文章摘要
张宜洋,郭凌华,武城运,海敬溥,王荣欣,陈睿.基于密度的凹版专色叠印色光谱预测模型的研究及应用[J].包装工程,2024,45(5):247-253.
ZHANG Yiyang,GUO Linghua,WU Chengyun,HAI Jingpu,WANG Rongxin,CHEN Rui.Research and Application of Spectral Prediction Model of Gravure Spot Color Overprint Color Based on Density[J].Packaging Engineering,2024,45(5):247-253.
基于密度的凹版专色叠印色光谱预测模型的研究及应用
Research and Application of Spectral Prediction Model of Gravure Spot Color Overprint Color Based on Density
投稿时间:2023-07-10  
DOI:10.19554/j.cnki.1001-3563.2024.05.030
中文关键词: 专色叠印  油墨密度  光谱反射率  预测模型
英文关键词: spot color overprint  ink density  spectral reflectance  prediction model
基金项目:陕西省重点研发计划资助(2020GY-320);陕西省西安市未央区科技计划项目(201825,201862)
作者单位
张宜洋 陕西科技大学 轻工科学与工程学院西安 710021
中国轻工业功能印刷与运输包装重点实验室西安 710021 
郭凌华 陕西科技大学 轻工科学与工程学院西安 710021
中国轻工业功能印刷与运输包装重点实验室西安 710021 
武城运 陕西科技大学 轻工科学与工程学院西安 710021
中国轻工业功能印刷与运输包装重点实验室西安 710021 
海敬溥 陕西科技大学 轻工科学与工程学院西安 710021
中国轻工业功能印刷与运输包装重点实验室西安 710021 
王荣欣 陕西科技大学 轻工科学与工程学院西安 710021
中国轻工业功能印刷与运输包装重点实验室西安 710021 
陈睿 陕西科技大学 轻工科学与工程学院西安 710021
中国轻工业功能印刷与运输包装重点实验室西安 710021 
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中文摘要:
      目的 建立一种基于密度与光谱反射率关系的专色叠印色光谱预测模型。方法 首先建立前景色、后景色密度与其光谱反射率关系;基于此建立叠印色光谱反射率的计算方法;其次对模型进行优化,完成专色叠印色光谱预测模型的建立;再通过凹版印刷实打样30张专色叠印色样张,基于Malab利用色差以及拟合决定系数R2对预测模型进行验证;最后在相同工艺条件下实打样专色叠印色样张进行预测,通过色差完成对模型的精度检验。结果 验证表明,不同专色叠印色在同一网点面积率下与其对应的前景色、后景色密度之间存在较强相关关系,其拟合决定系数R2均大于0.9;模型精度检验中,73.7%的模型预测值与样张实测值色差为0~2.5个CIE1976色差单位,大部分色块色差为0~2个CIE1976色差单位,占总频率的60.54%,整体平均色差为1.92个CIE1976色差单位。结论 本文所建模型具有较高的预测精度,能基本满足对颜色预测的需求。
英文摘要:
      The work aims to establish a spectral prediction model of spot color overprint color based on the relationship between density and spectral reflectance. Firstly, the relationship between front and back scene density and spectral reflectance was built according to the density definition formula. Based on this, a calculation method of spectral reflectance of overprint color was constructed. Secondly, the model was optimized, and the spectral prediction model of spot color overprint color was established. 30 spot color overprint color samples were printed by gravure. Based on Malab, the prediction model was verified with color difference and fitting coefficient R2. Finally, another batch of spot color overprint color samples were printed under the same process conditions, and the accuracy of the model was checked by color difference. The experimental results showed that under the same dot area rate, there was a strong correlation between different spot color overprint color and its corresponding front and back scene density, and the fitting coefficient R2 was greater than 0.9. In the accuracy test of the model, the color difference between the predicted value of the model and the measured value of the sample was between 0 and 2.5 CIE1976 for 73.7%, and the color difference between the majority of the color blocks was between 0 and 2 CIE1976, accounting for 60.54% of the total frequency. The overall average color difference was 1.92 CIE1976. Therefore, the model proposed has high prediction accuracy and can basically meet the demand for color prediction
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