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Spectrum segmentation and spectrum comparison method based on spectrum peak-splitting fitting

A technology of peak fitting and spectrum, which is applied in the field of spectral peak segmentation and spectral comparison algorithm, can solve the problems of great influence, correlation coefficient influence, misjudgment, etc., to eliminate the problem of spectral similarity calculation and improve The effect of correct judgment rate

Pending Publication Date: 2021-03-26
EAST CHINA UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the spectra measured by different Raman or infrared spectrometers will be different in terms of peak position or signal intensity, which will have an impact on the calculation of the correlation coefficient, sometimes with a large impact, and serious misjudgment will occur

Method used

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  • Spectrum segmentation and spectrum comparison method based on spectrum peak-splitting fitting
  • Spectrum segmentation and spectrum comparison method based on spectrum peak-splitting fitting
  • Spectrum segmentation and spectrum comparison method based on spectrum peak-splitting fitting

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Embodiment 1

[0033] This embodiment is a comparison of the Raman spectra collected by two different types of Raman spectrometers, using the Raman spectrum data of n-hexane measured by a handheld Raman spectrometer and a desktop Raman spectrometer for comparison. The n-hexane spectrum measured by the desktop Raman spectrometer is from the Raman spectrum database and used as the standard spectrum; the n-hexane Raman spectrum measured by the handheld Raman spectrometer is used as the unknown spectrum. Firstly, corresponding preprocessing is performed on the two spectra to meet the conditions required for matching, and the spectral peaks of the unknown are fitted using the Voigt function, and the spectral peaks are segmented according to the fitting results to obtain spectral fragments, and each spectrum is recorded The wavelength start position and the wavelength end position of the segment; the Voigt function fitting is performed on the standard spectrum using the same method as described abo...

Embodiment 2

[0037]This embodiment is the comparison of two different brands and types of infrared spectrometers collecting infrared spectra, using a portable mid-infrared spectrometer (using ATR mode) and a Fourier transform mid-infrared spectrometer (using transmission mode) to measure the infrared spectrum of ethyl acetate, respectively As a comparison between the unknown spectrum and the standard spectrum, the two spectra are firstly preprocessed to meet the matching conditions, and the spectral peak of the unknown is fitted using the Voigt function. Segmentation, obtain spectral fragments, record the wavelength start position and wavelength end position of each spectral fragment; use the same method as above to perform Voigt function fitting on the standard spectrum, and use the wavelength start position and wavelength of the previously recorded spectral fragments at the same time Do the same segmentation for the end position. A least-squares fit is then performed on each pair of unkn...

Embodiment 3

[0041] In this embodiment, 257 kinds of chemical raw materials are used to measure the spectrum with a portable Raman spectrometer, and the spectral wavenumber range is 200-3200cm -1 . The standard Raman spectrum database is measured by a grating Raman spectrometer, including the Raman spectra of 14,000 compounds. Based on the spectral segmentation and spectral comparison method of spectral peak fitting of the present invention, the Raman spectra of 257 kinds of chemical raw materials are fitted, segmented, corrected, merged, and reconstructed, and all Raman spectra are unified using automatic Adaptive iteratively reweighted penalized least squares (airPLS) was used for baseline correction. The only parameter λ of airPLS was uniformly set to 1E5, and Pearson correlation coefficient was used for the calculation of spectral correlation coefficient. The matching accuracy rate of 257 spectra to be matched is 61.87% before the method is processed, and the matching accuracy rate of...

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Abstract

The invention discloses a spectrum segmentation and spectrum comparison method based on spectrum peak-splitting fitting, and the method comprises the steps: carrying out the fitting of a spectrum peakin a spectrum of an unknown object through a mathematic function, and carrying out the segmentation of a fitted spectrum peak parameter, and obtaining each spectrum segment and the start and end positions of the corresponding wavelength; performing the same segmentation on a standard spectrum according to the starting position and the ending position of the spectrum segment to obtain the spectrumsegment of the standard spectrum; fitting the spectrum segments of each pair of unknown object and standard object with the related wavelength range, and correcting the spectrum of the unknown objectby using fitting parameters; and respectively combining the corrected unknown object spectrum segment and the standard spectrum segment, reconstructing the whole spectrum, and calculating the similarity between the reconstructed unknown object spectrum and the standard spectrum. The method can be applied to comparison of an infrared spectrum, a near infrared spectrum, a Raman spectrum and an ultraviolet-visible spectrum, and the positive judgment rate of spectrum comparison can be remarkably improved.

Description

technical field [0001] The invention belongs to the field of spectral data processing, in particular to a spectrum peak segmentation and spectrum comparison algorithm. Background technique [0002] As important molecular spectroscopy techniques, Raman spectroscopy and infrared spectroscopy have been widely used in structural identification and rapid identification of substances, such as the rapid identification of drugs, explosives, and chemical raw materials. The usual method of spectral identification is: establish a spectral database (generally pure compounds); collect spectra for unknown substances, compare them with the spectra in the database, calculate the correlation coefficient, and judge the unknown and the standard according to the size of the correlation coefficient (database). material) matching degree. Calculation of correlation coefficient is one of the most important links in substance identification, and it is also called similarity degree, matching degree,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/35G01N21/359G01N21/33G01N21/65G06K9/62G06F17/15
CPCG01N21/35G01N21/359G01N21/33G01N21/65G06F17/15G01N2021/3595G06F18/22G06F18/24
Inventor 杜一平张若秋杨吴烨陆偲倩王芳李龙
Owner EAST CHINA UNIV OF SCI & TECH
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