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针对无缝钢管斜轧穿孔生产中衡量毛管质量好坏的毛管横向和纵向壁厚不均检验滞后和难以建立其机理模型的问题,提出了基于均值子时段MPLS方法的毛管质量预报模型。介绍了均值子时段MPLS方法中过程数据时段分解、均值求取、回归模型建立和模型在线预报等关键内容。将建立的预报模型用于毛管质量预报中,为斜轧穿孔生产的无缝钢管质量提高奠定了良好的基础,并且其维护费用低、实时性好、可靠性及精度高,可以用于毛管质量的在线预报和优化。
Aiming at the problem of lag in horizontal and vertical wall thickness measurement and the difficulty of establishing its mechanism model in the production of cross-rolling of seamless steel tubes, the capillary quality prediction model based on mean sub-period MPLS method is proposed. This paper introduces the key elements of process data, such as period decomposition, average value, regression model establishment and online forecast of model in the mean sub-period MPLS method. The established forecasting model is applied to the prediction of capillary quality, which lays a good foundation for improving the quality of seamless steel pipe produced by cross-piercing perforation, and has the advantages of low maintenance cost, good real-time, high reliability and high precision, and can be used for capillary quality Online forecasting and optimization.