基于可见/近红外光谱的水性油墨助剂类型鉴别与浓度的定量分析  

Type Identification and Concentration Quantitative Analysis of WaterBased Ink Additives Based on Visible/Near-Infrared Spectroscopy

作　　者：白永利 黄新国[1] 张姗姗[1] 冷娴 钟云飞[1] 瞿小阳 谢小春 彭楠 Bai Yongli;Huang Xinguo;Zhang Shanshan;Leng Xian;Zhong Yunfei;Peng Nan(School of Packaging and Materials Engineering,Hunan University of Technology,Zhuzhou 412007,Hunan,China;Hunan Luck Printing Co.,Ltd.,Changsha 410100,Hunan,China)

机构地区：[1]湖南工业大学包装与材料工程学院,湖南株洲412007 [2]湖南福瑞印刷有限公司,湖南长沙410100

出　　处：《激光与光电子学进展》2022年第23期273-279,共7页Laser & Optoelectronics Progress

基　　金：国家自然科学基金青年基金(52004087);湖南省自然科学基金(2021JJ30218)。

摘　　要：针对目前水性油墨印刷适性难以准确检测和控制的问题,提出一种基于可见/近红外光谱结合化学计量学方法,准确检测水性油墨助剂的类型和浓度。首先,采用微型光谱仪(波长范围380~980 nm)获取水性油墨样本中含有不同浓度的乙醇、调色红和调色黄助剂的光谱数据,通过主成分分析法提取可完全表征样本光谱信息的特征波段,减少冗余信息,实现助剂类型的准确鉴别。然后,通过比较和讨论6种不同预处理方法结合偏最小二乘法、间隔偏最小二乘法(iPLS)构建的各助剂浓度预测模型。实验结果表明,通过主成分分析法,在617~726 nm光谱波段的前两个主成分累积贡献率高达99.909%,可实现对水性油墨助剂类型的准确判别。同时,通过比较分析发现,经过一阶导数和高斯窗平滑预处理后,在380~500 nm范围内,基于iPLS构建的各助剂浓度的预测模型,均达到了较好的预测效果。其中,乙醇助剂预测模型的决定系数和均方根误差分别为0.9798、0.0223,调色黄助剂的决定系数和均方根误差分别为0.9870和0.0075,调色红助剂的预测结果决定系数和均方根误差分别为0.9948和0.0038。实验证明,最优预处理方法结合iPLS建立的预测模型最优,可以准确检测水性油墨助剂的类型和浓度,满足水性油墨在印刷生产过程中检测与控制的应用需要,为后期实现水性油墨在线智能检测提供了技术基础。To address the current problem that the printability of water-based inks is difficult to detect and control accurately,a method based on visible/near-infrared spectroscopy combined with chemometrics is proposed to accurately detect the type and concentration of water-based ink additives.First,a micro-spectrometer(380-980 nm)was used to obtain spectral data of water-based ink samples containing different concentrations of alcohol,toning red,and toning yellow additives,and by extracting the characteristic bands that can completely characterize the spectral information of the samples through principal component analysis,redundant information is reduced and accurate identification of the auxiliary types is achieved.Then,the prediction models constructed by six different pretreatment methods combined with partial least squares(PLS)and interval partial least squares(iPLS)for each additive concentration were compared and discussed.The experimental results showed that the cumulative contribution rate of the first two principal components in the spectral band of 617-726 nm was as high as 99.909%by principal component analysis,and the accurate identification of waterbased ink additives types was achieved.Among them,the determination coefficient and root mean square error of alcohol additive prediction model were 0.9798 and 0.0223,while the determination coefficient and root mean square error of toning yellow additive were 0.9870 and 0.0075,and the determination coefficient and root mean square error of the toning red additive were 0.9948 and 0.0038.Experimental results prove that the model established by the optimal pretreatment method combined with the iPLS method is generally better than the single PLS model,which can accurately detect the type and concentration of water-based ink additives,meet the application needs of water-based ink detection and control in the printing production process,and provide a technical basis for the later realization of online detection of water-based ink.

关 键 词：光谱学 可见/近红外光谱 水性油墨 主成分分析 间隔偏最小二乘法 

分 类 号：O657.3[理学—分析化学]