Study On Bridge Surface Roughness Identification Using Dynamic Response Of A Moving Two-axle Vehicle

The surface roughness of a bridge is one of the significant indicators to evaluate the service performance,and is an important basis for the decision-making of bridge maintenance and management.With the increase in service time,traffic loads and influence of environmental factors,the level of bridge roughness has gradually decreased,which directly affects the riding comfort and even safety of the ongoing vehicles.Currently,conventional measurement of road roughness generally depends on many profiling devices,such as complex contact measuring equipment,laser profilers,highspeed cameras,etc.However,these devices remain expensive to purchase and inefficient to operate,which is difficult to meet rapid,economical and accurate measurement needs for the highways and bridges with large quantities and wide areas.This thesis focuses on the theory and method of bridge roughness measurement based on the response of moving vehicles,the main research works and results are as follows:(1)Based on the response of two connected vehicle,a procedure for identifying bridge roughness is proposed.The mathematical correlation of the displacement between front and rear contact points is established via the displacement influence lines(DILs),and then uncoupling conditions of bridge(contact points)displacement and roughness are obtained.With this,the closed solution of the roughness identification for bridges is derived.(2)The roughness identification formula is applied to simply-supported and threespan continuous bridges,utilizing two methods of theoretical derivation and numerical simulation to verify its validity.It shows that the identification errors keep a trend similar to the impact factor,and not too heavy test vehicle and a moderate speed(less than 50km/h)are recommended for use in practice.(3)The extended Kalman filter with unknown inputs(EKF-UI)is introduced,and the state and measurement equations are obtained via the relationship between bridge roughness and state variables,measurement variables,respectively.Then the analytical recursive solution of the bridge roughness is derived.Based on the response of moving two-axle vehicle and EKF-UI,the identification method of bridge surface roughness is established.(4)The finite element models of vehicle bridge interaction for simply supported and continuous bridges are established respectively.The numerical results show that the identification error of roughness based on EKF-UI algorithm increases as the vehicle speed,environmental noise increase,and decreases as the bridge damping increases,but is not affected by the vehicle-bridge mass ratio.The bridge roughness identification methods based on the response of two-axle vehicle proposed by this thesis only depend on the parameters of vehicle and its relative position on the bridge,but not the other properties of the bridge concerned,such as the cross-sectional area,stiffness,density,etc.,which proves that methods in this thesis can be applied to various types of bridges.