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Near-infrared spectrum model migration method based on deep Bi-LSTM network

A near-infrared spectroscopy and model technology, which is applied in the field of near-infrared model transfer, can solve problems such as model mismatch and model incompatibility between different samples, and save time.

Active Publication Date: 2022-01-21
YANSHAN UNIV
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  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to provide a near-infrared spectrum model migration method based on a deep Bi-LSTM network to solve the problem of mismatch between models caused by different external measurement environments and inadaptability of models between different samples

Method used

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  • Near-infrared spectrum model migration method based on deep Bi-LSTM network
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  • Near-infrared spectrum model migration method based on deep Bi-LSTM network

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Experimental program
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Effect test

Embodiment 1

[0054] (1) Use the near-infrared spectrum data set of tablets published on the website of the International Conference on Diffuse Reflectance. The data set download website: (http: / / www.idrc-charmbersburg.org / shootout2002.html).

[0055] (2) Add Gaussian white noise with signal-to-noise ratios of 70DB and 80DB to the source-domain near-infrared spectral data respectively.

[0056] (3) Perform VMD (Variational Mode Decomposition) decomposition on all near-infrared spectra. The VMD algorithm formula continuously iteratively updates the mode, the corresponding center frequency and the Lagrangian multiplier until the correlation coefficient meets the conditions, stops the iteration, and outputs all IMFS , only extract the first sub-mode IMF1 of each spectrum; perform SNV (Standard normal variate) correction on all IMF1; normalize the corrected spectral data.

[0057] (4) Use the spxy algorithm to screen 920 spectra from the source domain calibration set, 80 spectra from the verifi...

Embodiment 2

[0070] (1) Dilute polyglutamic acid life liquid and energy liquid by 50% successively to obtain samples with concentrations of 3.5g / mL, 1.75g / mL, 0.875g / mL, 0.4375g / mL, and 0.21875g / mL liquid.

[0071] (2) The near-infrared spectra of all samples were collected by using the Bruker Fourier transform near-infrared spectrometer, and the near-infrared spectral data of the vital liquid were used as the source domain data, and the near-infrared spectral data of the energy liquid were used as the target domain data.

[0072] (3) In order to avoid overfitting of the trained neural network model, Gaussian white noise with signal-to-noise ratios of 70DB and 80DB was added to the collected vital fluid data.

[0073] (4) Perform VMD decomposition on all spectra, and only take IMF1; perform SNV correction on all IMF1; normalize the corrected spectral data.

[0074] (5) Use the spxy algorithm to divide the spectral data of life fluid and energy fluid into calibration set, verification set ...

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Abstract

The invention relates to a near-infrared spectrum model migration method based on a deep Bi-LSTM network, which belongs to the technical field of near-infrared model transfer. The method comprises the steps of obtaining spectral data of a source domain and a target domain, performing data enhancement on the source domain spectral data, preprocessing the spectral data of the source domain and the target domain, dividing spectral data of a source domain and a target domain, designing a Bi-LSTM network structure, training a Bi-LSTM network structure by using the source domain spectral data, extracting all Bi-LSTM layers, and adding a full connection layer to form a neural network, training a full connection layer by using near-infrared spectral data of a target domain correction set and a verification set, and updating weights and deviations among layers of the neural network, and testing the migration model by using the near-infrared spectral data of the target domain prediction set, and evaluating the migration effect and the anti-noise capability of the model. According to the method, migration from the target domain quantitative model to the source domain quantitative model is achieved, a large amount of time for reconstructing the model is saved, and high-precision prediction is kept.

Description

technical field [0001] The invention relates to a near-infrared spectrum model transfer method based on a deep Bi-LSTM network, and belongs to the technical field of near-infrared model transfer. Background technique [0002] Near-infrared spectroscopy is a non-destructive and rapid analysis method, which is widely used in the rapid analysis of chemical composition determination. However, in practical applications, changes in the external measurement environment (such as between different spectrometers, between different temperatures, and different times) will cause a mismatch with the original model, which indirectly restricts the popularization of near-infrared spectroscopy. Since the near-infrared spectrum absorption band is the superimposition of the absorption bands of the fundamental frequency absorption in the mid-infrared spectrum region of the chemical bonds with higher energy (mainly CH, OH, NH) in the mid-infrared spectrum, the near-infrared spectrum There is ser...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/359G06N3/04
CPCG01N21/359G06N3/044
Inventor 谈爱玲王鋆鑫赵勇
Owner YANSHAN UNIV
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