Bridge weigh-in-motion system development using static truck/bridge models

In this paper, we investigate the problem of developing a weigh-in-motion (WIM) system for use on in-service highway bridges. We consider the problem of processing a bridge's elastic response due to a passing truck and estimating the unknown truck parameters: axle spacing, speed, axle weights, and gross weight. For this problem, the bridge is modeled as a static Euler beam, and the truck is modeled as two moving point masses. The midpoint deflection of the beam is measured over time, and an optimization routine is employed to estimate the values of the unknown parameters. The truck's axle weights, axle spacing, speed and total weight are unknown, and a variety of different truck parameters are considered. First, the deflection is monitored at a constant sampling rate and all points are used in the optimization routine. For this case, with zero measurement error, the errors in the estimates of the truck parameters were unduly large. Second, a sampling technique that used half the number of points as in the first case, but selected them randomly in time, was used. Using the latter technique, with zero measurement error in the data, the errors in the parameter estimates were essentially zero. Finally, measurement error was added to the data and, using the random sampling method, the estimates of all truck parameters were essentially perfect until the magnitude of the measurement error reached 10 microns. The error remained less than 5% with noise up to 100 microns.