Wavelength Point Recombination Method Based on Characteristic Peaks

Abstract

The invention discloses a method for recombining wavelength points based on characteristic peaks, which includes: collecting spectral data of a sample to be tested and performing modeling to obtain a spectral model M; performing second-order derivation on the spectral data of the sample to be tested to obtain the characteristics of the sample to be tested According to the wavelength point distribution characteristics of the portable near-infrared spectrometer, the wavelength point density near the characteristic peak is changed; the spectral data collection and spectral modeling of the same sample to be tested are carried out again to obtain the spectral model M'; compare the spectral model M and M', and judge the model Effect. This method reorganizes and optimizes the spectral wavelength points through the characteristic peak information, reduces the acquisition amount of spectral data with less correlation between samples, and collects more spectral data that can be used to characterize the sample to be tested, thereby effectively improving the effect of the spectral model.

Description

technical field [0001] The invention relates to the technical field of spectrum wavelength point recombination, in particular to a wavelength point recombination method based on characteristic peaks. Background technique [0002] In recent years, near-infrared spectroscopy has developed rapidly and has been applied in many fields such as chemical industry, pharmaceuticals, military industry, and food. Near-infrared spectroscopy belongs to molecular spectroscopy, which can indicate material composition and property information at the molecular level. It has achieved very high benefits and great development potential in terms of economic and social impacts. [0003] However, at present, most of the detection of material composition and property information is mainly carried out by large-scale laboratory near-infrared spectroscopy instruments. Although these methods are quantitatively accurate and sensitive, the equipment required is bulky and expensive, and the sample preparat...

AI Technical Summary

Problems solved by technology

However, portable near-infrared spectrometers are easily affected by light sources, detectors, detection methods, environmental conditions, etc., resulting in poor stability and low precision of the collected spectral data, which in turn affects the effect of the spectral model.

In particular, the currently used portable near-infrared spectrometer with wavelength equalization collects too much data information that is less relevant to the sample, which leads to problems such as poor spectral model effect and inaccurate data analysis.

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