Video-based multiscale identification approach for tower vibration of a cable-stayed bridge model under earthquake ground motions

Abstract

A camera can theoretically capture visual information of all target surfaces within its field of view. This capability allows a camera to act as a sensor for determining motion or deformation of targets at appropriate distances. Considering that there are so many cameras in public society (including cameras in smartphones) that can record the vibration of structures in an earthquake, this capability will be very helpful for assessing structural seismic damage post-earthquake. To this end, this paper proposes a two-step combination of the SCF (support correlation filters) algorithm with the KLT (Kanade-Lucas-Tomasi) algorithm for displacement identification of cable-stayed bridges from video with higher accuracy over SCF only and higher robustness over KLT only. The SCF algorithm can robustly and quickly track the target in the video, and the KLT algorithm can accurately track the pixel locations of targets. The shaking table test of a scale cable-stayed bridge model was conducted, and the vibration of the tower was recorded by a camera. The linear and nonlinear displacement responses of the tower under different earthquake ground motions were identified. The accuracy of the identified displacement response was validated through comparison with measurements from laser displacement transducers.