提出了一种基于拉曼光谱的石油产品快速分类方法.首先,利用经过谱图预处理的石油产品训练样本拉曼谱图构建模型知识库,计算各类别的特征拉曼谱图和类内阈值；其次,将石油产品测试样本的拉曼谱图经过相同的预处理,再计算其与各类别特征拉曼谱图的线性相关系数,若最大相关系数大于或等于最大相关系数对应类别的类内阈值,则该样本属于此类别.针对7类96个取自不同炼厂不同批次的石油产品样本和4个未知类别样本的分类测试表明:该方法可正确地对常用的石油产品样本进行分类,也可判断未知样本的存在.该方法概念简单清晰,无需人为干涉,不存在复杂的数学运算,便于实际应用中的程序实现.%A fast and effective method for classification of petroleum products based on Raman spectroscopy is proposed. A knowledge base composed by Raman spectra of training samples, intra-class feature spectra and intra-class thresholds of all classes was firstly established. Then, correlation coefficients between the test sample and the intra-class feature spectra were calculated. If the maximal correlation coefficient of the test sample is larger than or equal to the corresponding intra-class threshold, the test sample is determined to belong to the corresponding class. For 96 petroleum product samples belonging to 7 classes and 4 unknown samples, the experimental results show that this method can accurately classify known test samples and can also find the unknown test samples. This method costs little calculation time and human interference. Moreover, it can be easily implemented in the practical application.
展开▼
