an evaluation of mapping-grade and surveyingTLS vs. of the performance grade mobile LiDAR systems for bridge monitoring
Summary
LiDAR, known for its ability to directly generate accurate 3D point clouds with high density, has recently been receiving an increasing amount of interest by the construction management and infrastructure monitoring research/professional communities. Puri and Turkan [27] used a wheel-based mobile LiDAR system equipped with a Velodyne HDL-64E LiDAR unit for tracking the construction progress of a bridge. They pointed out that a noise level in the range of ±3–4 cm was present in the as-built data from MLMSs, affecting the performance of progress tracking. Lin et al [28] evaluated the performance of a wheel-based MLMSs equipped with four Velodyne LiDAR units for mapping airfield pavement before and after a resurfacing process. The positional accuracy of LiDAR point clouds was in the ±5 cm range, and a 9 cm increase in pavement elevation after resurfacing was detected. Data processing and analysis strategies that reduce the impact of the above factors, as well as inherent noise in the point cloud, are required to take full advantage of potential benefits of mobile LiDAR
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