基于近红外光谱分析技术的液态水性油墨印刷品颜色预测模型

针对印刷品颜色离线检测存在滞后、检测不精准等问题，提出基于近红外光谱分析技术的液态水性油墨印刷品颜色预测模型。用多元散射校正（MSC） 、标准正态变换（SNV）和卷积平滑滤波器（SG）对原始光谱数据进行预处理，将原始光谱数据及预处理后的光谱数据分别与印刷品的Lab值建立偏最小二乘回归（PLSR）和主成分回归（PCR）两种预测模型。结果表明，基于MSC预处理的PLSR预测模型的预测精度最高，L、a、b值的R2分别高达0.9885, 0.9879和0.9938，预测颜色的平均色差约为0.71。液态水性油墨的近红外光谱可以精确预测印刷品颜色，为印刷品的在线检测提供了新思路。

Color Prediction Model of Liquid Water-Based Ink Based on Near-Infrared Spectroscopy

Aiming at the problems of lag and imprecision in off-line color detection of printed material, a color prediction model of liquid water-based ink based on near-infrared spectroscopy was proposed. Multivariate Scatter Correction (MSC), Standard Normal Variate (SNV) and Savitzky-Golay filter (SG) were used to preprocess the original spectral data. Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR) prediction models were established for the original spectral data and the preprocessed spectral data with the Lab value of the printed material respectively. The results show that the prediction accuracy of PLSR prediction model based on MSC preprocessing is the highest, R2 of L, a and b are up to 0.9885, 0.9879 and 0.9938 respectively, and the average color difference of predicted colors is 0.71. Near infrared spectroscopy of liquid water-based ink can accurately predict the color of printed material, which provides a new idea for online detection of printed material.