为了快速检测不同厂家及批次外用溃疡散，以拉曼光谱技术结合主成分分析（PCA）-支持向量机（SVM）分类模型对不同厂家及批次外用溃疡散进行了分类鉴别。结果显示，虽然拉曼光谱的差异十分微小，几乎无法用肉眼直接进行分类鉴别，但是通过PCA-SVM分类模型能够对不同厂家及批次外用溃疡散进行准确的分类鉴别，且准确率均为100%。该方法且具有快速、准确、无损、简便等优点，对不同厂家及批次外用溃疡散的分类鉴别和质量监控具有潜在的应用价值。

To rapidly detect different manufacturers and batches of Wai Yong Kui Yang San, Raman spectroscopy combined with principal component analysis (PCA) - support vector machine (SVM) algorithm was used to classify and identify different manufacturers and batches of Wai Yong Kui Yang San. The results show that although the difference of Raman spectra is very weak, it can not be directly classified and identified by naked eyes, but PCA-SVM algorithm can accurately classify and identify different manufacturers and batches of Wai Yong Kui Yang San , and the accuracy rate is 100%. This method is rapid, accurate, non-destructive and simple, and has potential application value for classification, identification and quality control of different manufacturers and batches of Wai Yong Kui Yang San .