Incremental method for analysis of material component content based on infrared spectroscopy
A technology of infrared spectrum analysis and infrared spectrum, applied in the direction of color/spectral characteristic measurement, etc., can solve the problem of low efficiency of remodeling, achieve the effect of accurate and simple transfer relationship, reduce the amount of calculation, and predict the effect
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Embodiment 1
[0036] Such as figure 1 Shown, the present invention provides a kind of method based on infrared spectrum analysis substance composition content, comprises the following steps:
[0037] S101. Establish a first regression model according to the source-domain infrared spectrum data and the content of source-domain material components corresponding to the source-domain infrared spectrum data, and obtain parameters in the first regression model; the first regression model is, for example, A partial least squares regression model, performing feature extraction on the source domain infrared spectral data to obtain a first spectral feature, establishing the partial least squares regression model according to the first spectral feature and source domain material component content, and calculating the regression coefficient; specifically, the step of performing feature extraction on the source domain infrared spectral data to obtain the first spectral feature includes performing centra...
Embodiment 2
[0046] The method for analyzing the content of material components based on infrared spectroscopy in the present invention combines transfer learning and PLS algorithm to form a transfer calibration algorithm (CT_pls algorithm). Domain feature space, and then the model of the source domain can be used to process the data of the target domain. This method first uses the PLS algorithm to extract the features of the source domain samples and the target samples, then establishes a multivariate calibration model based on the source domain features and a linear transfer model between the source domain and target domain features, and finally uses the same method for the unknown After feature extraction and transfer of target domain samples, the source domain calibration model is used to predict the transferred features.
[0047] Assume that there are source domain datasets {X S ,y} and the target domain dataset {X T ,y}, where X S and x T Measured by the master spectrometer and t...
Embodiment 3
[0070] Such as image 3 As shown, the present invention provides an embodiment of an incremental method based on infrared spectroscopy to analyze the content of material components with reference to Embodiment 1 and Embodiment 2, which specifically includes the following steps:
[0071] S201. Establish a first regression model according to the source domain infrared spectrum data and the content of source domain material components corresponding to the source domain infrared spectrum data, and obtain parameters in the first regression model; specifically, for example, the first regression model A regression model is a partial least squares regression model, performing feature extraction on the source domain infrared spectrum data to obtain the first spectral feature, performing centralized processing on the source domain infrared spectrum data and source domain material composition content, according to the centralization Establishing a least squares regression model with the ...
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