Abstract Manager

Increasing traffic loads along with aging bridge degradation are resulting in oversize and overweight vehicles becoming a regular challenge for bridge structures worldwide. It is therefore essential to monitor the movement of heavy trucks on a bridge network for planning and maintenance. This has led to increased development of monitoring solutions to determine the prevalence of overweight loading events and their impact on bridge structures. Bridge Weigh In Motion (BWIM) methods estimate the weights of vehicles at full highway speeds by using an instrumented bridge as a scale. Current operational nonparametric BWIM methods based on the Mosses algorithm require frequent calibration to ensure accuracy due to changes in bridge behaviour from changing operational and environmental conditions. These calibrations currently require isolated vehicles of known weight which can be costly, disrupt traffic flow and are not always practical with busy highway structures. A novel dynamic parametric Bridge Weigh-in-Motion (BWIM) method has recently been developed. that utilizes experimentally estimated modal parameters of a two-dimensional bridge structure to simulate its response to a moving load. This research assesses the method's capability to accurately capture the evolving bridge response under changing environmental conditions by incorporating online modal parameters into the BWIM analysis. The study investigates the impact of environmental changes on estimated modal parameters, analyzes resulting alterations in bridge response characteristics, and evaluates the effect of these variations on BWIM accuracy. Additionally, the proposed automatic dynamic calibration method's effectiveness will be evaluated through a full-scale case study involving an arterial highway bridge in New Brunswick, Canada.