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Railroad bridges form an integral part of railway infrastructure throughout the world. Toaccommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence ofchanging structural conditions, the load carrying capacity and serviceability of existing bridges must beassessed. One way is through system identification of in-service railroad bridges. To dates, numerousresearchers have reported system identification studies with a large portion of their applications beinghighway bridges. Moreover, most of those models are calibrated at global level, while only a few studiesapplications have used globally and locally calibrated model. To reach the global and local calibration, bothambient vibration tests and controlled tests need to be performed. Thus, an approach for systemidentification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smartsensors are employed and provided a portable way to collect data that is then used to determine bridgefrequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides globaland local information of the bridge. The ability of the model to simulate local responses is validated bycomparing predicted and measured strain in one of the diagonal members of the truss. This researchdemonstrates the potential of using measured field data to perform model calibration in a simple andpractical manner that will lead to better understanding the state of railroad bridges.

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