Abstract:

In order to realize the automation detection of fiber glass bobbin yarn hairiness,a fiber glass bobbin yarn hairiness detect system based on machine vision was designed. First,image acquisition platform was built to obtain the hairiness images by applying the light source,camera,motor,et al. Then,the region of hairiness was extracted by the Binary large object analysis method,then the moment features of contours and the region features were calculated,and the hairiness classification was performed by combining these features and the support vector machine. Finally,the numbers of different types hairiness were obtained according to the results of classification and the difference of the coordinates between the previous and latter frames. At the same time,the data of the hairiness length in each frame was obtained by the minimum bounding rectangle of the hairiness,and the maximum value was regarded as the corresponding hairiness length. The experimental results show that the system can replace the manual detection of the bobbin yarn hairiness effectively,and the detection of a single bobbin yarn takes less than ten seconds,which can meet the industrial demand.

Key words: fiber glass, machine vision, bobbin yarn, hairiness detection, hairiness classification