Abstract
To facilitate the product design of hybrid multifilament fabric prior to spinning, a color prediction model was proposed. The monofilaments in the multifilament were assumed to have a square cross-section and stacked vertically. The prediction model considered the reflectance, transmittance and arrangement of the monofilaments in the fabric. To test the reflectance and transmittance of the monofilament with the Datacolor spectrophotometer, films with the same material and thickness as the monofilaments were made. 20 kinds of multifilaments with different blending ratios and fineness were produced and woven into fabrics. The color difference between the fabric color tested by the spectrophotometer and predicted by the new model and classical Kubelka-Munk (K-M) theory was calculated and compared. The result shows that the average color difference obtained by the new model was 1.02 Color Measurement Committee (CMC) (2:1) units, which was less than that of 1.78 CMC (2:1) units obtained by the K-M theory. Through Spearman correlation analysis, the fabric lightness and the multifilament fineness had a significant influence on the color difference, and the color difference decreased with the increase of them. Finally, the surface color of a fabric was reproduced, indicating the model can be used to characterize the phenomenon of uneven color mixing on the fabric surface.
摘要
为了便于原配色丝织物纺前设计,提出了一种颜色预测模型。假设复丝中的单丝具有方形截面并在复丝中垂直堆叠排列。预测模型考虑了单丝在复丝中的反射、透射以及排列方式。为了使用Datacolor测色仪测试单丝的反射率和透射率,制作了与单丝具有相同材质和厚度的薄膜。纺制了20种不同混色比和不同细度的单丝,并将其织成织物。使用分光光度计测试了织物真实的颜色,并分别计算了本颜色预测模型和K-M颜色预测模型预测的织物颜色与织物真实颜色之间的色差。结果表明,本颜色预测算法得到的平均色差为1.02 CMC (2:1)单位,小于K-M颜色预测模型得到的1.78 CMC (2:1)单位。通过斯皮尔曼相关性分析算法,发现织物亮度和复丝细度对本模型预测的计算色差有明显影响,即随着这两个因素的增加,色差逐渐增大。最后使用本颜色预测模型计算了织物表面颜色,表明本算法可以用于表征织物表面颜色不均匀程度。
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Foundation item: the National Natural Science Foundation of China (No. 61973127)
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Wang, Y., Li, W., Liu, J. et al. Color Prediction Model of Gray Hybrid Multifilament Fabric. J. Shanghai Jiaotong Univ. (Sci.) 28, 802–808 (2023). https://doi.org/10.1007/s12204-021-2326-0
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DOI: https://doi.org/10.1007/s12204-021-2326-0