Performance Assessment of a High-Speed Railway Bridge through Operational Modal Analysis
Publication: Journal of Performance of Constructed Facilities
Volume 35, Issue 6
Abstract
Modal parameters are widely recognized as valuable indicators for evaluating the performance of railway bridges in structural health monitoring. A major challenge in the mode-based performance assessment is to obtain modal parameters reliably because operational factors may cause significant identification errors or reduce modal identifiability. To reduce the operational effects on mode-based assessment, vibration responses are divided according to excitation types, and then two subspace identification techniques are developed for identifying modal parameters of the railway bridge. If the bridge is only acted on by the ambient excitation, the stochastic subspace identification (SSI) is taken in this paper. If the bridge is mainly acted on by the train excitation, modal parameters are difficult to identify due to the regularly spaced and highly energetic axle loads. In this case, a deterministic stochastic subspace identification (DSSI) method is developed for improving the modal identifiability of the railway bridge under train action. The monitoring responses of a high-speed railway bridge are analyzed in this paper to track long-term modal parameters. Besides, variations of modal parameters that are related to environmental factors, operational conditions, modal orders, vibration directions, and member types are extensively compared. The results show that modal parameters can be well-identified even though the nonwhite noise excitation exists, and the performance assessment can be well achieved through determining the optimal modal parameters.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 52050050, 51978128, and 51778105) and the LiaoNing Revitalization Talents Program (Grant No. XLYC1802035).
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Published In
Journal of Performance of Constructed Facilities
Volume 35 • Issue 6 • December 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Mar 31, 2021
Accepted: Aug 13, 2021
Published online: Sep 23, 2021
Published in print: Dec 1, 2021
Discussion open until: Feb 23, 2022
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