摘要
提出了一种光谱重叠的多种矿物油混合物组分含量测定的新方法。将偏最小二乘方法(PLS)推广至三维扩展(tri-PLS),不需要解决特征值问题。利用该方法对柴油、汽油和煤油混合物的三维荧光光谱进行研究,根据样本序列、激发波长、发射波长构造出三维数据矩阵,结合浓度矩阵应用tri-PLS法建立校正模型,对实验样本进行预测,实验结果表明tri-PLS方法的建模精度比常用的平行因子法优越。
A new method which extend the partial least squares （PLS） method to three-dimensional （tri-PLS） and don＆#39;t need to care about the eigenvalue is presented to determinate the content of a variety of mineral oil mixture with overlapping spectra . This method is used to study the three-dimensional fluorescence spectra of the mixture of diesel ,gasoline and kerosene .The 3D data matrix is constructed on the basis of the sample sequence ,the excitation wavelength and the emission wavelength .The com-bination of 3D data matrix and the concentration matrix can be modeled by tri-PLS to predict the test samples .The experimental results show that the modeling precision of tri-PLS is superior to PARAFAC .
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2017年第12期3771-3775,共5页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(61471312)
河北省自然科学基金项目(F2015203240
F2015203072)资助
