Enhanced measurements of structural inter-story drift responses in shaking table tests

Abstract

Accurate measurements of inter-story drift responses are critical in shaking table tests. This paper compared three commonly-used approaches of inter-story drift measurement, and developed the techniques for enhanced measurement. This study proposed a novel arrangement of displacement meters along with the associated data correction method. By setting the overhanging steel arms above and beneath a floor slab at the same position, the suggested approach could remove the influence of floor slab rotation and thus improve the accuracy of inter-story drift measurement. In addition, a novel computer vision-based target tracking approach based on a super-resolution (SR) image reconstruction technique was developed. This advanced deep learning-based SR method can transform blurry, low-resolution images into sharp, high-resolution ones for precise target tracking. The accuracy of these developed inter-story measurement approaches was evaluated through a case study of shaking table tests of a large-scale three-story reinforced concrete (RC) building structure. The results indicated that the novel arrangement of displacement meters and associated data correction method successfully eliminated the influence of floor slab rotation, which could result in an error of approximately 20% in the inter-story drift measurement if left uncorrected. The novel SR method overcame the limitation of video resolution and achieved a stable sub-pixel measurement result. In the case of seismic loading, the SR method improved the signal-to-noise ratio of the drift measurement by 68%, and reduced the root mean square error by 63%, compared with the conventional template matching technique. The modal parameters of the test structure were accurately identified from the small-magnitude displacement data of white noise vibration responses measured using the SR method.