Details
| Original language | English |
|---|---|
| Title of host publication | Model Validation and Uncertainty Quantification, Volume 3 |
| Subtitle of host publication | Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014 |
| Pages | 161-170 |
| Number of pages | 10 |
| Publication status | Published - 17 Mar 2014 |
| Event | 32nd IMAC Conference and Exposition on Structural Dynamics, 2014 - Orlando, FL, United States Duration: 3 Feb 2014 → 6 Feb 2014 |
Publication series
| Name | Conference Proceedings of the Society for Experimental Mechanics Series |
|---|---|
| Volume | 3 |
| ISSN (Print) | 2191-5644 |
| ISSN (electronic) | 2191-5652 |
Abstract
Modal characteristics including modal frequency, modal damping and mode shape are important structural parameters widely used in the design and analysis of structures. For example, modal parameters are valuable for calculating the dynamic response and capacity of a structure, updating finite element models and validating design assumptions. With the assistance of a vibration-based structural monitoring system, modal characteristics of an operational structure can be extracted in an autonomous fashion using output-onlymodal analysis techniques. If monitored over long periods of time, the modal properties of a structure can be tracked to determine the dependence between modal properties and other parameters such as environmental and load parameters. In this paper, modal parameters are autonomously extracted from 1 year’s worth of response data collected by the long-term structural monitoring system installed on the New Carquinez Bridge, a long-span suspension bridge constructed in 2003 in a seismic region of California. Two methods of parameter extraction are adopted using stochastic subspace identification: knowledge-based extraction and triangulation-based extraction. Statistical studies are performed on the extracted bridge modal parameters to quantify their distributions and to model their relationships with environment parameters.
Keywords
- Automated modal parameter extraction, Environmental impact, Modal analysis, Statistical analysis, Structural monitoring system
ASJC Scopus subject areas
- Engineering(all)
- General Engineering
- Engineering(all)
- Computational Mechanics
- Engineering(all)
- Mechanical Engineering
Cite this
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Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014. 2014. p. 161-170 (Conference Proceedings of the Society for Experimental Mechanics Series; Vol. 3).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Automated modal parameter extraction and statistical analysis of the new Carquinez bridge response to ambient excitations
AU - Zhang, Yilan
AU - Häckell, Moritz
AU - Lynch, Jerome P.
AU - Rolfes, Raimund
N1 - Funding information: The authors would like to gratefully acknowledge the generous support offered by the U.S. Department of Commerce, National Institute of Standards and Technology (NIST) Technology Innovation Program (TIP) under Cooperative Agreement Number 70NANB9H9008. Additional support was provided by the University of Michigan and the California Department of Transportation (Caltrans). On site assistance with sensor installation on the New Carquinez Bridge by Caltrans personnel, especially Mr. Edward Thometz, are also greatly appreciated.
PY - 2014/3/17
Y1 - 2014/3/17
N2 - Modal characteristics including modal frequency, modal damping and mode shape are important structural parameters widely used in the design and analysis of structures. For example, modal parameters are valuable for calculating the dynamic response and capacity of a structure, updating finite element models and validating design assumptions. With the assistance of a vibration-based structural monitoring system, modal characteristics of an operational structure can be extracted in an autonomous fashion using output-onlymodal analysis techniques. If monitored over long periods of time, the modal properties of a structure can be tracked to determine the dependence between modal properties and other parameters such as environmental and load parameters. In this paper, modal parameters are autonomously extracted from 1 year’s worth of response data collected by the long-term structural monitoring system installed on the New Carquinez Bridge, a long-span suspension bridge constructed in 2003 in a seismic region of California. Two methods of parameter extraction are adopted using stochastic subspace identification: knowledge-based extraction and triangulation-based extraction. Statistical studies are performed on the extracted bridge modal parameters to quantify their distributions and to model their relationships with environment parameters.
AB - Modal characteristics including modal frequency, modal damping and mode shape are important structural parameters widely used in the design and analysis of structures. For example, modal parameters are valuable for calculating the dynamic response and capacity of a structure, updating finite element models and validating design assumptions. With the assistance of a vibration-based structural monitoring system, modal characteristics of an operational structure can be extracted in an autonomous fashion using output-onlymodal analysis techniques. If monitored over long periods of time, the modal properties of a structure can be tracked to determine the dependence between modal properties and other parameters such as environmental and load parameters. In this paper, modal parameters are autonomously extracted from 1 year’s worth of response data collected by the long-term structural monitoring system installed on the New Carquinez Bridge, a long-span suspension bridge constructed in 2003 in a seismic region of California. Two methods of parameter extraction are adopted using stochastic subspace identification: knowledge-based extraction and triangulation-based extraction. Statistical studies are performed on the extracted bridge modal parameters to quantify their distributions and to model their relationships with environment parameters.
KW - Automated modal parameter extraction
KW - Environmental impact
KW - Modal analysis
KW - Statistical analysis
KW - Structural monitoring system
UR - http://www.scopus.com/inward/record.url?scp=84988702947&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-04552-8_15
DO - 10.1007/978-3-319-04552-8_15
M3 - Conference contribution
AN - SCOPUS:84988702947
SN - 9783319007670
T3 - Conference Proceedings of the Society for Experimental Mechanics Series
SP - 161
EP - 170
BT - Model Validation and Uncertainty Quantification, Volume 3
T2 - 32nd IMAC Conference and Exposition on Structural Dynamics, 2014
Y2 - 3 February 2014 through 6 February 2014
ER -