Ambient Vibration Analysis with Subspace Methods and Automated Mode Selection: Case Studies
Publication: Journal of Structural Engineering
Volume 134, Issue 6
Abstract
This study presents an investigation of the performance of subspace techniques for modal identification using ambient vibration measurements. Several models and structures characterized by increasing degrees of complexity are investigated to assess the potential benefits of stochastic subspace identification algorithms, and the difficulties that might be experienced during a modal identification analysis. The case studies include a simple three-degree-of-freedom (3 DOF) mass-spring-dashpot model, the 120 DOF finite element model, as well as the physical laboratory model of a small scale steel frame, and a long span suspension bridge. Stabilization diagram and clustering analysis approaches are adopted for spurious mode rejection, and the latter is found to be promising for automating the mode selection process. The experiences with experimental data reveal that some preconditioning tools are quite helpful in order to properly focus on the structural modes of interest, and that preconditioning improves the performance of the subspace methods. On the whole, the approaches investigated in this study are found to perform quite satisfactorily for operational modal analysis of engineering structures.
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Acknowledgments
The writers would like to thank Professor Sami F. Masri, University of Southern California, for providing the acceleration data from the Vincent Thomas bridge; and Professor Juan M. Caicedo, University of South Carolina, for both providing detailed information about the ASCE SHM benchmark problem and giving permission to use the photos on the Web site. This study was, in part, sponsored by the B.U. Research Fund under Project Code 05A402, whose support is greatly appreciated. The economic support provided to Bilge Alıcıoğlu by the Turkish Scientific and Technical Research Council (TÜBİTAK) under Program Code UNSPECIFIED2210 is greatly acknowledged. The writers also would like to thank their anonymous reviewer for the very detailed commentary that helped to improve their presentation.
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© 2008 ASCE.
History
Received: Sep 22, 2006
Accepted: Sep 18, 2007
Published online: Jun 1, 2008
Published in print: Jun 2008
Notes
Note. Associate Editor: Vinay Kumar Gupta
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