Spectral model transmission method based on unary linear regression
A linear regression and model transfer technology, applied in the field of spectral analysis, can solve problems such as too many parameters and insufficient accuracy of the transfer model
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Embodiment 1
[0051] The method flow of this example is as follows figure 1 As shown, the main steps are as follows:
[0052] Ⅰ. Pretreatment of sample spectra
[0053] In this example, there are 3 near-infrared spectroscopic analysis instruments, which are recorded as A, B, and C respectively. The 4 main components of 80 corn samples are known: the reference values of water, oil, protein and starch content. The sample set contains the near-infrared spectra of 80 corn samples measured on three different spectrometers, and the spectral wavelength range is 1100-2498nm with an interval of 2nm. In this example, the spectral data collected on three spectroscopic instruments are smoothed and preprocessed with the Savitzky-Golay smoothing method, the window size is 17, and the polynomial order is 3.
[0054] Ⅱ. Establishment of Calibration Model
[0055] In this example, firstly, the 80 corn samples were sorted according to the reference values of the contents of the four components; then, ...
Embodiment 2
[0108] The process of this example is also as figure 1 shown.
[0109] Ⅰ. Pretreatment of sample spectra
[0110] In this example, there are 2 spectrometers, denoted as D and E respectively. The sample set in this example contains 88 gasoline samples, and 88 near-infrared spectrum samples are measured on two spectrometers, and the spectral collection range is 700-1100nm. At the same time, the reference values of C7, C8, C9 and C10 component contents in each sample are known.
[0111] In this example, the standardized method is used to preprocess the spectral data collected on two spectrometers.
[0112] Ⅱ. Establishment of Calibration Model
[0113] In this example, the 88 gasoline samples are firstly sorted according to the reference values of the contents of the four components in gradients; then each of the 30 samples is selected as the prediction set, and the remaining 58 samples are used as the calibration set. The sample has 4 components, so there are 4 calibrat...
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