Vision-Based Dynamic Response Measurements of Structures by Using Smartphone Videos and Alternative Techniques

Abstract

This study aimed to measure dynamic responses of structural systems using smartphone videos and vision-based sensing processes. Two algorithms, based on template matching and feature extraction, are employed for this purpose. They were verified on the shake table experiments with single and multi-degree freedom steel specimens where their videos were captured by an ordinary smartphone during excitation. Dynamic responses such as strains at discrete sections as well as displacements, velocities, and accelerations at the floor levels of the specimens were obtained by following the signs of physical or virtual markers during the video recording. Through comprehensive experiments and one available full-scale multi-story shake table experiment in the literature, the developed vision-based algorithms were validated to be used with smartphone videos. It was also shown that regardless of the quality of the video record, substantial characteristics of a specimen or a structure could be determined reasonably by smartphone videos since the absolute mean relative differences varied between 10% to 20%.