• Spectroscopy and Spectral Analysis
  • Vol. 41, Issue 11, 3506 (2021)
Xiao-yu CHEN1、*, kun ZHANG1、1;, and De-ming KONG2、2; *;
Author Affiliations
  • 11. School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China
  • 22. School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
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    DOI: 10.3964/j.issn.1000-0593(2021)11-3506-06 Cite this Article
    Xiao-yu CHEN, kun ZHANG, De-ming KONG. Three-Dimensional Fluorescence Partial Derivative Spectroscopy Combined With Parallel Factor Algorithm for Detection of Mixed Oil[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3506 Copy Citation Text show less

    Abstract

    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.
    Xiao-yu CHEN, kun ZHANG, De-ming KONG. Three-Dimensional Fluorescence Partial Derivative Spectroscopy Combined With Parallel Factor Algorithm for Detection of Mixed Oil[J]. Spectroscopy and Spectral Analysis, 2021, 41(11): 3506
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