Point-wise deformation analysis of 3D models for structural health monitoring
-
A new point-wise deformation analysis was developed to automatically measure deflection in 3D models of structural systems
-
A direct 3D geometric comparison was implemented to accurately detect and quantify changes
-
Utilizing a statistical approach to improve the robustness of the algorithms in presence of outliers/noise
-
Using advanced distance metrics to take into account variability in local point density, roughness, and registration uncertainty
-
The findings indicate measurement accuracy of 0.2 mm, making the algorithm suitable for structural condition assessment
Related Publications
-
Jafari, B., Khaloo, A., and Lattanzi, D. (2017) "Deformation Tracking in 3D Point Clouds via Statistical Sampling of Direct Cloud-to-Cloud Distances," Journal of Nondestructive Evaluation, 36(4), 65.
-
Jafari, B., Khaloo, A., and Lattanzi, D. (2017) "Tracking Structural Deformations via Automated Sample-Based Point Cloud Analysis," ASCE International Workshop on Computing in Civil Engineering (IWCCE), Seattle, WA, June 2017.
-
Jafari, B., Khaloo, A., and Lattanzi, D. (2016) "Long-term Monitoring of Structures through 3D Point Cloud Analysis," SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring pp. 98052K-98052K. International Society for Optics and Photonics, Las Vegas, NV, March 2016.
U.S Forest Service Grant No. 15-CS-11100100-015