Long-term monitoring of structures through point cloud analysis

Bahman Jafari; Ali Khaloo; David Lattanzi

doi:10.1117/12.2217586

1 April 2016 Long-term monitoring of structures through point cloud analysis

Bahman Jafari, Ali Khaloo, David Lattanzi

Proceedings Volume 9805, Health Monitoring of Structural and Biological Systems 2016; 98052K (2016) https://doi.org/10.1117/12.2217586
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2016, Las Vegas, Nevada, United States

Abstract

Modern remote sensing technologies have enabled the creation of high-resolution 3D point clouds of infrastructure systems. In particular, photogrammetric reconstructions using Dense-Structure-from-Motion algorithm can now yield point clouds with the necessary resolution to capture small-strain displacements. By tracking changes in these point clouds over time, displacements can be measured, leading to strain and stress estimates for long-term structural evaluations. This study determines the accuracy of a comparative point cloud analysis technique for measuring deflections in high-resolution point clouds of structural elements. Utilizing a combination of a recently developed point cloud generation process and localized nearest-neighbors cloud comparisons, the analytical technique is designed for long-term field scenarios and requires no artificial tracking, targets, and camera calibrations. A series of flexural laboratory experiments were performed in order to test the approach. The results indicate sub-millimeter accuracy in measuring the vertical deflection, making it suitable for the small-displacement analysis of a variety of large-scale infrastructure systems. Ongoing work seeks to extend this technique for comparison with as-built and finite element models.

Citation Download Citation

Bahman Jafari, Ali Khaloo, and David Lattanzi "Long-term monitoring of structures through point cloud analysis", Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 98052K (1 April 2016); https://doi.org/10.1117/12.2217586

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