Fast recognition and classification of tetrazole compounds based on laser-induced breakdown spectroscopy and raman spectroscopy

In order to achieve fast non-contact recognition and classification of tetrazoles, an integrated system of laser-induced breakdown spectroscopy(LIBS) and Raman spectroscopy was established. First, the Raman spectra of four tetrazolium compounds, including tetrazolium, 5-aminotetrazol, 1, 5-diaminodiazole and 1-methyl-5-aminotetrazol were collected at an excitation wavelength of 1 064 nm. By analyzing the Raman shift of specific functional groups, they were successfully identified. The plasma radiation spectrum of each sample was collected based on LIBS technology. 140 sets of spectral data were selected for training and a classification model was established. The accuracy of the type area was verified by the remaining 60 sets of data. In this paper, two classification models were established based on PCA(Principal Component Analysis) and SVM(Support Vector Machine). On the one hand, the full spectra were used for PCA. The first 64 principal components were selected and the model was established using an SVM algorithm. On the other hand, 10 characteristic wavelengths were selected for PCA by comparing spectral differences and the first three were selected to establish the model. It was found that the average prediction accuracy of the former is only 88.3%, while the 60 spectral sample points of the latter are all located in the corresponding standard sample type area. The classification accuracy meets 100%. Experimental results show that the combination of LIBS and Raman spectroscopy can accurately identify tetrazole compounds.