基于统计回归分析的松散回潮出口含水率精准控制系统

Precise control system for moisture content in strips out of loosening and conditioning process step based on statistical regression analysis

为解决松散回潮工序片烟出口含水率控制精度低、过程控制能力弱等问题,通过对松散回潮工序历史数据进行统计回归分析,建立了松散回潮出口含水率精准控制模型,并采用自学习算法对控制模型进行了自适应优化调整。选取南阳卷烟厂"红旗渠(天行健)"牌卷烟松散回潮的在线监测样本数据,对该控制系统的应用效果进行验证,结果表明:改进后出口含水率的控制精度显著提高,过程偏移量减少0.24%,标准偏差和极差分别减小0.078%、0.34%,过程能力指数提高0.54,有效提高了生产过程控制水平。该方法为提高制丝生产过程批次内质量稳定性提供了支持。

In order to promote the control precision of moisture content in strips out of loosening and conditioning process step, a precise control model was developed following the statistical regression analysis of historical data of the said process step, and further revised for self-adaptive optimization with self-learning algorithm. The control system was validated with the data of on-line monitoring samples of ＂Hongqiqu（Tianxingjian）＂cigarette brand in Nanyang Cigarette Factory. The results showed that： the control precision of moisture content in output strips was significantly improved, process deviation, standard deviation and extreme difference decreased by 0.24%, 0.078% and 0.34%, respectively; process capability index increased by 0.54. It indicated that the level of process control was effectively improved. This method provides a support for the promotion of intra-batch quality consistency in tobacco primary processing.