Raman spectra pretreatment method for removing effects of background noises

A Raman spectroscopy and background noise technology, applied in the optical field, can solve problems such as ineffectiveness, large variation in Raman spectroscopy scattering intensity, temperature instability, etc.

A Raman spectroscopy and background noise technology, applied in the optical field, can solve problems such as ineffectiveness, large variation in Raman spectroscopy scattering intensity, temperature instability, etc.

CN102998296AActive Publication Date: 2013-03-27CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI

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  • Raman spectra pretreatment method for removing effects of background noises
  • Raman spectra pretreatment method for removing effects of background noises
  • Raman spectra pretreatment method for removing effects of background noises

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Embodiment Construction

[0031] The present invention will be further described below in conjunction with drawings and embodiments.

[0032] A Raman spectrum preprocessing method to remove the influence of background noise, such as figure 1 As shown, it includes the first-order differential of the information spectrum and the background spectrum respectively, and then subtracting the differential value of the background spectrum from the differential value of the information spectrum to obtain the differential difference spectrum C0; the Flag function marks C0 in segments; the effective information The differential difference spectrum C1 is obtained by the retention process; the effective information intervals in the differential difference spectrum C1 are segmentally integrated to obtain the effective Raman spectrum L1; the mutation point correction is performed to obtain the final information Raman spectrum after the preprocessing of the present invention.

[0033] Information Raman spectrum without...

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Abstract

The invention relates to a raman spectra pretreatment method for removing the effects of background noises. The raman spectra pretreatment method comprises the following steps: 1) obtaining an information raman spectrum and a background spectrum; 2) respectively carrying out first-order differentiation on the information raman spectrum and the background spectrum to obtain a differential difference spectrum; 3) carrying out segment treatment on the differential difference spectrum; 4) carrying out effective information reservation on the differential difference spectrum processed in step 3); 5) carrying out respective sectional integration on the effective part of the differential difference spectrum processed in step 4); and 6) correcting a mutational site of the integral spectrum obtained in step 5), so as to obtain the preprocessed raman information spectrum. The method is used for the pretreatment of the raman spectrum; the effective raman information can be effectively extracted from the complicated background noises; and the method is simple and easy to implement.

Description

technical field [0001] The invention relates to the optical field, in particular to a Raman spectrum denoising processing method. Background technique [0002] When performing Raman spectrum analysis, the Raman spectrum of the substance to be measured is often affected by background noise. These background noises include machine noise, fluorescence interference, Raman spectra of other substances, etc. Background noise interference will affect the accuracy of spectral analysis. Severe background noise interference will make spectral analysis difficult to perform effectively. Therefore, it is often necessary to find a suitable spectral preprocessing method to eliminate the influence of background noise before performing spectral analysis. [0003] Common spectral preprocessing methods for removing background and noise effects include Digital smoothing and filtering: Commonly used digital smoothing and filtering methods include window moving average method and window moving...

Claims

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Application Information

Patent Timeline
27 Mar 2013
Publication
CN102998296A
IPC
G01N21/65
Inventors
李华栋; 夏良平