Modeling method capable of improving accuracy of qualitative near-infrared spectroscopic analysis

A near-infrared spectroscopy and qualitative analysis technology, applied in the field of modeling and non-destructive analysis to improve the accuracy of near-infrared spectroscopy qualitative analysis, can solve the problem of less research, and achieve the effect of improving prediction accuracy and high practical value

Active Publication Date: 2015-12-16
四川斯菲提克科学仪器有限公司
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Problems solved by technology

Therefore, the EMD method has received widespread attention once it was proposed, and has been applied in the fields of biomedical signal analysis, bridge and b

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  • Modeling method capable of improving accuracy of qualitative near-infrared spectroscopic analysis
  • Modeling method capable of improving accuracy of qualitative near-infrared spectroscopic analysis

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Embodiment

[0028] 1) Data collection

[0029] Buy Haihe milk from different supermarkets at three different prices, namely bagged premium Tetra Pak, boxed Tetra Pak and boxed premium milk, with 20 samples for each price, 60 samples in total. A portable laser near-infrared spectrometer (XL-410, Axsun Technology Co., USA) was used to collect near-infrared spectra of 60 milk samples, with a wavelength range of 1350-1800 nm, a sampling interval of 0.5 nm, and a variable number of 901.

[0030] 2) Data grouping

[0031] Each of the three types of milk samples is grouped by KS, 2 / 3 of the samples are used as the training set (13 samples of each class are the training set), and 1 / 3 of the samples are used as the prediction set (7 samples of each class are the prediction set ). Then, the training set samples and prediction set samples of each category were combined to obtain 39 training set samples, which were used to build the model and optimize parameters; 21 prediction set samples were used...

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Abstract

The invention provides a modeling method capable of improving the accuracy of qualitative near-infrared spectroscopic analysis. The modeling method comprises the following steps: dividing acquired near infrared spectra and corresponding class target values into a training set and a prediction set; decomposing the spectra in the training set by using empirical mode decomposition (EMD); dividing IMFs and residual error matrixes obtained through decomposition into a high-frequency matrix and a low-frequency matrix according to frequency; expanding the two matrixes into augmented matrixes along the direction of a variable; converting a single row of class target values of various classes into a plurality of rows of target value matrixes of two classes; respectively building models for the augmented matrixes and a plurality of rows of target values; processing the spectra and target values of the prediction set as the spectra and target values of the training set and then substituting the processed spectra and target values into the models for prediction; and converting the obtained multiple rows of predicted target value matrixes of two classes into a single-row multi-class predicted value vector. The method expands the spectra into the augmented matrixes through empirical mode decomposition, so the accuracy of qualitative analysis is greatly improved. The modeling method is applicable to the field of analytical chemistry.

Description

technical field [0001] The invention belongs to the non-destructive analysis technology in the field of analytical chemistry, and in particular relates to a modeling method for improving the accuracy of near-infrared spectrum qualitative analysis. Background technique [0002] Near-infrared spectroscopy (NIR) is a non-destructive analysis technology that has developed rapidly in the field of analytical chemistry in recent years. Compared with traditional analysis techniques, near-infrared spectroscopy analysis technology has many advantages. The acquisition and measurement of near-infrared spectra can complete the determination of its multiple performance indicators; the spectral measurement does not require pretreatment of the analysis samples; no other materials are consumed or samples are damaged during the analysis process; the analysis has good reproducibility and low cost. Therefore, it has been widely used in agriculture, petrochemical, medical and other industries. ...

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Application Information

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IPC IPC(8): G01N21/359
Inventor 卞希慧范清杰李淑娟韩玉娇魏俊富
Owner 四川斯菲提克科学仪器有限公司
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