Identification of vehicles moving on continuous bridges with rough surface

This paper describes the parameter identification of vehicles moving on multi-span continuous bridges taking into account the surface roughness. Each moving vehicle is modelled as a two-degree-of-freedom system that comprises five components: a lower mass and an upper mass, which are connected together by a damper and a spring, together with another spring to represent the contact stiffness between the tyres and the bridge deck. The corresponding parameters of these five components, namely, the equivalent values of the two masses, the damping coefficient, and the two spring stiffnesses together with the roughness parameters are identified based on dynamic simulation of the vehicle–bridge system. In the study, the accelerations at selected measurement stations are simulated from the dynamic analysis of a continuous beam under moving vehicles taking into account randomly generated bridge surface roughness, together with the addition of artificially generated measurement noise. The identification is realized through a robust multi-stage optimization scheme based on genetic algorithms, which searches for the best estimates of parameters by minimizing the errors between the measured accelerations and the reconstructed accelerations from the identified parameters. Starting from the very wide initial variable domains, this multi-stage optimization scheme reduces the variable search domains stage by stage using the identified results of the previous stage. A few test cases are carried out to verify the efficiency of the multi-stage optimization procedure. The identified parameters are also used to estimate the time-varying contact forces between the vehicles and the bridge.