Abstract
Structural health monitoring is fundamental to improve safety of critical structures, such as bridges. Most of health monitoring techniques is based on the variation of modal parameters along the lifetime of the structure. However experimental identification of modal parameters of bridges represents a difficult task. Ambient vibration tests were proved to provide a reliable estimation of modal parameters. However when the bridge is still close to the traffic and excitation is only provided by wind buffeting, signal-to-noise ratio may be unfavorable, making identification of modal parameters challenging. Forced vibration tests represent an alternative. Compared with ambient vibration tests, this approach presents the advantage of providing well defined input excitations, which can be optimized to enhance the response of the vibration modes of interest. The drawback is that the bridge must be closed to the traffic and that in the case of large and flexible bridges (suspended and cable-stayed bridges) with natural frequencies of predominant modes in the range 0–1 Hz, it is challenging to provide controlled excitation for a significant level of response. In this paper, the effectiveness to induce bridge vibrations by means of a heavy vehicle running on a series of cleats is discussed. On the purpose, a numerical model for truck–bridge interaction was developed. Results of the implemented model are compared with experimental data collected during an experimental campaign carried out on the Adige bridge. During the tests both truck and bridge were instrumented with accelerometers to measure excitation and bridge response.
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Notes
- 1.
Although not reported here, both natural frequencies and mode shapes are in good agreement with the ones predicted by the FE model [16].
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Argentini, T., Sabbioni, E., Vignati, M. (2014). A Dynamic Model for Truck-Induced Vibrations on a Cable-Stayed Bridge. In: Catbas, F. (eds) Dynamics of Civil Structures, Volume 4. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-04546-7_40
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DOI: https://doi.org/10.1007/978-3-319-04546-7_40
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