Automated Operational Modal Analysis of a Cable-Stayed Bridge
Publication: Journal of Bridge Engineering
Volume 22, Issue 12
Abstract
Automated techniques for analyzing the dynamic behavior of full-scale civil structures are becoming increasingly important for continuous structural health-monitoring applications. This paper describes an experimental study aimed at the identification of modal parameters of a full-scale cable-stayed bridge from the collected output-only vibration data without the need for any user interactions. The work focuses on the development of an automated and robust operational modal analysis (OMA) algorithm, using a multistage clustering approach. The main contribution of the work is to discuss a comprehensive case study to demonstrate the reliability of a novel criterion aimed at defining the hierarchical clustering threshold to enable the accurate identification of a complete set of modal parameters. The proposed algorithm is demonstrated to work with any parametric system identification algorithm that uses the system order n as the sole parameter. In particular, the results from the covariance-driven stochastic subspace identification (SSI-Cov) methods are presented.
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Acknowledgments
This project was funded by the New South Wales Government in Australia and was undertaken by division Data61 within the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Australia. The authors wish to express their gratitude to the Western Sydney University for provision of the support and facilities for this research work.
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Published In
Journal of Bridge Engineering
Volume 22 • Issue 12 • December 2017
Copyright
© 2017 American Society of Civil Engineers.
History
Received: Nov 30, 2016
Accepted: May 31, 2017
Published online: Sep 28, 2017
Published in print: Dec 1, 2017
Discussion open until: Feb 28, 2018
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