Color-matching model of digital rotor spinning viscose mélange yarn based on the Kubelka–Munk theory

Abstract

The color-matching model is conducive to expanding the scope of application of colorful fabrics and can speed up the achievement of intelligent production. To solve the problem in which the existing color-matching system of intelligent colored spun yarn cannot be applied to the digital rotor-spinning products of dope dyed viscose fiber, 66 types of mélange yarn were spun with a digital rotor-spinning frame using red, yellow, and blue dope dyed viscose fibers at a ratio gradient of 10%. Furthermore, the knitted fabric samples were produced using a circular machine. Meanwhile, a Datacolor 650 spectrophotometer was used for color testing, and the experimental results were recorded. Based on the color-matching model of the Kubelka–Munk theory, a color-matching model is built based on the experimental results. In addition, the accuracy of the model was analyzed and verified using the least-squares and relative value methods. The results show that, compared with the relative value method, the color-matching model constructed using the absorption coefficient K value and scattering coefficient S value calculated based on the least-squares approach is more accurate. The error between the predicted ratio of the test sample and the actual ratio was only 0.0979, the average color difference was only 0.465, and there were no visible differences between the predicted color of the sample and the actual color.