Similarity-Based Identification Method of Mixture Components under Raman Spectroscopy

Abstract

The invention discloses a method for identifying components of a mixture based on similarity under Raman spectroscopy, and relates to the technical field of component analysis. The method for identifying components of a mixture collects Raman spectra of pure substances and mixtures to be identified. For the different characteristics of the mixture, the continuous wavelet transform with different wavelets as the mother wavelet function is used to find the characteristic peaks, and the identification is accurate; the characteristic vector group is extracted from the found characteristic peaks, so as to perform the preliminary screening of the similarity calculation between the pure substance and the mixture to be identified Candidate pure substances are selected, and after displacement correction is performed on the spectral data of candidate pure substances, the final component identification result is obtained by using non-negative least squares. The whole process does not require manual participation, and can be quickly and effectively applied to the identification of mixture components. To a certain extent, the precision rate and recall rate of mixture identification are improved, and it has the characteristics of fast and non-destructive, simple implementation process and accurate identification results.

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 that is widely used in the field of sample composition and content analysis. Raman spectroscopy analysis technology analyzes the scattering spectrum different from the incident light frequency to obtain molecular vibration and rotation information, and is often applied to the analysis methods of material composition (qualitative analysis) and concentration (quantitative analysis). Raman spectral analysis technology analyzes the characteristic information of chemical bonds or functional groups. Different substances have different chemical bonds or functional groups, which are manifested as different characteristic peaks on the Raman spectrum. In Raman spectral data, it is a key step to obtain the hid...

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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