Spectral data processing method

Abstract

The invention relates to a spectral data processing method. The spectral data processing method comprises the following steps: (A1) exciting a standard sample, collecting a spectrum of the standard sample, and determining whether a relative standard deviation of the standard sample spectrum is in a first threshold range or not; (A2) determining peaks with wave peak intensity smaller than a saturation threshold value of a detector and wave peak pure intensity greater than a second threshold value in the standard sample spectrum as effective peaks, and calculating a peak area of the effective peaks; (A3) calculating an effective coefficient, wherein the effective coefficient is a ratio of the peak area of the effective peaks in an original spectrum to the peak area of the effective peaks in the standard sample spectrum; (A4) performing polynomial fitting according to the effective coefficient and a pixel position of the corresponding effective peak, and obtaining a fitting curve of the effective coefficient and the pixel position relation: Coef=p1*i3+p2*i2+p3*i+c; and (A5) exciting a sample to be detected, and by virtue of the fitting curve, correcting an exciting spectrum as: Measureint.[i]=Coef[i]*Measureresa.[i]. The spectral data processing method has the advantages of convenience in operation, low cost, single standard sample correction and the like.

Description

technical field [0001] The invention relates to the field of spectral analysis, in particular to a spectral data processing method for correcting wavelength sensitivity. Background technique [0002] During the use of the spectrometer, as the use time increases, some key components in the spectrometer are prone to aging, pollution, and changes in the relative displacement between components, etc. The above factors plus changes in ambient temperature and humidity will cause The intensity of the characteristic peaks of the elements changes, and the spectral shift often occurs, resulting in inaccurate measurement results. In order to improve the accuracy of the measurement results, the current commonly used method is to obtain the content of the element to be measured in the new standard curve by re-establishing the standard curve; after the standard curve. However, whether it is to re-establish the standard curve or to calibrate the standard curve through high and low standa...

AI Technical Summary

Problems solved by technology

However, whether it is to re-establish the standard curve or to calibrate the standard curve through high and low standard samples, to obtain a new standard curve requires the measurement of a large number of standard samples, which is cumbersome and time-consuming, and the standard samples are expensive. There are many varieties required, and the cost is too high

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