基于大数据与卡尔曼滤波算法的切纸机速度自动化控制方法

Automatic Speed Control Method of Paper Cutter Based on Big Data and Kalman Filtering Algorithm

造纸技术的提升使人们对于纸张剪切质量的要求越来越高,为提升剪切纸张的品质,切纸机必须保持较高剪切精度,设计一种基于大数据与卡尔曼滤波算法的切纸机速度自动化控制方法。通过局部加权回归散点平滑法对切纸机非线性运行数据实施平滑处理。构建切纸机的非线性系统运动模型,代入处理后的非线性运行数据,完成模型最终搭建。设计切纸机速度观测器,运行步骤为初始化、采样、时间更新、测量更新,通过可编程逻辑控制器实现切纸机的速度自动化控制。测试结果表明,设计方法速度控制中的平均指令延迟时长均低于35ms,稳态控制精度测整体高于99%,操作次数为200次时,切纸机的最大切纸误差仅为0.318mm。

The improvement of paper making technology makes people more and more demanding on the quality of paper cutting.In order to improve the quality of paper cutting,the paper cutter must maintain a high cutting accuracy.An automatic speed control method of paper cutter based on big data and Kalman filtering algorithm is designed.The nonlinear operation data of paper cutter are smoothed by local weighted regression scatter smoothing method.Build the nonlinear system motion model of the paper cutter,substitute the processed nonlinear operation data,and complete the final model building.The paper cutter speed observer is designed.The operation steps are initialization,sampling,time update and measurement update.The automatic speed control of the paper cutter is realized through the programmable logic controller.The test results show that the average instruction delay duration in the speed control of the design method is less than 35ms,the steady⁃state control accuracy is higher than 99%as a whole,and the maximum paper cutting error of the paper cutter is only 0.318mm when the number of operations is 200.