Axle detection on prestressed concrete bridge using bridge weigh-in-motion system

Abstract

In the bridge weigh-in-motion (B-WIM) system, the free of axle detector (FAD) sensors, attached to the bottom of the slab, are used to obtain vehicle parameters such as velocity, axle numbers, and their distances. The experimental B-WIM test using FAD sensors by previous researchers on prestressed concrete I girder bridge yielded reliable responses; however, the frequency of vehicle parameter detection was questionable. On the prestressed concrete bridges, when the vehicle paths are near girders, the load gets transferred to the girder thus affecting the vehicle axle detection. Therefore, to properly detect the vehicle parameters, an optimized sensor location and number of sensors is required on the slab and near the girders. The previous experimental test, despite being accurate in single vehicle axle detection, was unsuccessful in breaking down the vehicle parameters on wide-span bridges that are subjected to multiple vehicles. Therefore, the fully developed 3 dimensional finite element model (3D FEM) of vehicle–bridge interaction considering different aspects of vehicle including suspension, damping, tire movement, air pressure, mass distribution on the axles, material and geometric behavior of the bridge was developed and verified with the experimental results. After verification the 3D FEM was used for sensor optimization on slab and the girder. Moreover, the optimized sensor locations were analyzed for multi-vehicles–bridge interaction. With the optimization, the sensor placement was made suitable for the B-WIM implementation on US bridges. Once implemented, the B-WIM system can be used for monitoring traffic for structural health and for law enforcement.