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鉴于目前没有一种方法能独立解决溢油鉴别的所有问题,本文提出了近红外光谱技术结合主成分聚类分析鉴别溢油种类的方法。通过有机溶剂萃取出自行配制的汽油、柴油和润滑油模拟样品中的溢油后记录其近红外光谱,对5800～6200cm-1区段范围内的谱图经多元散射校正(MSC)、Norris一阶导数平滑预处理处理后求其主成分,并在主成分的基础上引入Ward聚类分析法(离差平方和法)对样品分类。结果表明近红外光谱技术结合聚类分析能对体积分数在0.4～0.8mL/L间的海面溢油样品正确、快速分类,近红外光谱技术结合主成分聚类可作为溢油鉴别的一种辅助方法。
In view of the fact that there is not a single method that can solve all the problems of oil spill identification independently, this paper proposes a method of identifying oil spill types by NIRS combined with principal component analysis. NIR spectra were recorded after spilled oil from gasoline, diesel and lubricating oil samples prepared by organic solvent extraction. The spectra in the range of 5800 ~ 6200cm-1 were corrected by multivariate scatter calibration (MSC), Norris- Derivative smoothing preprocessing to calculate the principal components, and the introduction of the main components based on Ward clustering analysis (deviation sum of squares method) to classify the samples. The results showed that near-infrared spectroscopy combined with cluster analysis could accurately and rapidly classify oil spill samples with volume fraction of 0.4-0.8 mL / L. Near-infrared spectroscopy combined with principal component clustering can be used as an aid to identify oil spills method.