Use of Unmanned Aerial Vehicle for Quantitative Infrastructure Evaluation
Publication: Journal of Infrastructure Systems
Volume 21, Issue 3
Abstract
Unmanned aerial vehicles (UAVs) allow remote imaging which can be useful in infrastructure condition evaluation. Furthermore, emerging noncontact sensing techniques such as digital imaging correlation (DIC) and other photogrammetric and visual approaches, including simultaneous localization and mapping (SLAM), can compute three-dimensional (3D) coordinates and perform deformation measurements as in the case of DIC/photogrammetry. A quantitative assessment of ways remote sensing in conjunction with UAVs could be implemented in practical applications is critically needed to leverage such capabilities in structural health monitoring (SHM). A comparative investigation of the remote sensing capabilities of a commercially available UAV, as well as both an optical metrology system known by the acronym TRITOP and the X-Box Kinect, is presented in this paper. The evidence provided demonstrates that red-green-blue cameras on UAVs could detect, from varying distances, cracks of sizes comparable to those currently sought in visual inspections. In addition, mechanical tests were performed on representative bridge structural components to attempt, for the first time to the writers’ best knowledge, deformation measurements using an aerial vehicle; displacements and corresponding accuracies were quantified in static and flying conditions. Finally, an outdoor feasibility test with the UAV was accomplished on a pedestrian bridge to test the marker identification algorithm.
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Acknowledgments
The writers acknowledge Trilion Quality Systems for the use of the TRITOP system. The writers further acknowledge Dr. Ani Hsieh and Dr. Frank Moon for allowing the use of their laboratory facilities at Drexel, and for providing feedback at various stages of the research reported in this paper. The writers finally want to thank Mr. Matthew Nial and Mr. Eric Cristofalo for their assistance in the development of the algorithms.
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© 2014 American Society of Civil Engineers.
History
Received: Dec 23, 2013
Accepted: Oct 29, 2014
Published online: Dec 3, 2014
Discussion open until: May 3, 2015
Published in print: Sep 1, 2015
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