Structural Response Estimation Based on Kalman Filtering with Known Frequency Component of External Excitation and Multitype Measurements for Beam-Type Structure
Publication: Journal of Aerospace Engineering
Volume 34, Issue 6
Abstract
Structural health monitoring can be performed through long-term monitoring of key structural parts to obtain the structural response information of civil engineering structures in real service environments. This enables the provision of on-site measurement data for in-depth understanding of the structural performance and verifying design parameters. To address the issue of limited information from sensors, this paper proposes a structural response estimation method based on Kalman filtering and multitype measurements for beam-type structures. Starting from the structural motion equation, an internal structural model equation by extracting the modal external excitation frequency component and the structure’s inherent characteristics are used for structural response estimation. The frequency component of external excitation should be known in the proposed method. Then, based on the multitype measurements, the system and observation noises are considered, and a structural response estimation equation based on Kalman filtering is formulated. Finally, particle swarm optimization is applied to optimize the Kalman error parameter values and achieve multilocation and multitype structural response estimation based on the multitype measurements. The effectiveness and feasibility of the proposed method are verified via experimental analysis of the Binzhou Yellow River Bridge mode, where only pedestrian loading is used.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (NSFC) (Grant Nos. 51978214, 51678201, and 51878226), the National Major Scientific Research Instrument Development Program of China (Grant No. 51827811), and the Shenzhen Knowledge Innovation Program (KCXFZ202002011010039). The authors would also like to thank all the members of the research group who implemented the entire structural health monitoring system, collected information, and provided clear figures.
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Published In
Journal of Aerospace Engineering
Volume 34 • Issue 6 • November 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: May 30, 2020
Accepted: Apr 23, 2021
Published online: Jul 30, 2021
Published in print: Nov 1, 2021
Discussion open until: Dec 30, 2021
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