Obtaining vehicle parameters from bridge dynamic response: a combined semi-analytical and particle filtering approach

Railway Engineering Science - Dynamic load imposed on the bridge by moving vehicle depends on several bridge–vehicle parameters with various uncertainties. In the present paper, particle...     

Estimation of gross weight,suspension stiffness and damping of a loaded truck from bridge measurements

Particle filter method (PFM) based on Bayesian inference gives a reliable estimate of hidden parameters from the noisy measured signal. A new method of vehicle parameter identification based on measured bridge response has been proposed using PFM. An uncoupled iterative technique is utilised for solving bridge vehicle interaction problem which has been used as a forward solution of the PFM. A field test under moving truck has been conducted on an existing pre-stressed concrete bridge to collect response data at different locations. Based on the extracted bridge natural frequencies and measured peak acceleration responses at five sensor locations, finite element model of the tested bridge has been updated using response surface-based model updating technique. In addition to estimation of test truck parameters using measured bridge response, dynamic wheel load induced in the bridge has been determined. Excellent agreement has been found between the measured and reconstructed bridge response using estimated parameters.