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针对冷轧带钢板形统计存在误差的问题,基于广义极值分布理论,采用拟合优度检验方法,建立了板形分档定级统计模型。对在线检测的板形数据进行拟合优度检验,然后选用合适的统计函数对带钢的板形进行统计,得到带钢的质量等级。对比传统的板形统计方法,该模型以某1050六辊可逆式冷轧机在线检测板形数据为研究对象,对其进行实时统计。结果表明,板形分档定级统计模型统计误差小,计算速度快,可在线实时显示板形统计结果,给带钢板形在线调控提供了准确的统计数据,从而提高了带钢的质量等级。
Aiming at the problem of the error of plate shape measurement in cold rolled strip, a statistical model of plate profile classification was established based on generalized extreme value distribution theory and goodness of fit test. The goodness of fit of the flatness data of the on-line inspection is tested, and then the statistic function of the strip is used to count the strip shape of the strip to obtain the quality grade of the strip. Compared with the traditional flat shape statistical method, this model takes the on-line plate shape data of a 1050 six-roller reversing cold rolling mill as the research object, and real-time statistics is carried out. The results show that the statistical error of plate classification and grading statistical model is small and the calculating speed is fast. The plate shape statistics can be displayed online and in real time, which provides accurate statistic data for strip shape control and thus improves the quality grade of strip steel.