To further improve the existing bridge weigh-in-motion technique,this paper proposes a bridge weigh-in-motion system integrated with machine vision.Firstly,the machine vision algorithm is used to identify and track the vehicle;then,the bridge response monitoring information under the action of the vehicle is processed;furthermore,the axle load and axle base are identified by using the virtual simply-supported beam theory;finally,the method is tested by simulation and test.The results show that the method proposed in this paper has a good identification effect on the axle weight and wheelbase of vehicles under various working conditions.The average relative errors of the identification of axle weight,wheelbase and total weight are 3.40％,4.31％and 2.71％respectively.It has a certain anti-noise ability,which shows that the method has good robustness and applicability.
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