Full-Field Mode Shape Analysis, Alignment and Averaging Across Measurements
Noncontact methods of experimentally acquiring mode shapes and associated natural frequencies eliminate errors induced by mass-weighting of the structure by sensors. Traditional data acquisition methods require costly and delicate sensors such as accelerometers and strain gauges that are time-consuming to setup on each structure needing to be analyzed. Other non-contact data acquisition tools such as Laser Doppler Vibrometers (LDVs) and Digital Image Correlation (DIC) require expensive equipment and placement of speckle patters or high-contrast markers on the structure. Digital video cameras provide a relatively low-cost and portable method to measure a structure with high spatial resolution without needing to modify the structure. Previous work identified a novel variation on Operational Modal Analysis (OMA) to identify full-field mode shapes from video data. This work develops the algorithm’s robustness, investigating effects of camera motion, structure excitation type, and background intensity gradients. Camera motion and modal over-specification are shown to cause identification of modes that do not correspond to physical deformations of the structure. Previously, video stabilization algorithms have been used to eliminate camera motion from video data. These algorithms eliminate most camera motion, but residual motion remains and is identified in additional, spurious mode shapes. When the camera motion is oscillatory, these shapes can be correlated in the frequency domain to the spectrum seen by an accelerometer placed on the camera itself. Averaging techniques are implemented to improve mode shape quality and identify structural and camera modes from spurious modes identified from modal over-specification. When robustly understood, identification of full-field mode shapes and properties can cheaply and efficiently advance structural health monitoring, model verification and updating, change detection, load identification, and other fields of structural dynamics.
KeywordsFull-field Blind-source separation Video Registration
Los Alamos National Laboratory is operated by Los Alamos National Security LLC, for the National Nuclear Security Administration of the U.S. Department of Energy, under DOE Contract DE-AC52-06NA25396.
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