000019982 001__ 19982
000019982 005__ 20170118182349.0
000019982 04107 $$aeng
000019982 046__ $$k2017-01-09
000019982 100__ $$aFarrar, Charles
000019982 24500 $$aBlind Identification of Very High Spatial-Resolution Vibration Modes of Structures From Video Camera Measurements Only

000019982 24630 $$n16.$$pProceedings of the 16th World Conference on Earthquake Engineering
000019982 260__ $$b
000019982 506__ $$arestricted
000019982 520__ $$2eng$$aModal analysis is essential for dynamic modeling and analysis of seismic excited structures. Experimental or operational modal analysis traditionally requires physically-attached wired or wireless sensors for vibration measurement of structures. The sensor instrumentation could result in mass-loading on lightweight structures, and is costly and time-consuming for large civil structures, especially for longterm applications (e.g., structural health monitoring and seismic dynamic analysis) that require significant maintenance and labors for cabling (wired) or energy supply (wireless). In addition, these sensors are discrete point-wise, providing low spatial sensing resolution that is hardly sufficient for larger structures. Non-contact optical methods such as scanning laser vibrometers provide high-resolution sensing capacity without the mass loading effect; however, they operate sequential measurement that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and modal analysis, such as the digital image correlation (DIC) and the point-tracking techniques. However, they typically require speckle pattern or high-contrast markers instrumented on the surface of structures, which raises the instrumentation issue when the measurement area is large or inaccessible. This work explores advanced computer vision and video processing algorithms to develop a novel video measurement and vision based output-only modal analysis method that removes the need of structural surface preparation in existing vision based methods. By manipulating the motion encoded in the video measurements only using multi-scale image decomposition and unsupervised machine learning techniques, the proposed method efficiently and accurately extract modal frequencies, very high spatial (pixel) resolution mode shapes, and damping ratios of the structure. The method is validated by laboratory experiments on bench-scale structures including a building structure and a cantilever beam. Video demos of these experimental results are on http://www.lanl.gov/projects/national-security-educationcenter/engineering/research-projects/blind-modal-id.php.

000019982 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000019982 653__ $$aOutput-only Modal Analysis; Full-field Structural Dynamics; Video Processing; Motion Magnification; Blind Source Separation;

000019982 7112_ $$a16th World Conference on Earthquake Engineering$$cSantiago (CL)$$d2017-01-09 / 2017-01-13$$gWCEE16
000019982 720__ $$aFarrar, Charles$$iKenyon, Garrett$$iTalken, Zachary$$iMancini, Tyler$$iDorn, Charles$$iYang, Yongchao$$iMascarenas, David
000019982 8560_ $$ffischerc@itam.cas.cz
000019982 8564_ $$s613238$$uhttps://invenio.itam.cas.cz/record/19982/files/4874.pdf$$yOriginal version of the author's contribution as presented on USB, paper 4874.
000019982 962__ $$r16048
000019982 980__ $$aPAPER