Abstract: X. Xu, J. Zhan, C. Wang, Z. Wang, Y. Wang (2024)

Simply-supported bridges play an important role in transportation systems, and their structural integrity is often influenced by the increased traffic loads or inadequate maintenances. Consequently, the accurate identification of damage in simply-supported beams is paramount. The recurrence graph, containing rich structural vibration information, offers a promising avenue for damage identification. However, it is challenging to achieve precise damage identification by observing the recurrence graphs alone and the large scale of the recurrence matrix hinders efficiency of the identification. So, existing methods based on recurrence graphs are mostly relied on deep learning, necessitating a substantial volume of training samples, which inhibits its application in bridge engineering. In view of this, a novel damage-sensitive index named recurrence singular energy index (RSEI) is proposed, based on which the objective function is constructed and a damage identification methodology is established aiming to enhance the practicality of recurrence graph theory in bridge damage identification. The procedure involves threshold-free cross recurrence analysis on impact responses to derive the recurrence matrix, followed by singular value decomposition to extract damage features. Subsequently, the energy of the recurrence singular values is computed, establishing a precise, robust, and practical identification methodology combined with model updating technology. The effectiveness and efficiency of the proposed method are validated through numerical simulations and laboratory experiments. Results demonstrate that the RSEI exhibits sensitivity to damage, facilitating efficient damage quantification and localization as well as the proposed method exhibits strong practical value in simply-supported bridges.

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Damage identification of simply-supported bridges using impact response-based recurrence graph