基于RLS自适应滤波器的针织圆纬机旋转周期预测方法

Rotary Cycle Prediction of Circular Knitting Machine Based on RLS Adaptive Filter

针对国内针织圆纬机在实时生产中的智能疵点检测问题,依据图像定量分析方法,提出基于递归最小二乘法(Recursive least square,RLS)自适应滤波器的旋转周期预测方法。介绍了应用RLS算法进行周期预测的背景及工业应用价值,对RLS算法和进行周期预测的RLS滤波器的基本工作原理进行了详细的分析。最后,根据针织圆纬机上下位系统,在双面机实时生产中获取预测所需要的实际周期数据,对实际周期使用RLS滤波器处理,寻找RLS滤波器最佳阶数。在最佳阶数基础上,设计RLS自适应滤波器的周期预测方法和单步周期预测方法对比实验,证明RLS滤波器对圆纬机旋转预测周期的稳定性优于单步预测方法。结合两种方法的不同优势,得到了适用于工业现场实时控制的智能疵点检测系统周期预测处理机制。

Aiming at the problem of intelligent defect detection for the circlular knitting machine in real-time production in China,according to the method of image quantitative analysis,a rotary cycle prediction method based on recursive least squares(RLS)adaptive filter is put forward.The background and the value of industrial application of using RLS algorithm to cycle prediction are firstly introduced.Secondly,the RLS algorithm and the basic working principle of RLS filter of using cycle prediction are analyzed in detail.Finally,in the real-time production of two-sided machine,the real cycle data needed for the prediction is obtained according to the up-down system of circular knitting machine.The real cycle is dealt by using the RLS filter to find its optimal order.On the basis of the best order,contrast experiments of cycle prediction of RLS adaptive filter and one-step cycle prediction are designed to prove that the RLS filter for circular knitting machine rotating cycle stability is superior to the one-step prediction method.Combining the different advantages of the two methods,the cycle prediction processing mechanism of an intelligent defect detection system is obtained,which is applied to the real-time control of industry site.