基于拉曼光谱技术对不同厂家及批次外用溃疡散的分类鉴别研究  

Study on classification and identification of different manufacturers and batches of Wai Yong Kui Yang San by Raman spectroscopy

作　　者：阿木古楞 韩斯琴高娃[1] 包琳[2] 哈斯乌力吉[3] AMU Guleng;HAN Siqingaowa;BAO Lin;HASI Wuliji(Affiliated Hospital of Inner Mongolia Minzu University,Neimenggu Tongliao,028007,China;College of Physics and Electronics Information,Inner Mongolia Minzu University,Neimenggu Tongliao,02800,China;National Key Laboratory of Laser Spatial Information,Harbin Institute of Technology,Heilongjiang Harbin,150080,China)

机构地区：[1]内蒙古民族大学附属医院,内蒙古通辽028007 [2]内蒙古民族大学物理与电子信息学院,内蒙古通辽028000 [3]哈尔滨工业大学激光空间信息全国重点实验室,黑龙江哈尔滨150080

出　　处：《光散射学报》2024年第2期142-147,共6页The Journal of Light Scattering

基　　金：国家自然科学基金项目(82160806);内蒙古自治区自然科学基金项目(2022MS08064、2024LHMS08035、2024QN06013);内蒙古民族大学博士科研启动基金(BS668)资助。

摘　　要：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.

关 键 词：拉曼光谱 主成分分析(PCA) 支持向量机(SVM) 外用溃疡散 分类鉴别 

分 类 号：O657.37[理学—分析化学]