为了提高多组分混合物太赫兹光谱定量分析的准确性和稳定性, 将Tchebichef图像矩结合偏最小二乘回归(PLS)的建模方法引入到太赫兹光谱定量分析中, 以橡胶添加剂氧化锌、白炭黑与丁腈橡胶的混合物为实验样本, 对混合物中的氧化锌进行定量分析。获取样本太赫兹吸光度数据后, 用3维光谱自构建方法构建样本的3维光谱, 利用Tchebichef图像矩提取样本3维光谱灰度图的特征信息, 然后用PLS建立定量模型对氧化锌进行定量分析。结果表明, 由本方法得到的样本预测集相关系数和均方根误差分别为0.9993和0.0351, 与用PLS和支持向量回归直接对吸光度数据进行建模的方法相比, 结果更加准确和稳定。本方法能够对混合物中氧化锌进行准确、稳定的定量分析, 为多组分混合物太赫兹光谱定量分析提供了新思路。

In order to improve the accuracy and stability of terahertz spectroscopic quantitative analysis of multicomponent mixtures, Tchebichef image moment combined with partial least squares (PLS) regression modeling method was introduced into terahertz spectral quantitative analysis. The mixture of rubber additive zinc oxide, silica and nitrile-butadiene rubber was used as experimental sample. The zinc oxide in the mixture was quantitatively analyzed. After obtaining the terahertz absorbance data of the sample, 3-D spectra of samples were constructed by self-construction method of 3-D spectra. Tchebichef image moments were used to extract the feature information of the 3-D spectral gray image of the sample. Then a quantitative model was established by PLS to quantitatively analyze zinc oxide. The experimental results show that, the correlation coefficient and root mean square error of the sample prediction set obtained by this method are 0.9993 and 0.0351, respectively. Compared with the absorbance data modeling directly by PLS and support vector regression, the results are more accurate and stable. This method can be used for accurate and stable quantitative analysis of zinc oxide in mixtures. It provides a new idea for terahertz spectroscopic quantitative analysis of multicomponent mixtures.