Damage identification in cable-stayed bridges using modal data

In this study, damage detection methods of cable stayed bridges were investigated. Cable stayed bridges are flexible structures; meanwhile they are sensitive to vibrations due to their complicated and multiple vibrations modes; therefore, damage detection methods based on vibration data in cable-sta...

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Autores principales: Mohammad Alikhani Dehaghi, Gholamreza Ghodrati Amiri, Ali Zare Hosseinzadeh, Seyed Ali Seyed Razzaghi
Formato: article
Lenguaje:FA
Publicado: Iranian Society of Structrual Engineering (ISSE) 2020
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Acceso en línea:https://doaj.org/article/24d9a64f8f484e5aaea644bb35572406
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Sumario:In this study, damage detection methods of cable stayed bridges were investigated. Cable stayed bridges are flexible structures; meanwhile they are sensitive to vibrations due to their complicated and multiple vibrations modes; therefore, damage detection methods based on vibration data in cable-stayed bridges has become a challenging issue. In the present study, finite element model of Bill Emerson, Missouri cable stayed bridge was simulated in order to achieve a precise finite element model to simulate the damage scenarios in bridge and the study of them. General process includes four damage detection indices based on the modal data (mode shapes and natural frequencies) achieved by modelling structure and simulated damages and in each case the results of damage detection were presented by indices. These methods are: Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC), Modal Flexibility Index (MFI), Damage Index (DI). Some of the methods were applied in damage detection of the pervious structures and bridges. In this paper, correlative study of these methods were performed based on different damage scenarios as well as study of challenges such as different levels of random noise in the input data, incomplete modal data and low damage intensity in detection of damage in cable-stayed bridge and then, performance of the methods were assessed.