期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 177, 期 -, 页码 -出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2022.109155
关键词
Indirect frequency identification; Frequency domain analysis; Three-dimensional vehicle-bridge interaction; Three-dimensional road roughness; Cross-correlation function
资金
- Chinese State Key Laboratory for Disaster Reduction in Civil Engineering [SLDRCE19-A-11]
- National Natural Science Foundation of China [51978508]
- Science and Technology Cooperation Project of Shanghai Qizhi Institute [SYXF0120020109]
This study conducts a 3D simulation of vehicle-bridge interaction and proposes a novel frequency-domain method to identify bridge natural frequencies. The proposed method has the potential to fast inspect large quantities of bridges, making it valuable for indirect bridge structural identification.
Indirect identification of bridge frequencies, which refers to identifying bridge frequencies from the dynamic response of a vehicle moving on the bridge, has the potential to fast inspect bridges in large quantities. Accurate analysis on the dynamic response of the vehicle used for sensing is crucial to the indirect frequency identification. Most published research on this topic, however, is based on a simplified two-dimensional (2D) analysis of vehicle-bridge interaction (VBI), which cannot fully reproduce the mechanism of a real three-dimensional (3D) vehicle. As a complement, this study carries out the 3D simulation of VBI and accordingly proposes a novel frequency-domain method to identify bridge natural frequencies from the vertical acceleration of a full-car model's wheels. The wheels' equations of motion are first transferred into the frequency domain, then the frequency responses of the front and rear wheels are subtracted with a time lag to eliminate the adverse effect of road roughness. Also proposed by this study is a new method to identify the speed of the sensing vehicle with the correlation function of wheel acceleration so that the time lag for subtraction can be calculated. In order to investigate the performance of the proposed methods, a series of numerical simulations are conducted, including sensitivity analysis on the vehicle speed, the class of road roughness, the noise level, and the vehicle frequency. Finally, this paper remarks on the accuracy and robustness of the proposed method and challenges faced by the engineering practice of the indirect bridge structural identification methodology.
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