Method for identifying mixture component based on similarity under raman spectrum

Abstract

The invention discloses a method for identifying a mixture component based on similarity under a raman spectrum, and relates to the technical field of component analysis; the method comprises the following steps of collecting raman spectrums of a pure substance and a mixture to be identified, aiming at different characteristics of the pure substance and the to-be-identified mixture, a characteristic peak is searched for by adopting continuous wavelet transformation with different wavelet as a master wavelet function, so that accurate identification is realized; characteristic vector groups are extracted from the found characteristic peaks, so as to carry out similarity calculation on the pure substance and the to-be-identified mixture so as to preliminarily screen out the candidate pure substance; after the spectral data of the candidate pure substances are subjected to displacement correction, a final component recognition result is obtained by utilizing non-negative least squares; the whole process does not need manual participation, and can be rapidly and effectively applied to the identification of the mixture components, so that the precision ratio and the recall ratio of the mixture identification are improved to a certain extent, and the method has the characteristics of being rapid and lossless, simple in implementation process, accurate in identification result and the like.

Description

technical field [0001] The invention relates to the technical field of component analysis, in particular to a method for identifying mixture components based on similarity under Raman spectroscopy. Background technique [0002] Raman spectroscopy is a spectral analysis technique, which is widely used in the field of sample composition and content analysis. Raman spectroscopic analysis technology analyzes scattering spectra with different frequencies from incident light to obtain information on molecular vibration and rotation. It is often used in the analysis methods of material composition (qualitative analysis) and concentration (quantitative analysis). Raman spectroscopic analysis technology analyzes the characteristic information of chemical bonds or functional groups. Different substances have different chemical bonds or functional groups, which appear as different characteristic peaks on the Raman spectrum. In Raman spectral data, obtaining useful information hidden t...

AI Technical Summary

Problems solved by technology

However, there are certain defects in the above methods: the characteristic peak comparison method can effectively identify the components in the mixture in some specific occasions, but in most cases the Raman spectrum peaks of the mixture are numerous, and there will be overlap and coverage. Due to the complex detection environment and low instrument accuracy, the Raman spectrum peaks may shift, and the characteristic peak comparison method relies on the judgment of the human eye, which is time-consuming and laborious

The subspace overlapping method requires that all components in the mixture to be identified should be included in the known standard database, and when the components to be identified in the mixture are not in the known database, the algorithm will not be able to give the identification result

The neural network method requires a large number of training samples when training the model, and it is also time-consuming

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