Near infrared spectrum online modeling method based on partial least square method

A partial least squares method and near-infrared spectroscopy technology, which is applied in the field of near-infrared spectroscopy detection, can solve the problems of reduced prediction accuracy and achieve the effect of improving computing efficiency

Pending Publication Date: 2022-02-18
四川启睿克科技有限公司
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Problems solved by technology

At present, due to the impact of algorithm modeling operation efficiency, most products use offline modeling, import the screened optimal model into the system, and predict unknown samples; and online modeling prediction In order to improve the operating efficiency of the system, Compressing the search parameter interval is often used to reduce the amount of computation to achieve the effect of online modeling and prediction, but the compression of the search parameter interval can easily lead to a decrease in prediction accuracy

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  • Near infrared spectrum online modeling method based on partial least square method
  • Near infrared spectrum online modeling method based on partial least square method

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Embodiment

[0044] Such as figure 2 As shown, taking the data collected by the near-infrared spectrometer in the 1350nm-1650nm band as an example:

[0045] a. Import the original spectrum: In this embodiment, the original spectral data is 340×51 matrix data, which contains 340 spectral data, each spectral data has 50 bands, and 1 calibration value data;

[0046]b. Preprocessing the original spectral data: In this embodiment, 10 preprocessing methods such as Gaussian smoothing, Gaussian derivation, and SG smoothing are used, and each preprocessing method is given a very wide range of parameter settings, with a total of 2000 A combination of preprocessing, the broad preprocessing combination is to increase the robustness of the online modeling model, thereby improving the prediction accuracy of the portable spectrometer;

[0047] c. Modeling by partial least squares method: set the search parameter interval of the modeling principal components to [1, 2, ..., 15], and extract the maximum v...

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Abstract

The invention relates to the technical field of near infrared spectrum detection, and provides a near infrared spectrum on-line modeling method based on a partial least square method in order to improve the efficiency of near infrared spectrum on-line modeling, which comprises the following steps of: 1, inputting spectrum original data; 2, preprocessing the spectrum original data; 3, adopting an optimized partial least square method for modeling; 4, setting a model evaluation index; and 5, carrying out model screening according to the model evaluation indexes, and storing an optimal model. By adopting the mode, the online modeling efficiency of the near infrared spectrum can be improved.

Description

technical field [0001] The invention relates to the technical field of near-infrared spectrum detection, in particular to an online near-infrared spectrum modeling method based on a partial least square method. Background technique [0002] Near-infrared spectrum detection equipment mainly includes traditional large-scale spectral analysis systems and portable spectrometers. With the development of micro-electromechanical technology, in recent years, portable spectrometers have been widely used in various fields such as food, wine, medicine, and coal. The large-scale spectral analysis system has the advantages of simple structure, low cost, easy to carry, and real-time visible results. It has become a popular product in the field of spectroscopy. However, it also has certain shortcomings, such as stability, operating efficiency, and accuracy, which still have a certain gap with traditional large-scale laboratory equipment, and it needs to be continuously optimized in terms o...

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Application Information

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IPC IPC(8): G06K9/62G01N21/359
CPCG01N21/359G06F18/2135G06F18/217
Inventor贾利红闫晓剑张国宏刘浩
Owner四川启睿克科技有限公司