The idea that the majority of bridges have reached the end of their service life has become widely accepted. The need for continuous monitoring of a large number of structures has become both a duty and a burden for administrations and operators. While technological advancements enable the acquisition of numerous structural parameters, effectively harnessing the vast amount of data generated is not a straightforward task. Therefore, an automated tool that can conduct end-to-end analysis with minimal effort and cost is crucial. The presented solution is applied to two different bridges, both in reinforced concrete and instrumented with tailored monitoring systems, from sensors to the cloud-based dashboard. Modal parameters such as vibration modes, modal shapes, and damping are determined using the OMA algorithm, specifically PolyMAX, in an automated process. The analysis are performed through robust software provided by Siemens, e.g. Test Lab. Finally, by enhancing the potential of the cloud for measurement data storage, the implementation of advanced data management tools is being considered as interesting emerging prospects.

A Robust End-To End Framework for Automated Modal Identification for Infrastructure Monitoring / Imperiale, Alessandro; Ferrara, Mario; Imposa, Giacomo; Germano, Federico; Geroso, Simone; Bertagnoli, Gabriele.. - ELETTRONICO. - 515:(2024), pp. 228-235. (Intervento presentato al convegno 10th International Operational Modal Analysis Conference, IOMAC 2024 tenutosi a Napoli nel 21-24 May 2024) [10.1007/978-3-031-61425-5_23].

A Robust End-To End Framework for Automated Modal Identification for Infrastructure Monitoring

Ferrara, Mario;Bertagnoli, Gabriele.
2024

Abstract

The idea that the majority of bridges have reached the end of their service life has become widely accepted. The need for continuous monitoring of a large number of structures has become both a duty and a burden for administrations and operators. While technological advancements enable the acquisition of numerous structural parameters, effectively harnessing the vast amount of data generated is not a straightforward task. Therefore, an automated tool that can conduct end-to-end analysis with minimal effort and cost is crucial. The presented solution is applied to two different bridges, both in reinforced concrete and instrumented with tailored monitoring systems, from sensors to the cloud-based dashboard. Modal parameters such as vibration modes, modal shapes, and damping are determined using the OMA algorithm, specifically PolyMAX, in an automated process. The analysis are performed through robust software provided by Siemens, e.g. Test Lab. Finally, by enhancing the potential of the cloud for measurement data storage, the implementation of advanced data management tools is being considered as interesting emerging prospects.
2024
978-3-031-61425-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2993623