应用人工神经网络设定CSP精轧机组压下规程  

Setting CSP Finishing Mill Reduction Procedure by Applying Artificial Neural Network

作　　者：黄福洲[1] 程晓茹[1] 李春光[1] 尹皓[1] 陈凯[1] 蒋祝爽[1] 

机构地区：[1]武汉科技大学材料与冶金学院,湖北武汉430081

出　　处：《热加工工艺》2013年第7期101-103,106,共4页Hot Working Technology

摘　　要：以CSP精轧机组现场实测生产数据为样本,运用BP人工神经网络研究方法,建立CSP精轧机组压下规程模型。结果表明:BP人工神经网络模型具有很高的计算精度,可以准确地设定CSP精轧机组压下规程。Taking production data measured in CSP finishing mill set as a sample, the model of CSP finishing mill reduction procedures was established by using BP artificial neural network research method. The results show that BP artificial neural network model has high calculation accuracy, which can accurately set CSP finishing mill reduction procedures.

关 键 词：CSP BP人工神经网络 压下规程 

分 类 号：TG335.1[金属学及工艺—金属压力加工]