Abstract

This paper presents a cost-effective Bridge Weigh-in-Motion (B-WIM) system for the identification of train loads using fiber-optic technology. The system is capable of estimating the train’s speed, geometry and static axle loads, using the algorithm proposed by Moses. This algorithm involves the resolution of an inverse identification problem where the measured structural response is known and the loading scheme is unknown. The method relies on the concept of Influence Line (IL), which is estimated from the passage of a calibration vehicle with known characteristics. A numerical validation example, based on a simply supported bridge with a train passing at different speeds, demonstrated the functionality and potential accuracy of the implemented B-WIM system. For speeds up to 120 km/h, the maximum estimated errors of the wheelbase and axle loads were 10 cm and 2.5%, respectively. A B-WIM system was installed in an existing filler-beam bridge, located on the Portuguese Railways, consisting of a minimalist layout of fiber Bragg grating sensors, which guarantee higher-quality measurements, quick installation and long-term stability. The system allowed a precise characterization of several Alfa Pendular, Urban and Regional trains. This study constitutes a step forward in the development of online B-WIM systems capable of automatically estimating traffic characteristics. The accurate estimation of the traffic loads is a valuable information for the evaluation of the structural integrity and safety of railway bridges.

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