Nowadays, the need for effective Structural Health Monitoring (SHM) strategies, aiming at preserving the integrity and safety of strategic and historic infrastructures, is increasingly urgent. Within SHM, several vibration-based methodologies have been developed, including those exploiting Heterogeneous Data Fusion (HDF) procedures, as well as Denoising techniques for the treatment of response signals detected through appropriate sensor technologies. In this paper, these two approaches are reconsidered and rejoined, toward developing an innovative signal processing methodology for current condition assessment, specifically referring to historic bridges. In particular, a HDF approach, i.e. the process of combining information from multiple sources, in an effort to enhance the reliability of the monitoring process, and a denoising approach, devoted to the cleaning of spurious noise from the acquired signals, are combined all together, in an integrated strategy. The effectiveness of the proposed platform is tested on data from a real structure (historic bridges). Both dynamic acceleration and displacement response signals, directly detected under operational conditions, can be processed within the proposed methodology, and subsequently employed toward modal dynamic identification purposes and possible model updating of the structure at hand.

(2020). An integrated monitoring strategy for current condition assessment of historic bridges . Retrieved from http://hdl.handle.net/10446/172971

An integrated monitoring strategy for current condition assessment of historic bridges

Ferrari, Rosalba;Rizzi, Egidio;
2020

Abstract

Nowadays, the need for effective Structural Health Monitoring (SHM) strategies, aiming at preserving the integrity and safety of strategic and historic infrastructures, is increasingly urgent. Within SHM, several vibration-based methodologies have been developed, including those exploiting Heterogeneous Data Fusion (HDF) procedures, as well as Denoising techniques for the treatment of response signals detected through appropriate sensor technologies. In this paper, these two approaches are reconsidered and rejoined, toward developing an innovative signal processing methodology for current condition assessment, specifically referring to historic bridges. In particular, a HDF approach, i.e. the process of combining information from multiple sources, in an effort to enhance the reliability of the monitoring process, and a denoising approach, devoted to the cleaning of spurious noise from the acquired signals, are combined all together, in an integrated strategy. The effectiveness of the proposed platform is tested on data from a real structure (historic bridges). Both dynamic acceleration and displacement response signals, directly detected under operational conditions, can be processed within the proposed methodology, and subsequently employed toward modal dynamic identification purposes and possible model updating of the structure at hand.
Ravizza, Gabriele; Ferrari, Rosalba; Rizzi, Egidio; Dertimanis, Vasillis; Chatzi, Eleni
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10446/172971
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