UAV-enabled Structure from Motion Photogrammetry for Bridge Crack Detection
项目名称: UAV-enabled Structure from Motion Photogrammetry for Bridge Crack Detection
摘要: Bridge is a common structure form widely adopted in the engineering construction, which plays an important role in traffic and transportation system. Crack is considered as an indicator for a bridge’s structural and functional failures, and crack detection is one of the major tasks during bridge inspection to maintain the structure health and serviceability of a bridge. Literature review indicated that until now detection of 3D bridge crack is still a great challenge for structural engineer and there is little research on the automatic characterization of 3D bridge cracks. The objective of this proposed research is to develop a UAV-Enabled Structure-From-Motion Photogrammetry for detection and characterization for 3D bridge crack detection. Commercially available low-cost UAVs will be used to take the images needed for the analyses. A Structure-From-Motion Photogrammetry algorithm will be developed to reconstruct the 3D models of the bridges and deep learning will be used to automatically determine the cracks from the 3D modes. With the 3D models, crack characterization such as crack lengths, depths, widths, and patterns on bridge components can be automatically measured with high accuracy. The crack measurements will be compared and validated against results obtained from other existing methods such as local sensors and the high accuracy LiDAR system. This method for 3D crack mapping will provide us a high accuracy, low cost, and easy-to-operate tool for bridge maintenance and management.
状态: Active
资金: 92402
资助组织: Transportation Infrastructure Durability & Life Extension<==>Missouri University of Science & Technology, Rolla<==>Office of the Assistant Secretary for Research and Technology
项目负责人: Kline, Robin
执行机构: Missouri University of Science & Technology, Rolla
开始时间: 20210701
预计完成日期: 20220930
实际结束时间: 20220930
主题领域: Bridges and other structures;Data and Information Technology;Maintenance and Preservation
检索历史
应用推荐