Characteristic spectral line rapid selection method used for atomic emission spectroscopy analysis

Abstract

The invention belongs to the field of spectral analysis, and provides a method for rapidly selecting multiple characteristic spectral lines related with specific element content from a lot of spectrum data, which can greatly increase the selection efficiency, effectively reduces the characteristic spectral line quantity which participates in modeling, simplifies a calculating process, and increases the stability and accuracy of a quantitative prediction model. The rapid selection method comprises the following steps: 1) performing spectrum pretreatment on spectral original data; 2) dividing the all spectral variable spectral lines X into several groups of Xi at intervals; 3) performing integral partial least squares on all variables X' corrected by the step 2); 4) performing partial least squares on the current all variables X'; and 5) comparing the importance of the current variables with threshold one by one; and 6) if quantitative analysis requirement is satisfied, stopping an iteration process, otherwise returning to the step 4). The method is mainly used for spectral analysis occasion.

Description

technical field [0001] The invention belongs to the field of spectroscopic analysis, in particular to a method for quickly selecting characteristic spectral lines for atomic emission spectroscopic analysis. Background technique [0002] Atomic emission spectroscopic analysis is an important application technology of spectral analysis, which can realize the qualitative and quantitative analysis of specific elements or components in the fields of industry, agriculture, and medicine. Typical atomic emission spectroscopy techniques are based on different excitation light sources, such as laser-induced breakdown spectroscopy (LIBS), inductively coupled plasma emission spectroscopy (ICP-AES), spark discharge emission spectroscopy (Spark-AES), etc. Chemistry is a promising and rapidly developing research direction. Emission spectrum analysis is to study the composition and content of substances based on the emission spectrum obtained by the radiative transition of free atoms or ou...

AI Technical Summary

Problems solved by technology

For atomic emission spectroscopy, when applying the multivariate analysis method, it is necessary to select useful characteristic spectral lines from a large number of spectral data to establish a model. It is used for infrared spectrum analysis but rarely for atomic spectrum analysis, because in dense atomic spectrum lines, the selection effect of spectral lines is not ideal (even selection errors occur), and it takes a long time, requires a lot of manpower, and is inefficient

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