摘要
为了提高辊底式热处理炉的钢板温度预报精度,采用了遗传神经网络的方法,运用大量的现场实际数据进行训练和仿真,建立了钢板温度预报模型,并应用于计算辊底式热处理炉钢板温度的数学模型中。结果表明,所建立的模型简单、精度高,能够满足在线应用的要求。
In order to improve the steel plate temperature prediction accuracy of the roller-hearth heat treatment furnace, GA-BP neural network is trained by a great deal of actual data. A model is used to calculate the steel plate temperature of the roller-hearth heat treatment furnace. The result shows that the model is very simple and it has high precision which can satisfy the requirement of actual application.
出处
《钢铁研究学报》
CAS
CSCD
北大核心
2008年第9期50-53,共4页
Journal of Iron and Steel Research
关键词
辊底式热处理炉
温度预报
遗传神经网络
roller-hearth heat treatment furnace
temperature prediction
genetic neural network
