Data Transmission And Algorithm Research On Vehicle Weigh-in-motion Systems

With the rapid development of the economy, the traffic demand is increasing day by day. The development of transportation industry has played a positive role in promoting the national economic construction. But the phenomenon of the vehicle overload has caused great damage on people’s daily life. Thus, we need to adopt advanced technology to solve this problem fundamentally. In Inner Mongolia which is a province of China, there are many vehicles to transport coal, and the vehicle overload is coming from bad to worse.Firstly, this paper designs the vehicle weigh-in-motion(WIM) system according to the actual situation of the provinces thoroughfare. Then, it produces the operating principle of the WIM system. It mainly analyzes the factors may affect the accuracy of the WIM system in detail and obtains the key factors which influence the accuracy of the system.The data acquisition and transmission system is designed in this paper. Choose According to the requirement of actual accuracy, we choose the fiber grating sensors. The data acquisition system send the vehicle weight, the speed, the number of shaft and image data capture by the camera to PC through GPRS. The toll station save the information of the vehicle and send it to the section center through GPRS network and Internet network.In this paper, back-propagation (BP) neural network algorithm is introduced to processing the dada of the vehicle WIM system and one BP neural network algorithm model which is apply to WIM system is established. Simulated result using MATLAB and the experimental result is also on the paper. In order to accuracy of the test, the genetic algorithm is used to optimize the BP neural network. This method can speed up the convergence and avoid getting stuck in the local minimum. The experiment results show that the optimizing BP neural network algorithm based on genetic algorithm can reduce the average error of the calculation and prediction. And the accuracy and efficiency of the weigh-in-motion (WIM) system are improved.