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针对紫外光谱结合化学计量学方法快速测定渣油烃族组成模型适应性问题，对渣油光谱进行主成分分析，以主成分得分作为聚类的特征变量进行模糊聚类，建立了光谱结合主成分分析和模糊聚类方法的样品聚类与识别方法。采用这种方法对3种常见渣油（常压渣油、减压渣油和加氢渣油）进行了成功的分类和识别，为光谱结合化学计量分析方法中校正模型的正确选择提供了依据。
Based on the UV spectroscopy combined with chemometrics methods to quickly determine the adaptability of residual hydrocarbon hydrocarbon composition model, the principal component analysis of residual oil spectra, the principal component score as the cluster characteristic variables fuzzy clustering established spectral combination of principal component Analysis and Fuzzy Clustering Method for Sample Clustering and Recognition. The successful classification and identification of three kinds of common residual oils (atmospheric residue, vacuum residue and hydrogenated residue oil) by this method provide the basis for the correct selection of the calibration model in the combination of spectrometry and stoichiometry .