Fast and accurate identification of unknown hazardous solid are of pivotal interest in public security and safety. In this research, the Raman spectra of ten dangerous were measured: four biotoxins (including aconitine, tetrodotoxin, α -conotoxin GI and ricin), six explosives (including Octogen, Hexanitrohexaazaisowurtzitane, Hexogen, Trinitrotoluene, Triacetone triperoxide and Black powder). The micro confocal Raman spectroscopy was used to obtain the spectrum data. Structural assignments to Raman bands observed in the spectrum were also proposed. On this basis, The principal component analysis (PCA) method is used to reduce the dimension of spectral data, and the linear discriminant analysis (LDA) pattern is developed based on Python language to establish recognition algorithm. The recognition algorithm based on the linear discriminant analysis could achieve a high recognition accuracy of 98.61%. Meanwhile, all the testing process could be completed within a few minutes without loss of samples. It suggested from this study that the combination of Raman spectroscopy of fingerprint characteristics and pattern recognition algorithm can be used for rapid screening of unknown compounds. Moreover, this method provides solutions for timely deletion of unknown compounds.
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