Data fusion and machine learning for bridge damage detection

This study presents a new approach for bridge damage detection using multi-level data fusion and anomaly detection techniques. The approach utilises as input data accelerations, deflections and bending moments, measured at multiple sensor locations on a bridge subjected to a moving vehicle. A damage...

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Bibliographic Details
Main Authors: Hao Wang, Giorgio Barone, Alister Smith
Format: Default Conference proceeding
Published: 2022
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