Experimental image and range scanner datasets fusion in SHM for displacement detection

Abstract

Optical images and signals can be used to detect displacement in civil engineering structures. This paper presents a technical experimentation of a vision-based technology and artificial intelligence algorithms methodology for structural health monitoring of new and aging structures, by a noncontact and nondestructive system. The experimental study emphasis is on the outdoor urban environment, by the detection of spatial coordinate displacement on the structures, in order to perform a damage assessment. Also, the experimental study contains both theoretical and experimental aspects of the fusion of image and range scanner datasets created using intelligent algorithms. A camera and an optical scanning system were used to generate high resolution and quality images for 2D imaging, and 3D accuracy range data from optoelectronic sensor signals. Scans at a specific area of an engineering structure were performed to measure spatial coordinates displacements, successfully verifying the effectiveness and the robustness of the proposed non-contact and non-destructive monitoring approach.