Damage detection based on accelerometers and computer vision measurements of moving load-induced structural responses

Abstract

Damage identification is an important and challenging issue in structural health monitoring to prevent sudden structural failures. This study introduces a novel damage detection method for beams associated with the cross-correlation function of the moving load-induced full-field displacements. Firstly, through theoretical derivation, the structural responses of a single-span beam under arbitrary boundary conditions subjected to a moving concentrated force were investigated, both before and after damage occurred. The changes in structural responses due to local stiffness damage were analyzed from a theoretical perspective. Then, a method is introduced to extract high-resolution mode shapes, which represent the true state of the structure, from the computer vision-based displacements and accelerations measured at limited locations. These mode shapes were then used for full-field displacement reconstruction, and the changes in the cross-correlation function of these reconstructed displacements were employed for damage detection. The proposed method can obtain the higher-order responses compared to the traditional vision-based methods, and the displacements at the acceleration-unmeasured locations can be improved compared to the conventional data fusion method. Finally, the proposed method was validated both in numerical simulations and experimental tests on a beam model with multiple damage scenarios. The results have demonstrated the capability of the proposed method in mode shape extraction, full-field displacement reconstruction, and damage detection.