关键词: 色纺纱, Kubelka-Munk双常数理论, 颜色预测, 转杯纺纱, 反射率

Abstract: Due to the heavy workload and time-consuming and material-consuming of traditional manual color measurement and matching, color spinning technology came into being. Color spinning technology is a spinning technology that blends several colored fibers in a specific proportion to produce fashionable colors. The fabric and finished product made by using color spinning do not need to be dyed again and is considered a green ecological short process technology. However, due to the inability to freely control color during the spinning stage, the actual production and application of color spinning are greatly limited. To address this issue, a four primary color ternary coupling superposition full-color gamut grid-based color mixing model was first constructed, which can perform color phase control, brightness control, and chromaticity control within the full-color gamut range.
On this basis, combined with the characteristics of the Kubelka-Munk dual constant theoretical model, 84 grid point mixed sample formulas were selected from the constructed grid-based color mixing model, of which 54 mixed samples were used as measured samples. With a three-channel CNC rotor spinning machine as the platform, four primary colors of cyan (C), magenta (M), yellow (Y), and white (W) were used as raw materials. Based on the constructed full-color domain grid-based color mixing model and color mixing chromatography, we prepared actual spinning samples. Then, we measured the color values of 54 measured samples, and used the least squares method to calculate the K and S values of each primary color fiber, in order to achieve the prediction of full gamut color or primary color fiber mixing ratio. We also selected the remaining 30 mixed samples as prediction samples to verify the ability of the traditional Kubelka-Munk dual constant theory model to predict the color or primary color fiber mixing ratio. From the comparison between the predicted reflectance of the mixed samples and the actual reflectance, it is found that the predicted reflectance of some mixed samples is significantly lower than the actual reflectance. In response to the problem of insufficient prediction accuracy of traditional Kubelka-Munk double constant theory, the article proposes to reconstruct the Kubelka-Munk double constant theory model for color prediction, and then partially replace the part of the traditional method where the obviously mixed color yarn has a lower reflectivity than the actual reflectivity with the interpolation method. The results show that compared with the traditional Kubelka-Munk double constant theory, the average color difference of the reflectance predicted by the new method has been reduced from 1.48 to 1.04, and the color difference of all mixed samples can be controlled within 2.0. We use the least squares method to predict the monochromatic fiber blending ratio of ten mixed samples, and then substitute it into the Kubelka-Munk dual constant theoretical model to calculate the predicted reflectance. According to the CMC2:1 color difference formula, the color difference between the predicted reflectance and the actual reflectance of the ten mixed samples was obtained, with the minimum color difference being 0.18, the maximum being 0.91, and the average value being 0.45. As the mixing ratio changes, the color difference of the mixed samples fluctuates up and down within its average range, and the color difference is small. The prediction effect of the blending ratio is good. This prediction method has better prediction accuracy than the traditional Kubelka-Munk double constant theory. The constructed four primary color grid mixing model and Kubelka-Munk double constant theory model can be applied to predict the color mixing and mixing ratio of multi primary color fibers.

Key words: colored spun yarn, Kubelka-Munk dual constant theoretical, color prediction, rotor spinning, reflectivity