Structural Modal Flexibility Identification Through a Novel Mode Selection Method
Publication: Journal of Engineering Mechanics
Volume 147, Issue 3
Abstract
Flexibility is an important index in the assessment of bridge load-carrying capacity. Impact testing is an efficient and effective method to obtain the flexibility of small- and medium-span bridges. Modal parameter identification based on excitation and response data plays a key role in flexibility identification, which can obtain the modal scaling factor. As is well known, the combined deterministic-stochastic subspace identification (DSI) algorithm is one of the most popular identification methods. However, unavoidable factors often result in the appearance of spurious modes, which can affect flexibility identification. In this paper, a novel mode selection method is implemented to achieve better extraction of physical modes during the flexibility identification process. A simulated example is used to verify that the proposed method can effectively extract physical modes to obtain a flexibility matrix.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, or code generated or used during the study are available from the corresponding author by request.
Acknowledgments
This research work was jointly supported by the National Key Research and Development Program of China (Grant No. 2019YFC1511000), the National Natural Science Foundation of China (Grant Nos. 51625802, 51978128, and 51778105), the LiaoNing Revitalization Talents Program (Grant No. XLYC1802035), and the Foundation for High Level Talent Innovation Support Program of Dalian (Grant No. 2017RD03).
References
Catbas, N., H. B. Gokce, and D. M. Frangopol. 2013. “Predictive analysis by incorporating uncertainty through a family of models calibrated with structural health-monitoring data.” J. Eng. Mech. 139 (6): 712–723. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000342.
Li, P. J., Q. Xia, and J. Zhang. 2018. “Subspace flexibility identification adaptive to different types of input forces.” Int. J. Struct. Stab. Dyn. 18 (5): 1850067. https://doi.org/10.1142/S0219455418500670.
Li, P. J., Z. N. Zhang, and J. Zhang. 2019. “Simultaneously identifying displacement and strain flexibility using long-gauge fiber optic sensors.” Mech. Syst. Sig. Process. 114 (Jan): 54–67. https://doi.org/10.1016/j.ymssp.2018.05.005.
Qu, C. X., T. H. Yi, X. M. Yang, and H. N. Li. 2017. “Spurious mode distinguish by eigensystem realization algorithm with improved stabilization diagram.” Struct. Eng. Mech. 63 (6): 743–750. https://doi.org/10.12989/sem.2017.63.6.743.
Reynders, E., and G. De Roeck. 2008. “Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis.” Mech. Syst. Sig. Process. 22 (3): 617–637. https://doi.org/10.1016/j.ymssp.2007.09.004.
Ubertini, F., C. Gentile, and A. L. Materazzi. 2013. “Automated modal identification in operational conditions and its application to bridges.” Eng. Struct. 46 (Jan): 264–278. https://doi.org/10.1016/j.engstruct.2012.07.031.
Yang, D. H., T. H. Yi, and H. N. Li. 2017. “Coupled fatigue-corrosion failure analysis and performance assessment of RC bridge deck slabs.” J. Bridge Eng. 22 (10): 04017077. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001108.
Zhang, J., and F. L. Moon. 2012. “Novel structural flexibility identification in narrow frequency bands.” Smart Mater. Struct. 21 (12): 125020. https://doi.org/10.1088/0964-1726/21/12/125020.
Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 147 • Issue 3 • March 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Jul 18, 2020
Accepted: Dec 7, 2020
Published online: Jan 13, 2021
Published in print: Mar 1, 2021
Discussion open until: Jun 13, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.