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

Abstract

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.

Identification of Dynamic Vehicular Axle Loads: Theory and Simulations

“…While inertia forces are always included in dynamic simulations, their effect on the identified interaction forces was investigated since this effect was usually ignored in the bridge weigh-in-motion practice (Leming and Stalford, 2002). Both the deflection and the strain information from S5 while the vehicle is traveling along R2 were used in this identification process.…”

“…The first method is very expensive and difficult to implement, and the results obtained are subject to bias since the measurement is limited only to the instrumented vehicles, while the second method is subject to modeling errors. To obtain site-specific information of vehicle weight, weighin-motion systems have also been developed in the last few decades (Peters, 1984), but they usually measure only static axle loads, requiring a smooth road surface or slow vehicle movement to eliminate the dynamic effects (Leming and Stalford, 2002). Therefore, it would be beneficial if the dynamic axle forces of routine traffic vehicles could be identified from measured bridge responses, since such information is very valuable for bridge engineers.…”

A Novel Mechatronics Approach to Measure The Payload of Heavy Duty Vehicle

“…In Bridge Weigh-in-Motion, a potential alternative to the conventional weighbridges, the response of the bridge to the motion of the vehicle is taken into consideration. Herein, the bridge was modeled as a beam free from internal stresses and the vehicle as a two point moving mass [3]. It is comprehend-able that the attributes like efficiency, static parking weighing methodology or dynamic weighing system are not very satisfactory [4].…”

Identification of Dynamic Vehicular Axle Loads: Demonstration by a Field Study

“…Third, both the vehicle speed and road surface condition have insignificant effects on the identified mean values that approximately correspond to the truck's static weight, indicating that the developed methodology can be used for routine traffic conditions. This would be a significant advantage over most bridge weigh-in-motion systems which usually require smooth road surface conditions and slow vehicle movement to minimize the dynamic effect of vehicle loads (Leming and Stalford, 2002;McNulty and O'Brien, 2003). Lastly, as the road surface condition gets worse the standard deviation of the results gets larger, indicating that the dynamic effect induced by the road roughness becomes more significant.…”