三维荧光偏导数光谱结合平行因子算法对石油类混合油液的检测

石油类混合油液的组分检测是三维荧光光谱领域重要的研究内容，由于实际获得的混合油液三维荧光光谱数据存在不同组分光谱重叠严重、数据三线性较差等问题，通过平行因子算法解析时，会出现解析谱与标准谱差异过大或者不能正确判断油种的情况。在验证三维荧光偏导数光谱应用平行因子算法具有可行性的基础上，将三维荧光偏导数光谱与平行因子算法结合，能够提高平行因子算法得到的混合油解析谱与标准谱的拟合程度，实现石油类混合油液组分的准确检测。首先，以十二烷基硫酸钠（SDS）溶液作为溶剂，配制航空煤油、润滑油不同浓度的纯油溶液各15份，将航空煤油、润滑油按照不同浓度比配制9份混合油溶液；并利用FS920荧光光谱仪得到39份三维荧光光谱数据。然后，对三维荧光光谱数据进行预处理：通过扣除空白法去除拉曼散射，并将瑞利散射区域扣除，再利用分段三次hermite插值方法对扣除区域进行插值；利用小波变换阈值去噪法去除光谱数据中的高频噪声，得到预处理完成后的三维荧光光谱数据。最后，利用Savitzky-Golay拟合求导方法求三维荧光光谱的一阶偏导数光谱，并利用平行因子算法对三维荧光光谱和三维荧光偏导数光谱进行解析。将解析谱与纯油标准谱进行比较，实验结果表明：利用平行因子算法对混合油液的三维荧光光谱进行解析时，得到的润滑油解析结果较好，但航空煤油的解析结果存在较大问题。而三维荧光偏导数光谱经平行因子算法解析后，在保证润滑油解析结果的同时，显著提高了航空煤油的解析结果：航空煤油解析谱与标准谱之间的相关系数提升了12.0%（发射光谱）、6.7%（激发光谱），均方根误差减少了70.4%（发射光谱）、20.6%（激发光谱）。在三维荧光光谱数据三线性较差的情况下，三维荧光偏导数光谱结合平行因子分析方法优于三维荧光光谱结合平行因子分析方法，实现了对混合油液组分准确检测的目的。

Three-Dimensional Fluorescence Partial Derivative Spectroscopy Combined With Parallel Factor Algorithm for Detection of Mixed Oil

The component detection of petroleum mixed oil is an important research content in the field of three-dimensional fluorescence spectroscopy. The actual obtained three-dimensional fluorescence spectrum data of mixed oil has problems such as the serious overlap of different component spectra and poor trilinearity of the data. When analyzing the three-dimensional fluorescence spectrum by the parallel factor algorithm (parafac), the difference between the analytical spectrum and the standard spectrum is too large, or the type of oil cannot be judged correctly. The paper verifies that the parallel factor algorithm can be applied to three-dimensional fluorescence partial derivative spectroscopy. This paper combines the three-dimensional fluorescence partial derivative spectroscopy with the parafac, improving the degree of fitting between the analytical spectrum and the standard spectrum. Therefore, this paper realizes the accurate detection of the components of petroleum mixed oil. First, the paper use sodium dodecyl sulfate solution (SDS) as the solvent to prepare 15 parts of pure oil solutions of different concentrations of jet fuel and lubricating oil. 9 parts of mixed oil solution are prepared by jet fuel and lubricating oil according to different concentration ratios. The FS920 fluorescence spectrometer obtains the three-dimensional fluorescence spectrum data of 39 samples. They were using the following methods to preprocess the three-dimensional fluorescence spectrum data. Raman scattering is removed by the subtraction standard method. The Rayleigh scattering area is subtracted, and then the subtracted area is interpolated by the segmented cubic Hermite interpolation method to perfect the data. The wavelet transform threshold denoising method is used to remove the high-frequency noise in the spectrum data. Finally, the Savitzky-Golay fitting derivative method is used to obtain the first-order partial derivative spectrum of the three-dimensional fluorescence spectrum. The parafac is used to analyze the three-dimensional fluorescence spectrum and the three-dimensional fluorescence partial derivative spectrum. The experimental results show that when the parafac is used to analyze the three-dimensional fluorescence spectrum of the mixed oil, the lubricating oil analytical results are better, but the analytical results of jet fuel have big problems. When the parafac used to analyze the three-dimensional fluorescence partial derivative spectrum of the mixed oil, the analysis results of jet fuel are significantly improved while ensuring the analysis results of lubricating oil. The correlation coefficient between the analytical spectrum and the standard spectrum of jet fuel has increased by 12.0% (emission spectrum) and 6.7% (excitation spectrum), and the root means square error has reduced by 70.4% (emission spectrum) and 20.6% (excitation spectrum). In view of the poor trilinearity of three-dimensional fluorescence spectrum data, three-dimensional fluorescence partial derivative spectroscopy combined with parafac analysis method is better than three-dimensional fluorescence spectroscopy combined with the pafarac analysis method, which achieves accurate detection of mixed oil components.