Two camera 3D time series reconstruction of a mesh subjected to differential excitation

The present study proposes a novel bio-inspired scheme for the 3D time series reconstruction of a Mesh. The key motivation of this study is to develop a cost effective and accessible system without compromising capabilities for the fundamental understanding in complicated external stimuli-induced vibration of a Mesh. A bio-inspired algorithm traces along the strands of the mesh to match a known control point to the next keypoint until the entire surface is matched for the critical reconstruction at the first frame/timestep. The match is then disseminated to the subsequent frames steps via digital image correlation and photogrammetric methods applied to effectively recover the time series response of the dynamic surface. This study offers significant and quantitative insight into the vibration and fluctuation of the entire excited surface. A 160mm×160mm mesh fluctuation is successfully re-constructing with a sampling density of approximately 1600 points at 24 frames per second. The proof-of-concept experiment was able to detect the undulation of mesh under an in-phase and an out-of-phase excitation, which result in the reconstruction of the point cloud with a 0.38mm error, as well as the frequency and phase angle accuracy attainments of about 99.1% and 86.0%, respectively. In short, the current reconstruction scheme may provide insights into the control and response of a piezoelectric mesh.