Dynamic characterization is essential for understanding structural behavior and ensuring integrity. Structural Health Monitoring (SHM) using ambient vibration analysis offers a non-invasive, rapid, and effective approach for as-sessing historic structures. This study presents a case study on Venice’s his-toric masonry arch bridges, evaluating their structural conditions through synchronized Tromino sensors. These bridges are not only critical for pedes-trian mobility but also represent valuable cultural heritage, making their preservation a priority. A network of Tromino sensors was strategically deployed on each bridge to capture ambient vibrations induced by wind, pedestrian traffic, and environ-mental factors. The recorded signals were processed using advanced spectral analysis and peak-picking techniques to extract key dynamic parameters, in-cluding natural frequencies, mode shapes, and damping ratios. These insights provide a deeper understanding of structural behavior, enabling the detection of potential damage and deterioration trends over time. Results confirm that ambient vibration monitoring is a reliable and effective technique for evaluating bridge conditions, offering early warnings of struc-tural changes without invasive testing. The collected data also aids in the cali-bration of numerical models, improving predictive accuracy and facilitating Machine Learning applications for long-term structural health assessment. By applying this methodology to multiple case studies, this research high-lights the potential of SHM in preserving cultural heritage. The proposed ap-proach enhances structural evaluations, ensuring the longevity and safety of historic bridges while advancing modern engineering practices in infrastruc-ture monitoring and conservation.
Dynamic Characterization Through Ambient Vibration Monitoring Using Synchronized Trominos : Case Study of Venice’s Bridges
Imani Moghaddam H.
;Russo S.
2025-01-01
Abstract
Dynamic characterization is essential for understanding structural behavior and ensuring integrity. Structural Health Monitoring (SHM) using ambient vibration analysis offers a non-invasive, rapid, and effective approach for as-sessing historic structures. This study presents a case study on Venice’s his-toric masonry arch bridges, evaluating their structural conditions through synchronized Tromino sensors. These bridges are not only critical for pedes-trian mobility but also represent valuable cultural heritage, making their preservation a priority. A network of Tromino sensors was strategically deployed on each bridge to capture ambient vibrations induced by wind, pedestrian traffic, and environ-mental factors. The recorded signals were processed using advanced spectral analysis and peak-picking techniques to extract key dynamic parameters, in-cluding natural frequencies, mode shapes, and damping ratios. These insights provide a deeper understanding of structural behavior, enabling the detection of potential damage and deterioration trends over time. Results confirm that ambient vibration monitoring is a reliable and effective technique for evaluating bridge conditions, offering early warnings of struc-tural changes without invasive testing. The collected data also aids in the cali-bration of numerical models, improving predictive accuracy and facilitating Machine Learning applications for long-term structural health assessment. By applying this methodology to multiple case studies, this research high-lights the potential of SHM in preserving cultural heritage. The proposed ap-proach enhances structural evaluations, ensuring the longevity and safety of historic bridges while advancing modern engineering practices in infrastruc-ture monitoring and conservation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



