基于PCA-SVM融合离子迁移谱与拉曼光谱的毒品鉴别方法
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摘要
光学检测的指纹图谱具有专属性强、稳定性好、重现性好的特性。通过离子迁移谱毒品探测仪(IMS)与易制毒化学品拉曼快速检查仪分别采集离子与拉曼光谱的双谱图数据,然后将两个谱图进行创新数据融合后,结合主成分分析(PCA)和支持向量机(SVM)分类法对毒品进行鉴别。实验结果表明,融合后的数据相较于分别用单谱图数据进行鉴别,有效提高了对毒品的识别率和准确性。为鉴别毒品提供了一种安全、快速、可靠的新分析方法。
The fingerprint of optical detection has the characteristics of strong property,good stability and reproducibility.In this paper,the two types of data,ion and Raman spectra,were collected by ion mobility spectrometry(IMS)and Raman rapid detectors respectively for precursor chemicals.Then the two types of spectra are combined with the principal component analysis(PCA)and support vector machine(SVM)analysis for the drug identification.The experimental results show that the data fusion can effectively improve the recognition rate and the accuracy of the drug identification compared with that using single spectrum.In this paper,we provide a safe,fast and reliable new method for drug identification.
The fingerprint of optical detection has the characteristics of strong property,good stability and reproducibility.In this paper,the two types of data,ion and Raman spectra,were collected by ion mobility spectrometry(IMS)and Raman rapid detectors respectively for precursor chemicals.Then the two types of spectra are combined with the principal component analysis(PCA)and support vector machine(SVM)analysis for the drug identification.The experimental results show that the data fusion can effectively improve the recognition rate and the accuracy of the drug identification compared with that using single spectrum.In this paper,we provide a safe,fast and reliable new method for drug identification.
引文
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[18]檀景辉.基于脉冲正电晕放电离子源的离子迁移谱仪研究[D].天津:天津大学,2010.
[2]常颖,高利生.甲卡西酮概述及其分析方法[J].刑事技术,2011(5):35-38.
[3]EICEMAN G A,KARPAS Z.Ion mobility spectrometry[M].Florida:CRC Press,1994.
[4]EWING R G,ATKINSON D A,EICEMAN G A,et al.A critical review of ion mobility spectrometry for the detection of explosives and explosive related compounds[J].Talanta,2001,54(3):515-529,doi:10.1016/S0039-9140(00)00565-8.
[5]MKINEN M A,ANTTALAINEN O A,SILLANPM E T.Ion mobility spectrometry and its applications in detection of chemical warfare agents[J].Analytical Chemistry,2010,82(23):9594-9600,doi:10.1021/ac100931n.
[6]HARRIS G A,KWASNIK M,FERNNDEZ F M.Direct analysis in real time coupled to multiplexed drift tube ion mobility spectrometry for detecting toxic chemicals[J].Analytical Chemistry,2011,83(6):1908-1915,doi:10.1021/ac102246h.
[7]陈珊.拉曼光谱背景扣除算法及其应用研究[D].长沙:中南大学,2011.
[8]BIANCOLILLO A,BUCCI R,MAGRA L,et al.Data-fusion for multiplatform characterization of an italian craft beer aimed at its authentication[J].Analytica Chimica Acta,2014,820:23-31,doi:10.1016/j.aca.2014.02.024.
[9]TAN J,LI R,JIANG Z T.Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence,UV and visible spectroscopies[J].Food Chemistry,2015,184:30-36,doi:10.1016/j.foodchem.2015.03.085.
[10]BORRS E,FERRJ,BOQUR,et al.Data fusion methodologies for food and beverage authentication and quality assessment-A review[J].Analytica Chimica Acta,2015,891:1-14,doi:10.1016/j.aca.2015.04.042.
[11]CLOWERS B H,SIEMS W F,HILL H H,et al.Hadamard transform ion mobility spectrometry[J].Analytical Chemistry,2006,78(1):44-51.
[12]王继芬,余静,孙兴龙,等.毒品及其常见添加成分的拉曼光谱快速分析[J].光散射学报,2012,24(3):312-315.
[13]GROTH D,HARTMANN S,KLIE S,et al.Principal components analysis[C]∥REISFELD B,MAYENO A N.Computational Toxicology.Totowa,NJ:Humana Press,2013:527-547,doi:10.1007/978-1-62703-059-5_22.
[14]BOSER B E,GUYON I M,VAPNIK V N.A training algorithm for optimal margin classifiers[C]∥Proceedings of the 5th Annual Workshop on Computational Learning Theory.New York,NY,USA:ACM,1992:144-152.
[15]HAN J W,KAMBER M,PEI J.数据挖掘:概念与技术[M].范明,孟小峰,译.3版.北京:机械工业出版社,2012.
[16]徐鹏宇,苏婉芬,钟爱国.甲卡西酮光谱性质的密度泛函模拟与指认[J].当代化工,2014,43(3):334-336.
[17]赵金涛,彭勇,徐存英.麻黄素拉曼散射振动模式的研究[J].光散射学报,2001,13(2):114-118.
[18]檀景辉.基于脉冲正电晕放电离子源的离子迁移谱仪研究[D].天津:天津大学,2010.