Full-field Imaging and Modeling of Structural Dynamics with Digital Video Cameras

Abstract

Structures usually have complex geometries, material properties, and boundary conditions, and exhibit spatially local, temporally transient, dynamic behaviors. High spatial and temporal resolution vibration measurements and modeling are thus required for high-fidelity characterization, analysis, and prediction of the structure’s dynamic phenomena. For example, high spatial density mode shapes are needed for accurate vibration-based damage localization. Also, higher order (frequency) vibration modes typically contain local structural features that are essential for high-fidelity modeling of the structure’s dynamics. In addition, while it is possible to build a highly-refined mathematical model (e.g., a finite element model) of the structure, it needs to be experimentally validated and updated with high-resolution vibration measurements. However, it is a significant challenge to obtain high-resolution vibration measurements using traditional techniques. For example, the widely-used accelerometers and straingauge sensors can only provide low spatial resolution measurements. Laser vibrometers provide high-resolution measurements, but are expensive and make sequential measurements that are time-consuming. On the other hand, photogrammetry as an alternative non-contact optical measurement method uses passive white-light imaging of digital video cameras that are relatively low-cost, agile, and provide non-contact, high spatial resolution, simultaneous, measurements where every pixel effectively becomes a measurement point on the structure. A new framework is developed for the blind extraction and realistic visualization of the full-field, high-resolution, dynamics behaviors of an operating structure from only its digital video measurements, possibly temporally-aliased (sub-Nyquist), using video motion manipulation and unsupervised machine learning techniques. This highresolution, full-field structural dynamics characterization framework addresses a variety of problems that traditionally have been challenging, including the ability to localize minute, non-visible, structural damage at a pixel resolution. Laboratory experiments on bench-scale building structures, cantilever beams, and stay cables are demonstrated.