中厚板生产的高精度轧制力短期自学习  

High Precision Short-Term Self-Learning of Rolling Force in Plate Rolling Process

作　　者：祝夫文[1] 胡贤磊[1] 赵忠[1] 刘相华[1] 

机构地区：[1]东北大学轧制技术及连轧自动化国家重点实验室,辽宁沈阳110004

出　　处：《东北大学学报（自然科学版）》2008年第7期980-983,共4页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(50604006)

摘　　要：针对国内大多数企业没有安装测厚仪的现状,提出了中厚板生产中无测厚仪下的高精度轧制力自学习模型.模型通过自然对数法进行厚度族的划分,并将用于轧制力自学习的变形抗力参数按照不同的厚度族进行区分,最后模型采用了指数平滑法对各个厚度族内的变形抗力参数进行处理.以高精度弹跳模型为基础,提出将末道次实际出口厚度锁定为目标值的思想进行了各道次变形抗力参数的回归.将该模型实际应用于国内某3 000 mm轧机的过程控制系统中,获得了良好的效果.At the present condition that most of China＇s plate mills have no gauge-meter, a high-precision self-learning model is therefore developed for the rolling force in plate rolling process without gauge-meter. With the natural logarithm applied to the division of layers of thickness, the division of deformation resistance parameters is carried out according to different layers of thickness to solve the self-learning of rolling force. Then, the method of exponential smoothing is introduced into the model to deal with the deformation resistance parameters of each and every layer of thickness. Based on the high precision spring model, a new approach is proposed that the workpiece thickness after last rolling pass or at exit is set as the target thickness so as to regress the deformation resistance parameters which have been rolled via all scheduled passes. The model has been applied to the process control system of a 3 000 mm plate mill in China with favorable result obtained.

关 键 词：中厚板 轧制力自学习 测厚仪 厚度族 弹跳模型 

分 类 号：TG335.5[金属学及工艺—金属压力加工]