Long-Term Modal Analysis of Wireless Structural Monitoring Data from a Suspension Bridge under Varying Environmental and Operational Conditions: System Design and Automated Modal Analysis
Publication: Journal of Engineering Mechanics
Volume 143, Issue 4
Abstract
Structural monitoring systems installed on cable-supported bridges have the potential to generate large data repositories from which a deeper understanding of bridge behavior can be obtained. The core focus of this study is the use of response and environmental data collected by a permanent wireless monitoring system operating on the New Carquinez Bridge (Vallejo, California) since 2010. Given the large amount of data available, the study proposes an automated stochastic subspace identification approach for the extraction of bridge modal properties. The study fits logistic distributions to the extracted modal frequencies and modal damping ratios to provide statistical models for these important bridge properties. Low levels of modal damping well below 0.8% are reported for the majority of structural modes. Bridge modal properties exhibit sensitivity to the environmental and operational conditions of the bridge. Ridge regression and Gaussian process regression (GPR) are used to model the dependency of modal frequency on bridge environmental and operational conditions. The GPR models are shown capable of accurately modeling the relationship between modal frequency and bridge environmental and operational conditions.
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Acknowledgments
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 California Department of Transportation (Caltrans); the help provided by Li Hong Sheng, Patrick Hipley, Ed Thometz, and Mark Efe was invaluable to the execution of the monitoring study. Additional support was provided by the National Science Foundation Grant Numbers CCF-0910765, CMMI-1362513, CMMI-1436631, and ECCS-1446521.
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Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 143 • Issue 4 • April 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Jun 20, 2016
Accepted: Sep 19, 2016
Published online: Nov 28, 2016
Published in print: Apr 1, 2017
Discussion open until: Apr 28, 2017
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