Detection of Wrapping Defects by a Machine Vision and Its Sensitivity to the Process Variables in a Ring Core-spinning System

Abstract

A core-spun yarn can be understood as a cross-sectionally structured composite yarn in which the core strands are wrapped by staples. The quality of the core-spun yarns is thus determined by the structural characteristics, when the core filaments are steadfast located in the center of the yarn and well covered by the sheath-staples. A variety of core-spun yarns can be obtained by combining various staples with different kinds of functional filaments that can show better mechanical and thermal performance. Therefore numerous functional and innovative yarns can be manufactured, complementing individual ingredients. Nowadays the ring spinning technology is widely applied to manufacture staple yarns because of its simplicity of the principle and the good quality of the products. However, applying the ring spinning principle to the core-spinning often causes some problems in the yarn; for example, the aesthetic defects similar to "barberpole" due to the asymmetrical location of the sheath staples and the altering position of the core filaments, or slip-out of the sheath fibers from the yarn while being used. In this study we are going to analyze the effect of process variables on the cross-sectional arrangement of the constituents for reducing the aesthetic defects and optimizing the process conditions. We check the feasibility of using a machine vision to detect the defects on the yarn surface. Experimental results show that a twist among process variables was the most sensitive factor to the defects, while the input bundle thickness being the least. The frequency of defects on the yarn surface changes distinctively according to the process variables with different weighting factors.