Using Linear Mean and Variance Technique to Evaluate the Patterning in Random Winding Process

In random cone winding system, the patterningconcept results in many problems in further processes, e.g.yarn breakage and/or early take off of the package. incurrent winding machines, there is no system to detect thepatterning and consequently the anti-patterning system isworking continuously. in this research, an online-computervisionsystem is used to detect the concept of patterningthrough the linear mean and variance technique. in fact,photographs of bobbin surface are continuously taken withspecified time interval. in this way, the mean or variance iscalculated from columns within the image matrix, and avector is obtained. then again, the variance or the mean ofthe vector is calculated, thus a number is obtained for eachmatrix. therefore, there are four methods including mean ofmean (mom), mean of variance (mov), variance of mean(vom) and variance of variance (vov) to give the indexnumber. accordingly, a diagram of image number versusindex value is plotted for each method, and a peak isperceived in place of patterning defect. by finding this peak,the moment of occurrence of defect is diagnosed, and the“patterning” can be recognized. the results show that amongthe four methods, the mov is more accurate. finally, thisoutcome is mathematically analyzed.