Modal shape identification for short and medium span bridges using wavelet based vehicular sensing approach
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Bibliografische Angaben
| Autor(en): |
Xudong Jian
(State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China)
Limin Sun 
(State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China)
Ye Xia (Department of Bridge Engineering, Tongji University, Shanghai, China) |
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| Medium: | Tagungsbeitrag | ||||
| Sprache(n): | Englisch | ||||
| Tagung: | IABSE Congress: Resilient technologies for sustainable infrastructure, Christchurch, New Zealand, 3-5 February 2021 | ||||
| Veröffentlicht in: | IABSE Congress Christchurch 2020 | ||||
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| Seite(n): | 567-575 | ||||
| Anzahl der Seiten (im PDF): | 9 | ||||
| DOI: | 10.2749/christchurch.2021.0567 | ||||
| Abstrakt: |
Modal parameter identification has been one of the key issues in the research of indirect bridge structural health monitoring. This paper presents a new indirect approach identifying modal parameters for short and medium span bridges, using dynamic responses of three connected vehicles. Accelerations of these vehicles are firstly subtracted to eliminate road roughness effects, so that the bridge frequency visibility in the frequency domain is improved. The wavelet analysis is performed to identify modal frequencies and shapes of bridges from the subtracted acceleration of moving vehicles. Systematic numerical experiments are performed to investigate the fidelity of the approach. Results show that the proposed approach can identify the bridge modal frequencies and shapes with promising accuracy and robustness. |
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