Identification of masses moving on multi-span beams based on a genetic algorithm

This paper describes a theoretical study on the identification of masses moving on a multi-span continuous beam using the acceleration measurements. In the study, the acceleration measurements are simulated from the solution to the forward problem of a continuous beam under moving masses, together with the addition of artificially generated measurement noise. In particular, the forward problem for the simulation is solved using the modified beam vibration functions. A simple dynamic force identification procedure using pseudo-inverse and singular value decomposition is first employed to arrive at rough approximations of the moving masses. A genetic algorithm is then used to find the best estimated values of the moving masses by minimizing the errors between the measured accelerations and the reconstructed accelerations from the moving masses in each generation. Five numerical examples are given to demonstrate the robustness of this method. Various possible sources of error including the effects of measurement noise and surface roughness are also discussed.