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基于组合算法的油类污染物三维荧光光谱分析

Three-Dimensional Fluorescence Spectra Analysis of Oil Contaminants Based on Algorithm Combination Methodology

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摘要

针对油类污染物成分复杂、光谱重叠难以识别的问题, 提出三维荧光光谱结合组合算法(ACM)。将交替三线性分解(ATLD)、自加权交替三线性分解(SWATLD)与平行因子分析(PARAFAC)算法组合, 实现3种算法的优势互补。通过配制以四氯化碳为溶剂的不同质量浓度的柴油、汽油和煤油的混合溶液, 利用F-7000荧光光谱仪测量混合溶液的三维荧光光谱, 采用空白扣除法与缺损数据修复——主成分分析法进行预处理消除散射干扰, 对三维光谱数据矩阵进行分解, 并与以上3种算法解析结果进行对比。结果表明, ACM对组分数不敏感, 且解析结果更准确, 样本中对柴油、汽油和煤油的平均回收率分别为 96.68%、97.83%、97.11%。实现了混合油类物质的定性、定量分析, 具有一定的普适性。

Abstract

This study proposes a new technique that combines three-dimensional fluorescence spectra with algorithm combination methodology (ACM) to address issues associated with complex components of oil pollutants and the difficulty in identifying their overlapping spectra. By combining alternating trilinear decomposition (ATLD), self-weighted alternating trilinear decomposition (SWATLD), and parallel factor analysis (PARAFAC), ACM realizes the complementary advantages of using three algorithms. First, using carbon tetrachloride as the target contaminant, a three-component mixed solution of diesel, gasoline, and kerosene with different concentrations are prepared. Then, the three-dimensional fluorescence spectra of the mixed solution are measured using a F-7000 fluorescence spectrometer. Blank deduction and missing data recovery-principal component analysis are then employed as pretreatment methods to eliminate the scattering interference. Finally, ACM is used to decompose the three-dimensional spectral data matrix. Results are compared with the three separate algorithms for component analysis, revealing that ACM is insensitive to component concentration. The average recoveries for diesel, gasoline, and kerosene are 96.68%, 97.83% and 97.11%, respectively, which further indicated that this method is more universal and can be used for the qualitative and quantitative analyses of contaminants in oil mixtures.

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中图分类号:O433.4;O657.3

DOI:10.3788/lop56.033002

所属栏目:光谱学

基金项目:国家自然科学基金(61471312, 61771419)、河北省自然科学基金(F2015203240)

收稿日期:2018-06-15

修改稿日期:2018-08-29

网络出版日期:2018-08-31

作者单位    点击查看

陈至坤:华北理工大学电气工程学院, 河北 唐山 063210
黄微:华北理工大学电气工程学院, 河北 唐山 063210
程朋飞:华北理工大学电气工程学院, 河北 唐山 063210
沈小伟:华北理工大学电气工程学院, 河北 唐山 063210
王福斌:华北理工大学电气工程学院, 河北 唐山 063210

联系人作者:黄微(huangwei_ncst@163.com)

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引用该论文

Chen Zhikun,Huang Wei,Cheng Pengfei,Shen Xiaowei,Wang Fubin. Three-Dimensional Fluorescence Spectra Analysis of Oil Contaminants Based on Algorithm Combination Methodology[J]. Laser & Optoelectronics Progress, 2019, 56(3): 033002

陈至坤,黄微,程朋飞,沈小伟,王福斌. 基于组合算法的油类污染物三维荧光光谱分析[J]. 激光与光电子学进展, 2019, 56(3): 033002

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