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Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
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Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
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Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring

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Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring
Journal Article

Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring

2025
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Overview
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.