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Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Yang, Yongchao and Dorn, Charles and Mancini, Tyler and Talken, Zachary and Nagarajaiah, Satish and Kenyon, Garrett and Farrar, Charles and Mascareñas, David (2017) Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements. Journal of Sound and Vibration , 390 . pp. 232-256. ISSN 0022-460X. https://resolver.caltech.edu/CaltechAUTHORS:20170216-101458562

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Abstract

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially 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 subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1016/j.jsv.2016.11.034DOIArticle
http://www.sciencedirect.com/science/article/pii/S0022460X16306897PublisherArticle
Additional Information:© 2017 Elsevier Ltd. Received 29 February 2016, Revised 19 November 2016, Accepted 24 November 2016, Available online 5 December 2016.
Subject Keywords:Operational modal analysis; Full field measurement; Video processing; Sub-Nyquist sampling; Signal aliasing; Blind source separation
Record Number:CaltechAUTHORS:20170216-101458562
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170216-101458562
Official Citation:Yongchao Yang, Charles Dorn, Tyler Mancini, Zachary Talken, Satish Nagarajaiah, Garrett Kenyon, Charles Farrar, David Mascareñas, Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements, Journal of Sound and Vibration, Volume 390, 3 March 2017, Pages 232-256, ISSN 0022-460X, http://dx.doi.org/10.1016/j.jsv.2016.11.034. (http://www.sciencedirect.com/science/article/pii/S0022460X16306897)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:74366
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 Feb 2017 18:20
Last Modified:03 Oct 2019 16:37

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