Abstract
Crack breathing under train passages is an essential aspect of managing the existing concrete bridges since it can cause bridge stiffness to decrease or fluctuate. On the other hand, nonlinear modal identification methods corresponding to the rapid system frequency fluctuation under forced vibration state, on the other hand, are required to estimate bridge responses. The Bayesian TV-ARX method, which is a time-varying system identification method that takes external force characteristics into account, is suggested in this study and applied to the recorded displacement responses of a high-speed railway concrete girder when train passages. The identified time-varying bridge frequencies are compared to the results of some wavelet analysis. As a result, it was determined that the suggested Bayesian TV-ARX approach can achieve the instantaneous decrease in bridge frequency that cannot be estimated by the continuous wavelet transform.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
