海洋溢油是主要环境灾害之一, 而且近年来其发生频率呈上升趋势。 快速地对油品进行种类鉴别、 来源评估有利于及时采取应急措施, 因此具有重要意义。 采用衰减全反射傅里叶变换红外光谱法(ATR-FTIR)对25种不同来源的油品进行了检测, 用不同数据预处理方法对原始光谱进行了预处理, 继而用主成分分析(PCA)和系统聚类分析(HCA)方法对光谱进行了分类鉴别。 结果表明用多元散射校正(MSC)和连续小波变换(CWT)方法进行数据预处理可以提高分类的准确性, 使分类结果与油样的实际来源一致。 该方法对正构烷烃差异较大的油品进行了很好的区分, 但对差异较小的油品其分辨能力仍有一定局限性。 因此提供了一种快速的油品鉴别方法, 可用于溢油事件的初步鉴定, 从而为油品的进一步鉴定提供有用信息。Transform Infrared Spectrometry Combined with Pattern Recognition Techniques

In the present work, the combination of attenuated total reflectance-Fourier transform infrared spectrometry (ATR-FTIR) and pattern recognition,including principal components analysis (PCA) and hierarchical cluster analysis(HCA), is used as a fast and convenient analytical tool to classify oil samples.Twenty five samples including crude oils and fuel oils with different totalcontents of n-alkanes were analyzed. It was found that multiplicative scattercorrection (MSC) and continuous wavelet transform (CWT) as a pretreatment methodcould improve the classification results of pattern recognition. Theclassification results were proved to be in agreement with the origin of the oilsamples. The oils with high content of n-alkanes and those with low content wereclassified clearly by this developed method, but it still had some constraint todifferentiating oils with little difference. The present work provides a feasiblemethod for quick classification of oils, which can be used for the initialidentification of spill oils and afford useful information for the furtheridentification of the oils.infrared spectrometry (ATR-FTIR); Principal components analysis (PCA);Hierarchical cluster analysis (HCA)验室课题项目(200816)资助