Virtual Axle Method for Bridge Weigh-in-Motion Systems Requiring No Axle Detector

Abstract

Bridge weigh-in-motion (BWIM) systems provide an effective approach to identifying the axle and gross vehicle weights of vehicles as they travel over an instrumented bridge. For the majority of BWIM systems, the vehicle configuration (including axle count and axle spacing) and vehicle speed are prerequisites for identifying the axle and gross weights of vehicles. Existing nothing-on-road (NOR) BWIM systems acquire such data through dedicated sensors, namely, free-of-axle-detector (FAD) sensors, in addition to weighing sensors. These FAD sensors are usually installed on the underside of the bridge deck or girders. This study presents a novel method for identifying the axle spacing and weights of vehicles. It only requires the flexural strain signal recorded from the weighing sensors, leading to both a reduction in the installation cost and broader applications of BWIM systems. The effectiveness and accuracy of the proposed method are demonstrated through numerical simulations. Laboratory experiments based on a scaled vehicle–bridge interaction (VBI) model were also conducted for verification. The results show that the proposed method has good accuracy for axle spacing and axle weight identification.