skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

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

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 basedmore » 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. Furthermore, 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.« less

Authors:
 [1];  [2];  [3];  [3];  [4];  [1];  [1];  [1]
+ Show Author Affiliations
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  3. Missouri Univ. of Science and Technology, Rolla, MO (United States)
  4. Rice Univ., Houston, TX (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1335628
Report Number(s):
LA-UR-16-21151
Journal ID: ISSN 0022-460X
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Sound and Vibration
Additional Journal Information:
Journal Name: Journal of Sound and Vibration; Journal ID: ISSN 0022-460X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; operational modal analysis; full field measurement; video processing; Sub-Nyquist sampling; signal aliasing; blind source separation

Citation Formats

Yang, Yongchao, Dorn, Charles, Mancini, Tyler, Talken, Zachary, Nagarajaiah, Satish, Kenyon, Garrett, Farrar, Charles Reed, and Mascarenas, David Dennis Lee. Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements. United States: N. p., 2016. Web. doi:10.1016/j.jsv.2016.11.034.
Copy to clipboard
Yang, Yongchao, Dorn, Charles, Mancini, Tyler, Talken, Zachary, Nagarajaiah, Satish, Kenyon, Garrett, Farrar, Charles Reed, & Mascarenas, David Dennis Lee. Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements. United States. https://doi.org/10.1016/j.jsv.2016.11.034
Copy to clipboard
Yang, Yongchao, Dorn, Charles, Mancini, Tyler, Talken, Zachary, Nagarajaiah, Satish, Kenyon, Garrett, Farrar, Charles Reed, and Mascarenas, David Dennis Lee. Mon . "Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements". United States. https://doi.org/10.1016/j.jsv.2016.11.034. https://www.osti.gov/servlets/purl/1335628.
Copy to clipboard
@article{osti_1335628,
title = {Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements},
author = {Yang, Yongchao and Dorn, Charles and Mancini, Tyler and Talken, Zachary and Nagarajaiah, Satish and Kenyon, Garrett and Farrar, Charles Reed and Mascarenas, David Dennis Lee},
abstractNote = {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. Furthermore, 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.},
doi = {10.1016/j.jsv.2016.11.034},
url = {https://www.osti.gov/biblio/1335628}, journal = {Journal of Sound and Vibration},
issn = {0022-460X},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {12}
}
Copy to clipboard
Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1016/j.jsv.2016.11.034
Copyright Statement
Other availability
Search WorldCat Search WorldCat to find libraries that may hold this journal
Citation Metrics:
Cited by: 4 works
Citation information provided by
Web of Science
Save / Share:
Export Metadata
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.

Works referencing / citing this record:

Video-based multiscale identification approach for tower vibration of a cable-stayed bridge model under earthquake ground motions
journal, January 2019

A literature review of next-generation smart sensing technology in structural health monitoring
journal, January 2019

Estimation of full‐field dynamic strains from digital video measurements of output‐only beam structures by video motion processing and modal superposition
journal, July 2019

Thermal strain extraction methodologies for bridge structural condition assessment
journal, September 2018

Operational Deflection Shape Extraction from Broadband Events of an Aircraft Component Using 3D-DIC in Magnified Images
journal, April 2019

A framework for the identification of full-field structural dynamics using sequences of images in the presence of non-ideal operating conditions
journal, February 2018

Marker-free monitoring of the grandstand structures and modal identification using computer vision methods
journal, September 2018

Photogrammetry-based structural damage detection by tracking a visible laser line
journal, April 2019

The promise of implementing machine learning in earthquake engineering: A state-of-the-art review
journal, June 2020

A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking
journal, March 2019

    [ × clear filter / sort ]

    Similar records in OSTI.GOV collections: