基于拉曼光谱的混合物组分识别方法
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摘要
提出了一种基于拉曼光谱的混合物组分识别新方法。对混合物的拉曼光谱进行背景校正和去噪处理,利用Voigt函数对拉曼谱峰进行拟合,获取其谱峰的拉曼位移、半峰全宽及强度作为混合物特征参数向量,通过与数据库纯净物特征向量进行相关性分析,实现混合物组分的有效识别。构建了由18种纯净物拉曼光谱数据构成的标准组分数据库,并对6种混合物进行了组分识别实验。实验结果表明,所提方法的识别准确率达到100%。
A novel algorithm for component identification in mixtures based on Raman spectroscopy is proposed,in which background correction and de-noising operation on the Raman spectra of mixtures are firstly performed,the Voigt function is then used to fit the Raman peaks to obtain the Raman shifts,full widths at half maximum,and peak intensities as the feature parameter vector of mixtures,and finally,the effective component identification of mixtures is finally realized via the correlation analysis of the feature vectors between the mixtures and the pure substances in the database.The Raman spectral data of 18 pure substances are used to build a standard database,and the component identification experiment of 6 kinds of mixtures are conducted.The experimental results show that the recognition accuracy of the proposed algorithm is up to 100%.
A novel algorithm for component identification in mixtures based on Raman spectroscopy is proposed,in which background correction and de-noising operation on the Raman spectra of mixtures are firstly performed,the Voigt function is then used to fit the Raman peaks to obtain the Raman shifts,full widths at half maximum,and peak intensities as the feature parameter vector of mixtures,and finally,the effective component identification of mixtures is finally realized via the correlation analysis of the feature vectors between the mixtures and the pure substances in the database.The Raman spectral data of 18 pure substances are used to build a standard database,and the component identification experiment of 6 kinds of mixtures are conducted.The experimental results show that the recognition accuracy of the proposed algorithm is up to 100%.
引文
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[2] Wang J,Zhang F, Wang X P,et al. Threedimensional fluorescence characteristics by parallel factor method coupled with self-organizing map and its relationship with water quality[J].Acta Optica Sinica,2017,37(7):0730003.王娟,张飞,王小平,等.平行因子法结合自组织映射神经网络的三维荧光特征及其与水质的关系[J].光学学报,2017,37(7):0730003.
[3] He T, Shen J L. Applications of terahertz spectroscopy in illicit drugs detection[J].Spectroscopy and Spectral Analysis,2013,33(9):2348-2353.和挺,沈京玲.太赫兹光谱技术在毒品检测中的应用研究[J].光谱学与光谱分析,2013,33(9):2348-2353.
[4] Liu B,Liu Y H.Determination of 18 kinds of polycyclic aromatic hydrocarbons in food plastic packaging[J].Food Science and Technology,2018,43(6):317-321.刘彬,刘云虎.食品塑料包装中18种多环芳烃的气相色谱-质谱联用检测方法研究[J].食品科技,2018,43(6):317-321.
[5] Wu L S,Zhao M Y,Ge C,et al.Simultaneous determination of 16polycyclic aromatic hydrocarbons in mainstream cigarette smoke by solid phase extraction-GC/MS[J]. Tobacco Science &Technology,2018,51(4):46-52.吴丽洒,赵明月,葛畅,等.固相萃取-GC/MS法同时测定卷烟主流烟气中的16种多环芳烃[J].烟草科技,2018,51(4):46-52.
[6] Li K K,Miao C Y,Wang D K.Detection of drugs by Raman spectroscopy and data analysis based on R software[J].The Journal of Light Scattering,2018,30(2):156-162.李开开,苗翠英,王登魁.利用拉曼光谱对毒品的检验及基于R软件的数据分析[J].光散射学报,2018,30(2):156-162.
[7] Ma J.Rapid detection of chlorinated organic mixture by laser Raman spectroscopy[J].Spectroscopy and Spectral Analysis,2014,34(7):1865-1868.马靖.激光拉曼光谱技术对氯代有机混合物的快速检测研究[J].光谱学与光谱分析,2014,34(7):1865-1868.
[8] Huang P X,Yao Z X,Su H,et al.Spectral pattern recognition of mixed alcohols by means of the method based on judging the subspace coincidence[J].Journal of Instrumental Analysis,2013,32(3):281-286.黄培贤,姚志湘,粟晖,等.基于子空间重合判断的混合醇组分光谱识别方法[J].分析测试学报,2013,32(3):281-286.
[9] Zhang Y Q,Dong W,Zhang B,et al.Research on detection method of adulterated olive oil by Raman spectroscopy and least squares support vector machine[J].Spectroscopy and Spectral Analysis,2012,32(6):1554-1558.章颖强,董伟,张冰,等.基于拉曼光谱和最小二乘支持向量机的橄榄油掺伪检测方法研究[J].光谱学与光谱分析,2012,32(6):1554-1558.
[10] Yang G Y,Li L,Chen H,et al.Baseline correction method for Raman spectra based on generalized Whittaker smoother[J].Chinese Journal of Lasers,2015,42(9):0915003.杨桂燕,李路,陈和,等.基于广义Whittaker平滑器的拉曼光谱基线校正方法[J].中国激光,2015,42(9):0915003.
[11] Wang X,Fan X G,Xu Y J,et al.A baseline correction algorithm for Raman spectroscopy by adaptive knots B-spline[J].Measurement Science and Technology,2015,26(11):115503.
[12] Fan X G,Wang X F,Wang X,et al.Research of the Raman signal de-noising method based on feature extraction[J].Spectroscopy and Spectral Analysis,2016,36(12):4082-4087.范贤光,王秀芬,王昕,等.基于特征提取的低信噪比拉曼光谱去噪方法研究[J].光谱学与光谱分析,2016,36(12):4082-4087.
[13] Wang X B,Wu R M,Liu M H,et al.Study for wavelet denoising methods of laser Raman spectrum of carbendazim pesticide[J].Science and Technology of Food Industry,2014,35(5):277-280.王晓彬,吴瑞梅,刘木华,等.多菌灵农药激光拉曼光谱的小波去噪方法研究[J].食品工业科技,2014,35(5):277-280.
[14] Tan B,Huang M,Zhu Q B,et al.Detection and correction of laser induced breakdown spectroscopy spectral background based on spline interpolation method[J].Spectrochimica Acta Part B:Atomic Spectroscopy,2017,138:64-71.
[15] Tan B,Huang M,Zhu Q B,et al. Method on elements automatic identification of spectral peaks in laser-induced breakdown spectroscopy[J].Chinese Journal of Lasers,2018,45(8):0811002.檀兵,黄敏,朱启兵,等.激光诱导击穿光谱谱峰元素自动识别方法研究[J].中国激光,2018,45(8):0811002.
[16] Li B Q,Li C P,Huang Q B,et al.Research of portable mass spectrometer overlapped peak resolution method based on wavelet transform[J].Journal of Chinese Mass Spectrometry Society,2015,36(3):199-205.李宝强,李翠萍,黄启斌,等.基于小波变换的便携式质谱重叠峰解析方法研究[J].质谱学报,2015,36(3):199-205.
[17] Owusu-Ware S K,Chowdhry B Z,Leharne S A,et al.Quantitative analysis of overlapping processes in the non-isothermal decomposition of chlorogenic acid by peak fitting[J].Thermochimica Acta,2013,565(24):27-33.
[18] Hou X S,Zhang J,Tan Y.Application of Raman spectra feature extraction in material identification[J].Modern Scientific Instruments,2014(4):100-104.侯兴松,张健,镡云.拉曼特征峰提取在多组分混合溶液检测中的应用[J].现代科学仪器,2014(4):100-104.