Structural Health Monitoring Techniques
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Peer reviewed
Abstract
Abstract
This work investigates the capability of a permanent monitoring system to detect structural degradation before it compromises bridge operational requirements. The target structure is a multi-span steel truss railway bridge located in Italy, characterized by a complex geometry featuring Gerber connections and dual-deck configuration. Utilizing a high-fidelity finite element model of the entire structure, a comprehensive set of damage scenarios is simulated. The research evaluates the sensitivity of a monitoring setup consisting of inclinometers mounted on all three spans. A data processing pipeline is implemented to purge sensor signals from temperature-induced variations using multiple linear regression and principal component analysis. Damage detectability is then assessed by comparing damage-induced variations from ”virtual sensors” against the residual statistical variance (±2σ) derived from the real-world monitoring data of the healthy structure. The outcomes provide insights into the effectiveness of static monitoring systems for the identification of different damage conditions in complex truss bridges.
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@article{Giorgi2026Framework,
title = {A Framework for Assessing Bridge Damage Detectability and Serviceability under Environmental and Operational Variability},
author = {Viviana Giorgi and Lorenzo Bernardini and Pablo Alex Ramírez Balbiano and Gabriele Cazzulani and Claudio Somaschini},
journal = {e-Journal of Nondestructive Testing},
year = {2026},
doi = {10.58286/33916},
url = {https://doi.org/10.58286/33916}
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