摘要
文章通过对某1700热轧带钢生产线立辊短行程模型的解析和参数优化,通过投入神经网络自学习等措施,使带钢头尾失宽或超宽超过4 mm的比例由优化前的13.6%降低到了优化后的3.4%。通过现场数据测量,统计出板坯头尾失宽量与板坯宽度、厚度和立辊压下量的对应关系。
Through the analysis and parameter optimization of the vertical roll short stroke model of a 1700 hot strip production line,and through the input of neural network self-learning and other measures,the proportion of strip head and tail width loss or super width exceeding 4 mm is reduced from 13.6%before optimization to 3.4%after optimization.Through field data measurement,the corresponding relationship between slab head and tail width loss and slab width,thickness and vertical roll reduction is counted.
作者
吕小虎
王瑞
金鑫
令狐克志
Lyu Xiaohu;Wang Rui;Jin Xin;Linghu Kezhi(Tangshan Iron and Steel Co.,Ltd.of Hegang Group,Tangshan Hebei 063000)
出处
《现代工业经济和信息化》
2021年第8期62-64,共3页
Modern Industrial Economy and Informationization
关键词
立辊
短行程
模型
vertical roll
short stroke
model