基于RBF神经网络的中厚板轧制宽展模型

Model of width spread in medium plate rolling based on RBF neural network

以4200轧机轧制钢板的实测数据为基础,利用Matlab神经网络工具箱,建立了中厚板轧机宽展的RBF神经网络预测模型。通过分析宽展的影响因素,结合传统的数学模型,确立了网络的输入层参数,并对宽度系数spread进行试验调整,确定了最佳的网络结构形式,提高了模型的预测精度。通过实例比较了RBF模型与BP模型的预测效果,并且分析了不同参数下RBF神经网络逼近精度。结果表明,RBF神经网络模型有较好的收敛速度和预测精度,能更好地适用于中厚板轧机宽展模型。

Based on the experimental data obtained from 4200 rolling mill,this paper established a RBF neural network prediction model of width spread in medium plate mill by Matlab neural network toolbox. By analyzing influential factors of width spread,and taking into account the traditional mathematical model,this paper affirmed the parameters of input layer. By selecting suitable spread, this paper affirmed the best form of the network,as a result,it improved the prediction accuracy. The predictions by the RBF neural network and those by the BP neural network were compared through examples. The accuracy of RBF neural network indifferent parameters is analyzed. The results indicate that RBF neural network converges more quickly,has better accuracy and can be better applied in the model of width spread in medium plate mill.