一种设定记忆长度的轧辊偏心在线检测算法  

Online algorithm with memory range for identification of roll eccentricity

作　　者：吴巍[1] 张武军[2] 张晓彤[1] 钱艺[1] 

机构地区：[1]北京科技大学信息工程学院,北京100083 [2]北京科技大学机械工程学院,北京100083

出　　处：《北京科技大学学报》2009年第4期499-503,共5页Journal of University of Science and Technology Beijing

摘　　要：轧制控制过程中轧辊偏心信号是影响带钢厚度精度的重要因素.针对该类问题,将基于设定记忆长度的在线反向传播算法用于对偏心信号的检测.通过与普通在线反向传播算法在检测性能上的对比表明:该方法具有学习收敛速度快,抗噪声能力强等特点,可有效使变幅、变相和变频的偏心信号引起的厚度波动减少95%左右,从而准确地补偿由偏心信号引起的厚度偏差,提高轧钢过程中的带钢厚度精度.Roll eccentricity in rolling mills has an important influence on the delivery gauge of rolled strips. An online back propagation algorithm with memory range was used to identify roll eccentricity and compared with the simple online back propagation algorithm on identification. The results show that the roll eccentricity identification method with memory range has a faster convergence and a better anti-noise performance. It can make the thickness fluctuation decrease about 95 96 when the eccentricity＇s magnitude, phase and frequency change, consequently compensate thickness error induced by roll eccentricity and improve the delivery gauge of rolled strips effectively.

关 键 词：轧辊偏心 在线检测 记忆长度 反向传播算法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]