Adaptive model correcting method and system based on GT-KF-PLC near infrared spectrum
A technology of GT-KF-PLS and near-infrared spectroscopy, applied in the field of online analysis of near-infrared spectroscopy technology, can solve the problems of calibration model divergence, observation noise uncertainty KF-PLS, etc.
Inactive Publication Date: 2017-02-15
CHONGQING CITY MANAGEMENT COLLEGE +1
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[0005] In order to achieve the above object, the present invention provides a near-infrared spectrum adaptive model correction method and system based on GT-KF-PLS (Gamma test-Kalmanfilter-Partial least square, the Kalman filter partial least square of gamma test), with Solve the divergence problem of KF-PLS correction model caused by the uncertainty of observation noise
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[0093] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that these embodiments may be practiced without these specific details.
[0094] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0095] In order to illustrate the correction method based on the GT-KF-PLS near-infrared spectrum adaptive model provided by the present invention, figure 1 It shows the process flow of the self-adaptive model correction method based on GT-KF-PLS near-infrared spectrum according to the embodiment of the present invention.
[0096] Such as figure 1 As shown, the GT-KF-PLS near-infrared spectrum adaptive model correction method provided by the present invention includes:
[0097] S1: Use the K / S algorithm to select representative modeling samples from standard sample...
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The invention provides an adaptive model correcting method and an adaptive model correcting system based on GT-KF-PLC near infrared spectrum, wherein the method includes steps of selecting representative molding samples from standard samples by a K / S algorithm; setting up a linear relationship (PLS correction model) between near infrared spectrum data and concentration for the molding sample by PLS (partial least squares) method; predicting the sample to be tested by using the PLCS correction model, and obtaining the prediction value of the sample to be tested; regularly testing the sample to be tested, and collecting the sample data of the sample to be tested; applying Gamma Test to perform noise statistical value calculation on sample spectrum data and the sample data of the sample to be tested, obtaining accurate noise variance yield of system noise; through KF algorithm, modifying a main factor coefficient of the PLS correction model at current moment. The invention can effectively solve the divergence problem of KF-PLS correction model caused by uncertainty of observing noise, and provide an effective way for setting up the accurate correcting model based on the near infrared spectrum in online analyzing process by KF-PLS.
Description
technical field [0001] The invention belongs to the field of online analysis of near-infrared spectroscopy technology, in particular to a near-infrared spectrum dynamic evolution model correction based on GT-KF-PLS (Gammatest-Kalman filter-Partial least square, gamma test Kalman filter partial least squares) methods and systems. Background technique [0002] KF-PLS (Kalman FilterPartial Least Squares) has been proven to be a new method to improve the adaptability of multivariate calibration models for near-infrared spectroscopy. The calibration model established by this method has the advantages of adapting to equipment obsolete, environmental changes and out-of-boundary samples. [0003] However, the KF-PLS noise variance method is difficult to obtain the noise variance value of the dynamic near-infrared spectrometer measurement process with uncertain observation noise, so the observation noise variance value is often set to zero, and the forgetting factor is introduced to...
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IPC IPC(8): G01N21/359
CPCG01N21/359
Inventor 梅青平李太福乐明于单光庆姚立忠唐一科董引娣张望
Owner CHONGQING CITY MANAGEMENT COLLEGE