纺织学报 ›› 2017, Vol. 38 ›› Issue (12): 27-32.doi: 10.13475/j.fzxb.20161204707

• 纺织工程 • 上一篇    下一篇

数码转杯纺的Stearns-Noechel配色模型

  

  • 收稿日期:2016-12-26 修回日期:2017-05-24 出版日期:2017-12-15 发布日期:2017-12-18

Stearns-Noechel color matching model of digital rotor spinning

  • Received:2016-12-26 Revised:2017-05-24 Online:2017-12-15 Published:2017-12-18

摘要:

为研究数码转杯纺的配色规律,纺制红、黄、蓝三原色棉纤维混纺纱,测试样本的光谱反射率,用经典方法确定两组分和三组分样本Stearns-Noechel 模型参数,考虑波长因素优化模型参数,并根据优化参数和波长线性相关、分段相关2种方式简化参数。结果显示:引入波长后二组分样本平均色差由2.7 降至1.48,三组分样本平均色差由3.32降至1.66,优化效果显著;优化参数和波长线性相关时,2类样本平均色差增大到3.59和4.56,不能满足基本配色需求;优化参数和波长分段相关时,2类样本平均色差为1.54和1.91,优于经典算法的预测效果;此外,Stearns-Noechel 模型对二组分样本的颜色预测能力准确性高于三组分样本。

关键词: 数码转杯纺, 配色, Stearns-Noechel 模型, 参数优化

Abstract:

In order to study the color matching principles for digital rotor spinning, Red, yellow and blue three primary colors cotton fiber are used to spin blended yarn, and measure the spectral reflectance of the samples with datacolor colorimeter. The Stearns-Noechel model parameters M of the two-component and three-component samples were determined by classical way,model parameter M is optimized considering the wavelength factor. Then the parameter M is simplified according to the optimal parameter M and the wavelength are linely related or segment-related. The study show that the average color difference of the two-component and three-component sample decreases from 2.7 to 1.48 and from 3.32 to 1.66 using the optimal parameter M, and the optimal parameter M has significant effect. The study also show that when the optimal parameters M and the wavelength are linearly related, the average color difference of two categories samples increases to 3.59 and 4.56, which can’t satisfy color matching needs, and when the optimal parameter M and the wavelength are segment-related, the average color difference of two categories samples is 1.54 and 1.91, better than the result of the classical algorithm. At the same time research find that Stearns-Noechel model has different color prediction ability for two-component and three-component samples, the prediction accuracy of two-component samples is better than that of three-component samples.

Key words: digital rotor spinning, color matching, Stearns-Noechel model, parameter modification

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