Start Date

2016 12:00 AM

Description

Structures with complex geometries, material properties, and boundary conditions, 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 resolution mode shapes are needed for accurate vibration-based damage localization. Also, higher order vibration modes typically contain local structural features that are essential for high-fidelity dynamic modeling of the structure. 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, accelerometers and strain-gauge sensors 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, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. A new framework is first developed for the blind extraction and visualization of the full-field, high- resolution, dynamic parameters of an operating (output-only) structure from the digital video measurements using video motion manipulation and unsupervised machine learning techniques. See Fig. 1 for the experimental results of a vibrating cantilever beam and more video demos at http://www.lanl.gov/projects/national-security-education-center/engineering/research-projects/blind-modal-id.php.

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

Full-field Structural Dynamics by Video Motion Manipulations

Structures with complex geometries, material properties, and boundary conditions, 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 resolution mode shapes are needed for accurate vibration-based damage localization. Also, higher order vibration modes typically contain local structural features that are essential for high-fidelity dynamic modeling of the structure. 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, accelerometers and strain-gauge sensors 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, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. A new framework is first developed for the blind extraction and visualization of the full-field, high- resolution, dynamic parameters of an operating (output-only) structure from the digital video measurements using video motion manipulation and unsupervised machine learning techniques. See Fig. 1 for the experimental results of a vibrating cantilever beam and more video demos at http://www.lanl.gov/projects/national-security-education-center/engineering/research-projects/blind-modal-id.php.