Using search based optimization algorithms in Bridge Weigh-In-Motion systems

Abstract

A method for the identification of vehicle axle loads on slab-on-girder bridges is presented in this paper. The method is based on the development of a bridge specific static influence line matrix and the use of an optimization method combined with a pattern search algorithm. A 1/3 scale laboratory model of a six girder bridge was used as part of the case studies which demonstrate the development and implementation of the method. A finite element model of the bridge was developed and calibrated against experimental data. The search based optimization procedure was necessary to provide an estimate of vehicle characteristics when noise was present in the recorded data and when error was present in the numerical model. The estimated vehicle characteristics therefore did not exactly match the actual vehicle; this deviation was designated as an identification error. The statistical behavior of the identification error with respect to the level of noise in the measured response or error in the model was studied. Methods for reduction of the identification error were numerically evaluated. It was shown that a field calibrated bridge model is important and that averaging of multiple vehicle estimates for different positions on the bridge can decrease the identification errors.