基于ATR-SEIRAS分析技术的苯二氮卓类镇静药物无损分类与识别  

Nondestructive Classification of Benzodiazepines Sedatives Based on ATR-SEIRAS Analysis Technology

作　　者：朱密[1] 朱洪建 陈瑶清[1] Zhu Mi;Zhu Hongjian;Chen Yaoqing(Department of Criminal Science and Technology,Hunan Police College,Changsha,Hunan 410138,China;Yuelu Branch of Changsha Public Security Bureau of Hunan Province,Changsha,Hunan 410006,China)

机构地区：[1]湖南警察学院刑事科学技术系,湖南长沙410138 [2]湖南省长沙市公安局岳麓分局物证鉴定室,湖南长沙410006

出　　处：《激光与光电子学进展》2022年第2期494-501,共8页Laser & Optoelectronics Progress

基　　金：2019年湖南省普通高等学校教学改革项目(1108)。

摘　　要：镇静类药物的无损快速检验分析在法庭科学理化检验中具有重要意义。为了实现对苯二氮卓类镇静药物种类的准确区分,本实验室对8类共计81份样本进行了检验;借助衰减全反射-表面增强红外光谱(ATR-SEIRAS)分析技术获取各样本的光谱数据,基于原始光谱数据集、一阶导数光谱数据集、光谱融合数据集分别构建Fisher判别分析(FDA)和多层感知器神经网络(MLPNN)分类模型。结果表明:不同样本的理化信息存在一定差异,ATRSEIRAS谱图可以将这些差异反映出来,从而为实现不同苯二氮卓类镇静药物的有效分类奠定基础;基于光谱融合数据集构建的FDA模型的识别准确率最高,为100%,基于一阶导数光谱数据集和原始光谱数据集构建的FDA模型的识别准确率分别为96.3%和92.6%;基于上述三种数据集构建的MLPNN模型的识别准确率分别为97.5%、96.3%和88.9%。ATR-SEIRAS分析技术结合Fisher判别分析和多层感知器神经网络可以实现8类苯二氮卓类镇静药物的无损准确识别。Rapid and nondestructive analysis of sedative drugs plays an important role in forensic science.To demonstrate the potential of classifying benzodiazepine sedative drugs,we examined 81 samples from eight types of benzodiazepine sedatives.Spectral data of each sample were analyzed by attenuated total reflection-surface enhanced infrared spectroscopy(ATR-SEIRAS).Fisher discriminant analysis(FDA)and multilayer perceptron neural network(MLPNN)models were constructed based on the original spectral dataset,first derivative spectral dataset,and spectral fusion dataset.The results showed that there were some differences in the physical and chemical details of different samples.ATR-SEIRAS spectra could reflect these differences,which laid a foundation for the effective classification of different benzodiazepine sedatives.The classification accuracy of the FDA model based on the spectral fusion dataset was the highest(100%),and the classification accuracy of the first derivative spectral dataset and original spectral dataset was 96.3% and 92.6%,respectively.Based on the above datasets,the classification accuracy of the MLPNN model was 97.5%,96.3%,and 88.9%,respectively.Overall,the results demonstrate that ATR-SEIRAS combined with FDA and MLPNN classifiers can achieve rapid and nondestructive classification of eight types of benzodiazepine sedatives.

关 键 词：光谱学 光谱融合 导数光谱 苯二氮卓类镇静药物 无损分类 

分 类 号：O433.4[机械工程—光学工程]