Knowledge of the camera motion is important in the applications of structural dynamic response measurement using a vision‐based approach because in most of the field measurements, such motion can be non‐trivial and the accuracy of dynamic response measurements is strongly affected by the camera motion. This paper presents a new framework for camera motion estimation and vision‐based displacement measurement, which greatly lowers the barriers to the application of generally positioned cameras from strictly stationary cameras. The contributions in this paper are twofold. First, camera motion as well as reconstructed structural displacement are calculated based on reference planar structures visible in a given scene. In this case, a homography is more effective at describing view changes and planar geometric constraints can be incorporated early in the reconstruction process, thereby improving the quality and effectiveness of the estimates. The second contribution is that the homography of the planar structure is estimated by a newly proposed tracking algorithm that combines RANSAC algorithm and Efficient Second‐order Minimization (ESM) technique, which refines the final estimates to sub‐pixel accuracy and avoids tracking drift and non‐smoothness effectively. Experimental results indicate that the quality of the camera motion estimation and displacement reconstruction can be significantly improved by the judgmatical use of the proposed algorithm for planar structure homography estimation. Furthermore, nonlinear structural system identification is carried out to additionally verify the proposed algorithm using unscented Kalman filter.

We propose a new flexible technique for accurate vision-based seismic displacement measurement of building structures via a single non-stationary camera with any perspective view. No a priori information about the camera’s parameters or only partial knowledge of the internal camera parameters is required, and geometric constraints in the world coordinate system are employed for projective rectification in this research. Whereas most projective rectifications are conducted by specifying the positions of four or more fixed reference points, our method adopts a stratified approach to partially determine the projective transformation from line-based geometric relationships on the world plane. Since line features are natural and plentiful in a man-made architectural building environment, robust estimation techniques for automatic projective/affine distortion removal can be applied in a more practical way. Both simulations and real-recorded data were used to verify the effectiveness and robustness of the proposed method. We hope that the proposed method could advance the consumer-grade camera system for vision-based structural measurement one more step, from laboratory environments to real-world structural health monitoring systems.

This study introduces the first application of nonlinear signal‐based control (NSBC) to shake table experiments with sliding masses. NSBC utilising a nonlinear signal was specifically developed for nonlinear system control. In shake table experiments with a steel structure, it realised a seismic acceleration record on the table with near 100% accuracy even when the structure displayed nonlinear characteristics due to yielding of its components. Regarding the severity, sliding is stronger than yielding because of the rapid shifts of stick and slip states. Sliding is utilised for structural damage mitigation in seismic isolation systems, which are prominent devices in earthquake engineering. However, when sliding occurs on a shake table, it significantly jeopardises the table control. Thus, this study investigates the performance of NSBC to shake table experiments involving the phenomenon. First, this study examines the effectiveness of NSBC via numerical simulations on a shake table with a sliding interface, demonstrated by the Karnopp model, with a friction coefficient of 0.2. Subsequently, a linear model is designed based on the stability analysis of NSBC to assess stability margins obtained from different models. Experiments are performed by placing masses weighing approximately twice the table weight on sliding interfaces with friction coefficients of 0.2–0.4. In these experiments, NSBC with a reasonable linear model design realised expected acceleration records with sufficiently high accuracies, whereas inversion‐based control failed. This study verifies the effectiveness of NSBC for shake table experiments with sliding masses.