Using Sensing On-Board Passing Vehicles for the purpose of Virtual Sensing of Bridges

The dynamics of bridges and (traversing) vehicles are coupled through the contact forces at the interface between the two subsystems. This study proposes the concept of virtual sensing (response reconstruction) in bridges using information from on-board sensors installed on an instrumented vehicle with known dynamic characteristics. The premise of the proposed approach is that contact force estimation requires knowing solely the properties of the vehicle model and information from on-board sensors, and, subsequently, using the Augmented Kalman Filter (AKF) technique. Interestingly, the proposed contact force estimation scheme does not necessitate knowledge of the rail profile irregularities characteristics, even though the contact forces depend on them. The estimated contact forces become then input to a finite element model of the traversed bridge, which enables the reconstruction of bridge response (acceleration, displacement, strains, stresses, etc). The estimated strain/stress time histories on the bridge can provide valuable information on the health status of the bridge. The proposed approach is verified with the aid of simulated data from railway bridge-vehicle interaction analyses, examining a 10-degree-of-freedom vehicle model that is representative of realistic train vehicles. The railway bridge considered is a simply supported Euler-Bernoulli beam model. The results offer valuable insights into the effects of different factors (measurement and model errors, vehicle speed, and rail irregularities) on the accuracy of contact force estimation and bridge response reconstruction, and suggest an optimal sensor configuration based on the minimum number of sensors required and their location on the vehicle.