RBF神经网络算法在动态称重中的应用

针对高速公路动态检测系统中称重数据的复杂性，将不同的称重数据处理办法做出对比，并提出利用 RBF神经网络对动态称重数据进行处理。文章首先综述性的介绍了车辆动态系统整体构成，之后对径向基函数网络的拓扑结构以及径向基函数中心的选取进行了介绍，最后利以试验台搭建检测平台，通过实验用两轴小车进行以不同的速度通过试验台，采集其动态参数。最后利用采集到的数据，用 MATLAB 进行仿真，验证了径向基函数网络对动态称重数据的处理表现出良好的速度与精度。

Application of RBF neural network algorithm in dynamic weighing

In this paper,focus on the complexity of weighing data in the dynamic detection system of the highway,the different weighing data processing methods to make a comparison,and proposed the use of RBF neural network to deal with the dynamic weighing data.Firstly review introduced the whole vehicle dynamic system,after the radial basis function network topology and the centers of the radial basis function selection are introduced.Finally the test-bed to build a testing platform,through experiments with a two axle vehicle with different speed through the test stand,the dynamic parameters acquisition.Finally,using the data collected,using MATLAB to simulate,verify the radial basis function network to the dynamic weighing data processing show good speed and accuracy.