【作者】 李启正；

【导师】 祝成炎；

【作者基本信息】 浙江理工大学 ， 纺织工程， 2015， 博士

【摘要】 机织产品开发中,将数种颜色的纱线通过不同的组织结构和经纬工艺进行交织,可获得丰富的织物颜色效果。交织混色技术以往主要应用在条格和大提花织物的颜色设计中,本课题致力于将交织混色技术推广应用到服用或家用有色面料的生产开发中,使交织混色技术能够替代部分织物的染色工艺。目前,限制其推广使用的主要瓶颈在于交织混合颜色的准确控制和精确预测。为研究色纱并置颜色混合的特点和规律,解决交织混色织物设计中存在的颜色数目限制,预期颜色与实际颜色不符合,传统配色方法费时费力等问题,课题以原液着色涤纶长丝及其交织织物为例,建立了交织混色织物颜色评价方法、构建了颜色预测模型、探明了交织混色规律和开发了测配色系统。以期为交织混色技术的进一步推广应用奠定理论基础和提供实际参考,继而推动节水或免染纺织品的发展,实现CO2和印染废水的减排。(1)为探讨适用于色纱和交织混色织物颜色评价的正确方法,并为下一步的颜色预测模型和颜色混合规律研究打好基础,本文比较了不同测色方法和仪器设备用于不同类型色样颜色评价的适用性和局限性,提出了不同形态纱线色样及交织混色织物色样的颜色评价方法。研究发现:数码成像测色法由于原理上的限制,存在一定的色域缺陷,但通过视觉评判分析可知,其较符合交织混色织物的视觉观察的结果;本研究中,校准后的数码成像测色系统和分光光度测色系统用于纸质色卡的颜色测试时,能够获得较为一致的颜色评价(?E00=0.79);但当它们用于非平整表面的染色织物的颜色评价时,会出现一定的颜色差异(?E00=2.19);用于交织混色织物的颜色评价时,色彩差异进一步增大(?E00=3.25),但色彩差异与织物的细密程度和测试时的折叠层数有关。研究认为:数码成像测色系统适用于大批量或无法形成测色平面的纱线及织物样品的颜色评价,在进行交织混色织物的测配色研究时,建议采用分光光度法。(2)为建立具有更好适应性和更高精度的交织混色织物颜色预测模型,本文以原液着色涤纶长丝交织混色织物为例,建立了单组纬和双组纬交织织物的修正几何结构模型,提出了交织混色织物表面色纱和间隙覆盖率的理论计算方法,并根据理论色纱覆盖率与实际色纱覆盖率之间的迭代与逼近计算,提出了几何结构模型中纱线压扁系数的计算方法,最后采用多种模型进行了验证;本文以色度学理论和Kubelka-Munk的二光通理论为基础,基于织物实际测量的光谱反射率数据,提出了一个带经验系数和中间函数的新模型用于交织混色织物的颜色预测,并采用牛顿迭代确定了经验系数。课题织造了不同规格和经纬密度的原液着色涤纶长丝交织织物用于模型的验证,预测颜色值与实测颜色值之间的色差统计表明,新模型在不同波长范围内具有不同的预测精度,但整体预测精度明显高于现有方法和模型,适用性良好。(3)为得到纱线交织混色的最佳原色组合、互补色及色度规律,本文选取现有纱线色样中的最接近理想原色的6种,设计并织造了288块原色纱线交织织物,并从色域分布角度展开讨论,交织混色织物实际颜色在CIE1976色度图中的分布规律表明:在RGB、CMY、NCS和RGBCMY等原色组合中,RGBCMY原色组合可以在不增加过多原色的前提下获得相对完整和较大的色域;在Gabrijel?i?等的研究基础上,本文研究发现,在CIE 1976色度图中,交织混色织物颜色坐标基本分布在其交织原色坐标的连线上,其具体位置由织物表面色纱的覆盖率决定。通过对交织混合规律的研究,本文提出了交织混色的原色选取原则,归纳了交织混色的互补色规律;通过实测数据的拟合分析,得到了CIE 1976色度图中交织混色织物位置系数和色纱覆盖率之间的理论和实际关系式,并得到了明度差系数和色纱覆盖率之间的理论和实际关系式。(4)基于矩阵计算和VB程序开发环境,本文将新模型用于交织混色织物的颜色预测及配色实践,得到了织物表面色纱覆盖率与织物组织结构、经纬密度、纱线线密度之间的换算方法,结合经纬纱线的颜色配置,形成交织混色织物的测配色系统。测配色系统能够对色纱混合的颜色进行准确预测,还能从织物最终呈现颜色进行反向推导,在既定的经纬纱线组合下,得到合理的织物表面色纱覆盖率,并最终推导得到相应经纬覆盖率的经纬纱线颜色比例和线密度、织物经纬密度和组织。目前,交织混色织物颜色预测模型在预测精度和适用性方面还存在不足,尚未建立成熟的理论体系和实用有效的测配色方法;本研究查询到的文献及著作中,从色域分布角度开展对交织混合原色、互补色及色度规律的研究仍为空白。本课题基于修正的织物几何结构模型,提出的交织混色织物颜色预测模型由于带有经验系数和中间函数,对织物表面的色纱覆盖率和织物经纬原料的形态特征等都具有较好的修正作用,在预测精度和适用性方面都优于以往固定形式的颜色预测模型;基于可靠的颜色评价方法和色域分布分析,得到的交织混合最佳原色组合和颜色规律,对于全色系交织混色织物的设计开发具有重要的指导意义;颜色预测新模型的应用实践可为机织物测配色系统的进一步开发提供可借鉴的算法和程序,本课题是纺织工程和色度学及计算机技术相结合的一个新的研究领域。更多还原

【Abstract】 During the woven fabric development, the interweaving of colored yarns of several colors through different weave structures and weaving processes can enable fabrics to gain rich color effects. Interwoven technology was mainly used in the color design of yarn-dyed check fabrics and jacquard fabrics in the past. This study is committed to applying interwoven technology to the production and development of chromatic clothing or household textile fabrics so that it can replace dyeing process of some fabrics. The main bottleneck restricting its promotion and use is exact control and accurate prediction of color. In order to study the mechanism and laws of colored yarn interweaving, solve problems such as a limited number of colors, inconsistency between the expected color and actual color in product design, traditional color matching process of fabric sample is time-consuming and laboursome, this study takes dope dyed polyester filament yarn and its interwoven fabrics for example and conducts researches on color evaluation of interwoven color mixing fabrics, color prediction model building, analysis of interwoven color mixing laws and color measurement and matching system development so as to lay a theoretical foundation and provide practical references for the further promotion and application of interwoven color mixing technology and then greatly promote the development of water saving or waterless dyeing textiles and realize emission reduction of printing and dyeing wastewater and carbon dioxide.(1) In order to explore the most suitable color evaluation method for colored yarn and interwoven color mixing fabrics and lay a foundation for color prediction model building and color measurement and matching system research, this paper compares the applicability and limitations of different color measurement methods and equipment used in color evaluation of different color samples, and proposes color measurement methods for different forms of colored yarns and color samples of interwoven color mixing fabrics. In this research, visual method, spectrophotometric method and digital image color measurement method are applied to color evaluation of paper color card and color samples of dyed fabrics and interwoven color mixing fabrics at the same time. Parallel comparison shows that: as a result of limitations of principle, digital image color measurement system has certain color gamut defects; but visual evaluation and analysis show that it more corresponds to the visual observation result; calibrated digital image color measurement system and spectrophotometric color measurement system can obtain consistent color evaluation results(?E00 = 0.79) when they are used for color measurement of paper color card; but color differences will emerge when they are used for color evaluation of dyed fabrics without flat surface(?E00 = 2.19); color differences further increase when they are used for color evaluation of interwoven mixing fabrics(?E00 = 3.25). In addition, color difference is related to the fine degree and folded layers in tests. As a conclusion, digital image color measurement system is more suitable for color evaluation of large-batch and non-planar yarn or fabric samples; but in the study of color measurement and matching, spectrophotometric method used to measure the reflectivity spectrum of color samples is recommended.(2) In order to build more accurate interwoven color prediction model, this study chooses dope dyed polyester filament interwoven fabric as example, constructs modified geometric structure models of single and double weft interwoven fabrics, proposes the theoretical calculation method of surface dyed yarn and gap coverage rate of interwoven color mixing fabrics, puts forward the theoretical calculation method of flattening coefficient of yarns in the geometric structure model through iteration and approximation calculation between actual and theoretical dyed yarn coverage rates, and conducts verification with multiple models. Based on the colorimetry theory and Kubelka-Munk theory and spectral reflectance data of fabrics measured practically, a new model with empirical coefficient and intermediate function, which can be applied to the color prediction of interwoven color mixing fabrics, is proposed and the empirical coefficient is determined with Newton iterative algorithm. Interwoven fabrics with different specifications and thread counts are made for model verification. Statistics of color difference between predicted and measured color values shows that, the new model has different prediction accuracy in different wavelength ranges, but the overall prediction accuracy is much higher than existing models and methods.(3) In order to obtain the optimal primary color combination, complementary colors and chromaticity laws of interwoven color mixing yarn, this paper selects 6 yarns of primary color most approximate to the ideal primary color and designs and makes 288 pieces of interwoven fabrics of primary color yarn and conducts discussions from the perspective of color gamut distribution. The distribution law of actual colors in CIE1976 chromaticity diagram shows that, among primary color combinations such as RGB, CMY, NCS and RGBCMY, only RGBCMY primary color combination can obtain a relatively complete and large color gamut without adding excessive primary colors. On CIE1976 chromaticity diagram, color coordinates are basically distributed on the connected line of primary color coordinates and their specific positions are determined by the coverage rate of dyed yarn on the fabric surface. Through the study on interwoven color mixing law, this paper proposes the selecting principle of primary color, summarizes complementary color laws of interwoven color mixing, and obtains theoretical and practical relational expressions between position coefficient and dyed yarn coverage rate in CIE 1976 chromaticity diagram and those between lightness difference coefficient and dyed yarn coverage rate through fitting analysis on measured data.(4) Based on matrix calculation and VB software development environment, the new model is applied to color prediction and matching practice of interwoven color mixing fabrics. Therefore, the method for conversion among dyed yarn coverage rate on the fabric surface and weave structure, thread count and linear density is obtained. In combination with color setting of weft and warp, color measurement and matching system of interwoven color mixing fabrics is formed. The system can forecast the color of dyed yarn mixture accurately, obtain the reasonable dyed yarn coverage rate on the fabric surface under a given weft and yarn combination through backward derivation based on the final color of fabrics, and finally obtain the warp and weft color of the corresponding weft and warp coverage rate, thread count and weave structure.At present, systematic research of interwoven color mixing laws and prediction accuracy of interwoven color prediction models still have many deficiencies; mature theoretical system and effective color measurement and matching method haven’t been built yet; among literatures and works available in this thesis, research on yarn color mixing law from colorimetric perspective is still blank. Benefited from empirical coefficient and intermediate function, the color prediction model of interwoven color mixing fabrics put forward in this study based on the modified fabric geometric structure model has certain correction function for dyed yarn coverage rate on the fabric surface and morphological characteristics of warp/weft raw materials. The prediction accuracy and applicability of the new model are much higher than previous interwoven color prediction models with fixed forms. The optimal primary color combination and color mixing law obtained based on reliable color evaluation method and color gamut distribution analysis have important guiding significance for the design and development of full color interwoven fabrics. The application practice of the new model of color prediction provides valuable algorithm and program and is a new research area with the combination of textile engineering, colorimetry theory and computer technology.更多还原