Abstract
Civil steel structures and infrastructures, such as truss railway bridges, are often subject to potential damage, mainly due to fatigue phenomena and corrosion. Terefore, damage detection algorithms should be designed and appropriately implemented to increase their structural health. Today, the vast amount of information provided by data processing techniques and measurements coming from a monitoring system constitutes a possible tool for damage identifcation in terms of both detection and description. For this reason, the research activity aims to develop a methodology for a preliminary description of the damage in steel railway bridges induced by fatigue phenomena. Te proposed approach is developed through an integration of global and local procedures. At the global scale, vibration-based procedures will be applied to improve a forecast numerical model and, subsequently, to identify the zones most involved in fatigue problems. At the local scale, careful and refned local identifcation will be pursued via image processing techniques whose evidence will be analyzed and described through nonlinear numerical models. A case study of a historical railway bridge in Spain will illustrate the methodology’s performance, potentiality, and critical issue.
Cite
CITATION STYLE
Crognale, M., Potenza, F., & Gattulli, V. (2023). Fatigue Damage Identification by a Global-Local Integrated Procedure for Truss-Like Steel Bridges. Structural Control and Health Monitoring, 2023. https://doi.org/10.1155/2023/9594308
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