A bridge weigh-in-motion system based on iteratively reweighted least squares

At present, the commercial bridge weigh-in-motion systems (BWIM) are generally based on the Moses algorithm. Although they can efficiently and quickly identify the axle weights of vehicles driving by bridges, the accuracy is low. To solve this problem, this paper presents a novel algorithm that finds axle weights using the bridge response subjected to the drive-by vehicles. Unlike Moses’ algorithm assuming all the bridge response have the same uncertainties, the proposed algorithm based on iteratively reweighted least squares (IRLS) considers the unequal uncertainties and can assign each observed response data its proper amount of influence over the axle weights estimates. Firstly, derive the formula of axle weights identification using IRLS; then, Numerical simulations are conducted to verify the IRLS algorithm using a simply supported beam-vehicle interaction model; finally, based on the field test of Wushui Fifth Bridge approach bridge, compares and analyses the axle weight identification of Moses algorithm and IRLS algorithm. Results show that IRLS algorithm reasonably allocates the contribution of different load responses to axle load identification and it can get more accurate axle weights than Moses’ algorithm. © 2023 Chinese Vibration Engineering Society. All rights reserved.