Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
Unmanned aerial vehicle (UAV) vision-based sensing has become an emerging technology for structural health monitoring (SHM) and post-disaster damage assessment of civil infrastructure. This article proposes a framework for monitoring structural displacement under earthquakes by reprojecting image po...
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MDPI AG
2025-01-01
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| Online Access: | https://www.mdpi.com/1999-4893/18/2/66 |
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| author | Ruipu Ji Shokrullah Sorosh Eric Lo Tanner J. Norton John W. Driscoll Falko Kuester Andre R. Barbosa Barbara G. Simpson Tara C. Hutchinson |
| author_facet | Ruipu Ji Shokrullah Sorosh Eric Lo Tanner J. Norton John W. Driscoll Falko Kuester Andre R. Barbosa Barbara G. Simpson Tara C. Hutchinson |
| author_sort | Ruipu Ji |
| collection | DOAJ |
| description | Unmanned aerial vehicle (UAV) vision-based sensing has become an emerging technology for structural health monitoring (SHM) and post-disaster damage assessment of civil infrastructure. This article proposes a framework for monitoring structural displacement under earthquakes by reprojecting image points obtained courtesy of UAV-captured videos to the 3-D world space based on the world-to-image point correspondences. To identify optimal features in the UAV imagery, geo-reference targets with various patterns were installed on a test building specimen, which was then subjected to earthquake shaking. A feature point tracking-based algorithm for square checkerboard patterns and a Hough Transform-based algorithm for concentric circular patterns are developed to ensure reliable detection and tracking of image features. Photogrammetry techniques are applied to reconstruct the 3-D world points and extract structural displacements. The proposed methodology is validated by monitoring the displacements of a full-scale 6-story mass timber building during a series of shake table tests. Reasonable accuracy is achieved in that the overall root-mean-square errors of the tracking results are at the millimeter level compared to ground truth measurements from analog sensors. Insights on optimal features for monitoring structural dynamic response are discussed based on statistical analysis of the error characteristics for the various reference target patterns used to track the structural displacements. |
| format | Article |
| id | doaj-art-0c1a547610da4e9ba41f4fc3308ade7f |
| institution | DOAJ |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-0c1a547610da4e9ba41f4fc3308ade7f2025-08-20T03:11:19ZengMDPI AGAlgorithms1999-48932025-01-011826610.3390/a18020066Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement MonitoringRuipu Ji0Shokrullah Sorosh1Eric Lo2Tanner J. Norton3John W. Driscoll4Falko Kuester5Andre R. Barbosa6Barbara G. Simpson7Tara C. Hutchinson8Department of Structural Engineering, University of California San Diego, La Jolla, CA 92093, USADepartment of Structural Engineering, University of California San Diego, La Jolla, CA 92093, USAQualcomm Institute, University of California San Diego, La Jolla, CA 92093, USAQualcomm Institute, University of California San Diego, La Jolla, CA 92093, USAQualcomm Institute, University of California San Diego, La Jolla, CA 92093, USADepartment of Structural Engineering, University of California San Diego, La Jolla, CA 92093, USASchool of Civil and Construction Engineering, Oregon State University, Corvallis, OR 97331, USADepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USADepartment of Structural Engineering, University of California San Diego, La Jolla, CA 92093, USAUnmanned aerial vehicle (UAV) vision-based sensing has become an emerging technology for structural health monitoring (SHM) and post-disaster damage assessment of civil infrastructure. This article proposes a framework for monitoring structural displacement under earthquakes by reprojecting image points obtained courtesy of UAV-captured videos to the 3-D world space based on the world-to-image point correspondences. To identify optimal features in the UAV imagery, geo-reference targets with various patterns were installed on a test building specimen, which was then subjected to earthquake shaking. A feature point tracking-based algorithm for square checkerboard patterns and a Hough Transform-based algorithm for concentric circular patterns are developed to ensure reliable detection and tracking of image features. Photogrammetry techniques are applied to reconstruct the 3-D world points and extract structural displacements. The proposed methodology is validated by monitoring the displacements of a full-scale 6-story mass timber building during a series of shake table tests. Reasonable accuracy is achieved in that the overall root-mean-square errors of the tracking results are at the millimeter level compared to ground truth measurements from analog sensors. Insights on optimal features for monitoring structural dynamic response are discussed based on statistical analysis of the error characteristics for the various reference target patterns used to track the structural displacements.https://www.mdpi.com/1999-4893/18/2/66unmanned aerial vehicle (UAV)vision-based sensingearthquaketarget trackingworld point reconstructionstructural displacement monitoring |
| spellingShingle | Ruipu Ji Shokrullah Sorosh Eric Lo Tanner J. Norton John W. Driscoll Falko Kuester Andre R. Barbosa Barbara G. Simpson Tara C. Hutchinson Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring Algorithms unmanned aerial vehicle (UAV) vision-based sensing earthquake target tracking world point reconstruction structural displacement monitoring |
| title | Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring |
| title_full | Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring |
| title_fullStr | Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring |
| title_full_unstemmed | Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring |
| title_short | Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring |
| title_sort | application framework and optimal features for uav based earthquake induced structural displacement monitoring |
| topic | unmanned aerial vehicle (UAV) vision-based sensing earthquake target tracking world point reconstruction structural displacement monitoring |
| url | https://www.mdpi.com/1999-4893/18/2/66 |
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