Static and dynamic vehicle load identification with lane detection from measured bridge acceleration and inclination responses

Abstract

The effects from passing vehicle's load on bridge are divided into two categories: static effect and dynamic effect. The static effect usually indicates the pseudo-static responses of the bridge caused by the vehicle gross weight while the dynamic effect means dynamic responses due to vehicle and bridge dynamic properties and bridge pavement roughness. Both effects need to be properly evaluated because the vehicle static weight is a governing factor in determining bridge's fatigue life while the dynamic part of the vehicle load tends to amplify the bridge responses. In this paper, a method based on an extended Kalman filter is proposed to identify vehicle static and dynamic load only from responses recorded by portable accelerometers, together with their transverse position, which affects the identification of the loads. Even though only accelerometers are employed as sensors, the bridge vertical acceleration can capture the dynamic load components and the inclination obtained from the projection of the gravitational acceleration in the longitudinal direction can capture the low-frequency component. The feasibility of the proposed method is proved through numerical simulation and an experimental test on a bridge. This paper makes full use of three-axis accelerometers to estimate vehicle's static and dynamic load considering the vehicle's passing route, thus solving the nonlinear problem caused by vehicle's transverse position. Moreover, the proposed method eliminates the need of using other devices like displacement sensor or strain gauges to obtain low-frequency components.