Novel Sensing Approaches for Structural Deformation Monitoring and 3D Measurements

Nowadays, laser vision systems have allowed the development of different applications such as reverse engineering, manufacturing, navigation systems and, structural health monitoring (SHM). However, most of the machine vision systems for structural behavior analysis have restricted field of view, consume high levels of computational resources for image processing and require special illumination conditions to achieve lower error rates. Therefore, the purpose of this paper is to present a technical vision system (TVS) for structural behavior analysis using dynamic laser triangulation and k- Nearest Neighbor (k-NN) machine learning regression algorithm. The proposed vision system was tested in order to demonstrate the practicality of it, different deformations and displacements were analyzed over real structures in controlled laboratory conditions to assure the reproducibility of the experimentation. The TVS prototype proved to be a reliable option on SHM tasks, presenting balance between precision and operating ranges, without the issues aforementioned.