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dc.contributor.authorLi, Jun
dc.contributor.authorHao, H.
dc.date.accessioned2017-01-30T10:56:16Z
dc.date.available2017-01-30T10:56:16Z
dc.date.created2016-08-03T19:30:18Z
dc.date.issued2015
dc.identifier.citationLi, J. and Hao, H. 2015. Dynamic condition assessment of shear connectors in composite bridges with acceleration measurements: A field study, in Proceedings of the 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII), Jul 1-3 2015, pp. 2124-2131. Torino, Italy: International Society for Structural Health Monitoring of Intelligent Infrastructure.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/6891
dc.description.abstract

Shear connectors are generally used to link the slab and girders together in slab-on-girder bridge structures. Damage of shear connectors in such structures will result in shear slippage between the slab and girders, which significantly reduces the load-carrying capacity of the bridge. This paper explores to use transmissbility and power spectral density transmissbility to identify the damage of shear connectors in slab-on-girder bridge structures. Transmissbility and power spectral density transmissbility can be used to identify shear connector conditions without reference data of the baseline structure. Measured impact force and acceleration responses from hammer tests are analyzed to obtain the frequency response functions at sensor locations by experimental modal analysis. A reference sensor is identified when calculating the damage index. The proposed damage index is applied to evaluate the shear connector conditions in a real composite bridge with in-field testing data.

dc.titleDynamic condition assessment of shear connectors in composite bridges with acceleration measurements: A field study
dc.typeConference Paper
dcterms.source.titleSHMII 2015 - 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure
dcterms.source.seriesSHMII 2015 - 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure
curtin.departmentDepartment of Civil Engineering
curtin.accessStatusFulltext not available


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