Bridge State and Average Train Axle Mass Estimation for Adaptive Railway Bridges

Adaptive structures are equipped with sensors and actuators to counteract deformations caused by external loads. Concerning railway bridges, previous work has shown that active vibration damping allows extend the service life. Trains as loads represent decisive influencing factor for bridge be taken into account when applying model-based control concepts. This article proposes a state disturbance estimator (SDE) based on moving point load train model estimating average axle mass. The employed estimation is linear time variant, which use of an augmented Kalman filter. Estimability analyzed Fisher information proposed systematically tested through simulations. A quadratic regulator designed combined SDE evaluate closed-loop performance vibrations during crossing.