The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Structural Displacement Measurement Using an Unmanned Aerial System
Open accessAbstract
Vibration‐based Structural Health Monitoring (SHM) is one of the most popular solutions to assess the safety of civil infrastructure. SHM applications all begin with measuring the dynamic response of structures, but displacement measurement has been limited by the difficulty in requiring a fixed reference point, high cost, and/or low accuracy. Recently, researchers have conducted studies on vision‐based structural health monitoring, which provides noncontact and efficient measurement. However, these approaches have been limited to stationary cameras, which have the challenge of finding a location to deploy the cameras with appropriate line‐of‐sight, especially to monitor critical civil infrastructures such as bridges. The Unmanned Aerial System (UAS) can potentially overcome the limitation of finding optimal locations to deploy the camera, but existing vision‐based displacement measurement methods rely on the assumption that the camera is stationary. The displacements obtained by such methods will be a relative displacement of a structure to the camera motion, not an absolute displacement. Therefore, this article presents a framework to achieve absolute displacement of a structure from a video taken from an UAS using the following phased approach. First, a target‐free method is implemented to extract the relative structural displacement from the video. Next, the 6 degree‐of‐freedom camera motion (three translations and three rotations) is estimated by tracking the background feature points. Finally, the absolute structural displacement is recovered by combining the relative structural displacement and the camera motion. The performance of the proposed system has been validated in the laboratory using a commercial UAS. Displacement of a pinned‐connected railroad truss bridge in Rockford, IL subjected to revenue‐service traffic loading was reproduced on a hydraulic simulator, while the UAS was flown from a distance of 4.6 m (simulating the track clearance required by the Federal Railroad Administration), resulting in estimated displacements with an RMS error of 2.14 mm.
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Cites
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Cited by
Azimi, M., Eslamlou, A., & Pekcan, G. (2020) · Sensors · doi:10.3390/s20102778 · Cited by 769
Assessment and monitoring of bridges using various camera placements and structural analysis
Bai, Y., Demir, A., Yilmaz, A., & Sezen, H. (2024) · Journal of Civil Structural Health Monitoring · doi:10.1007/s13349-023-00720-6 · Cited by 26
Bai, Y., Sezen, H., Yilmaz, A., & Qin, R. (2023) · Advances in Bridge Engineering · doi:10.1186/s43251-023-00105-1 · Cited by 19
Metadata
- Authors
- Yoon, H., Shin, J., & Spencer, B. F.
- Venue
- Computer-Aided Civil and Infrastructure Engineering
- Publisher
- Elsevier BV
- Published
- 2017-12-12
- Volume
- 33
- Issue
- 3
- Pages
- 183-192
- ISSN
- 1093-9687 (ISSN-L)
- 1467-8667
- OpenAlex
- W2774494272
- Cited by
- 265
- References
- 46
- FWCI
- 13.98
- Type
- journal article
- Language
- en
- Open access
- hybrid
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