Analysis of dynamic features on local fatigue cracks in steel bridges

Wei, Qingyang and Kövesdi, Balázs Géza and Cao, Maosen and Dunai, László (2024) Analysis of dynamic features on local fatigue cracks in steel bridges. PROCEDIA STRUCTURAL INTEGRITY, 57. pp. 262-270. ISSN 2452-3216

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Abstract

In steel bridges with orthotropic decks, a common and important engineering structure, fatigue cracks can appear under long-term operation. Existing artificial detection is the main approach to detecting fatigue cracks in steel bridges, in addition to some non-destructive testing or image processing methods, and unmanned aerial vehicle are applied to improve accuracy and efficiency. However, the detection of fatigue cracks in steel bridges based on the variation of dynamic responses or dynamic parameters is another attractive idea, which is still rarely mentioned and investigated in the international literature. The reason is that local cracks usually have negligible effect on the global dynamic characteristics of steel bridges, resulting in the insensitivity to dynamic indexes to fatigue cracks. On this occasion, this study numerically explores and establishes two sensitive damage features to local damage, i.e., the crack in the vertical rib, based on the fatigue cracks found on the Türr Istvan bridge over the Danube River in Hungary. The local vibrations of the bridge are excited through the local impact on the structural details, i.e., the vertical rib, and then the high-order frequencies of the entire bridge are examined. The obtained high-order frequencies are proved to be more sensitive to the fatigue cracks on vertical ribs and increased with the crack depths. On the other hand, the correlation of the stress curves on opposite sides of the crack is sensitive to the depth of the crack. If fatigue cracks are found, the development degree of the fatigue cracks can be monitored more accurately by focusing on the correlation of local stresses near the crack. These two damage features are numerically proven to have feasibility and are expected to break through the insensitivity of the existing dynamic detection methods. © 2024 The Authors. Published by Elsevier B.V.

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