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研究了应用BP网络在辊道窑炉温度过程中建立数学模型的方法.所研究的辊道窑炉的烧成段有八个区,靠燃料阀门开度调节温度.选取三层网络,辊道窑炉烧成段各区的燃料阀门开度作为网络的输入,各区的温度作为网络的输出,隐层节点数取10,建立温度过程数学模型.通过计算机仿真计算和实测温度曲线比较,满足误差范围要求.证明人工神经网络建立的数学模型能较准确计算辊道窑炉参数,为实现辊道窑炉生产过程的优化研究奠定了基础.
The method of establishing mathematical model in the roller kiln temperature by using BP network was studied.The furnace section of the roller kiln was studied in eight sections and the temperature was adjusted by the opening degree of the fuel valve.The three- The opening of the fuel valve in each section of the kiln firing section is taken as the input of the network and the temperature of each section is taken as the output of the network. The number of hidden layer nodes is taken as 10 to establish the mathematical model of the temperature process. Comparing the measured temperature curve with the computer simulation and satisfying the error range It is proved that the mathematical model established by artificial neural network can more accurately calculate the parameters of roller kiln and lay the foundation for the optimization research of roller kiln production process.