Structural Health Monitoring of a steel truss railway bridge studying its low frequency response
Auteur(s): |
Luca Radicioni
(Department of Mechanical Engineering Politecnico di Milano Milano Italy)
Lorenzo Bernardini (Department of Mechanical Engineering Politecnico di Milano Milano Italy) Francesco Morgan Bono (Department of Mechanical Engineering Politecnico di Milano Milano Italy) Mattia Anghileri (Department of Civil and Environmental Engineering Politecnico di Milano Milano Italy) Luca Capacci (Department of Civil and Environmental Engineering Politecnico di Milano Milano Italy) Gabriele Cazzulani (Department of Mechanical Engineering Politecnico di Milano Milano Italy) Claudio Somaschini (Department of Mechanical Engineering Politecnico di Milano Milano Italy) Aniket Ketan Pande (Department of Mechanical Engineering Politecnico di Milano Milano Italy) Fabio Biondini (Department of Civil and Environmental Engineering Politecnico di Milano Milano Italy) Simone Cinquemani (Department of Mechanical Engineering Politecnico di Milano Milano Italy) Marco Belloli (Department of Mechanical Engineering Politecnico di Milano Milano Italy) |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | ce/papers, septembre 2023, n. 5, v. 6 |
Page(s): | 876-885 |
DOI: | 10.1002/cepa.2184 |
Abstrait: |
In the framework of direct Structural Health Monitoring approaches, this paper presents a low frequency range analysis performed on a steel truss bridge designed in 1946 and built up in Northern Italy. The bridge is instrumented with a permanent structural health monitoring system, that guarantees a continuous flux of data and information from a heterogeneous set of sensors. In this analysis, static and quasistatic bridge responses are considered. These experimental data are merged with the analogous outputs obtained from numerical simulations, performed on FE models representative of the actual bridge, with the purpose of identifying damage‐sensitive indexes. Simulations are performed considering the healthy structure and modelling different damage scenarios. The static analysis consists in the construction of a regressive model able to estimate sensor output responses starting from environmental measurements, with the primary purpose to reduce the effect of temperature over measured static response. This procedure allows to relate the damages simulated by means of a numerical model with the real data, so that the monitoring rules can effectively defined. |
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10767273 - Publié(e) le:
17.04.2024 - Modifié(e) le:
17.04.2024