Structural state estimation of earthquake-damaged building structures by using UAV photogrammetry and point cloud segmentation
Structural state estimation of earthquake-damaged building structures by using UAV photogrammetry and point cloud segmentation
复制标题
利用无人机摄影测量和点云分割对地震受损建筑结构进行结构状态估计
DOI：
10.1016/j.measurement.2022.111858
复制
发表时间：
2022-09-08
期刊：
影响因子：
5.6
通讯作者：
Zhu, Hongtao
中科院分区：
文献类型：
--
作者：
Yu, Runze;Li, Peizhen;Zhu, Hongtao
Post-earthquake rapid structural assessment has been a widely recognized and valuable inspection need, which can accelerate community recovery and contribute to seismic resilience. Nowadays, three-dimensional point cloud models can be collected quickly using unmanned aerial vehicles (UAVs) for building structures. Regarding post-event rapid inspection, timely processing and informative interpretation of field data sets may still be a significant challenge, while limited attempts have been made to automatically extract geometrical features of point cloud models for estimating full-field deformation states of seismic-damaged structures. This study pro-poses a point cloud-based structural component segmentation approach to realize structural inclination and residual drift estimation at both system-level and story-level. Two real-world multi-story structures are illus-trated to validate the segmentation and estimation performance of the proposed method by employing wall and column inclination and full-field residual drift distribution. The results demonstrate that the developed approach can segment the target components and present high-precision deformation estimates.
