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LPP (Local Preserving Projection)-based Infrared spectrometer calibration method

A technology of locally maintaining projection and infrared spectrometer, which is applied in the field of infrared spectrum model transfer, can solve problems such as the inability to completely eliminate the differences between spectra of different instruments, undeveloped technologies and literature, and interference of spectral transformation methods, so as to improve robustness , maintain the local structure, eliminate the effect of nonlinear interference

Inactive Publication Date: 2013-04-03
JIANGSU PROVINCE INST OF QUALITY & SAFETY ENG
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Problems solved by technology

[0005] However, preprocessing methods may lead to loss of spectral information, so that the differences between different instrument spectra cannot be completely eliminated
Spectral transformation methods such as piecewise direct normalization methods can suffer from normal noise
The model transfer method based on locally preserving projection can effectively overcome the influence of noise, and there is no mature technology and literature yet
In addition, different instrument models and changes in the acquisition environment will lead to various complex differences between the spectra collected by different instruments. How to effectively eliminate these differences through transformation methods is a difficult problem in model transfer technology.

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[0031]Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0032] The following first gives the local preservation projection model:

[0033] Given observation data x 1 ,x 2 ,...x m ∈ R n , the local preservation projection transformation seeks a projection matrix A, and maps these m points to y 1 ,y 2 ,...,y m ∈ R l (li able to represent x i ,y i =A T x i .

[0034] The local-preserving projection algorithm is divided into the following steps:

[0035] 1. Construct an adjacency graph: Let the graph G consist of m nodes. According to the k-nearest neighbor principle, if the sample x i is x j The k nearest neighbors or samples x j is x i k-nearest neighbors, connect nodes i and j with an edge.

[0036] 2. Select weights: Let W be a sparse weight matrix of size m×m. W ij is the weight on the edge connecting vertices i and j, if vertices i and j are not connected, then W ij is 0. Weights can be defined in tw...

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Abstract

The invention discloses an LPP (Local Preserving Projection)-based Infrared spectrometer calibration method. The LPP-based Infrared spectrometer calibration method comprises the following steps of: collecting infrared spectrograms of master and slave instrument guide sample sets; establishing a subspace LPP transformation matrix which can reflect the difference between the master and slave instrument infrared spectrograms according to the collected infrared spectrograms of the master and slave instrument guide sample sets; obtaining a corresponding transformation relation between the infrared spectrograms of the master and slave instrument guide sample sets by utilizing the subspace LPP transformation matrix, and transforming the infrared spectrogram on the salve instrument to the master instrument; and forecasting the transformed infrared spectrogram according to a multivariate calibration model established on a master instrument calibration set so that the master instrument model can be successfully applied to the infrared spectrogram of the slave instrument, thus achieving model transformation. The LPP-based Infrared spectrometer calibration method provided by the invention is simple in operation method, high in calibration forecasting accuracy and high in reliability, and the influence of nolinear factors, noise and other redundancy characteristics in the spectrogram can be effectively eliminated.

Description

technical field [0001] The invention relates to the technical field of infrared spectrum model transfer, in particular to an infrared spectrometer calibration method based on local projection preservation. Background technique [0002] Infrared spectroscopy is widely used in industrial fields because of its fast, accurate and non-destructive. Spectral multivariate correction technology can be effectively used in the content detection of material components and online process monitoring. However, the multivariate calibration model is often limited in practical applications, mainly because the established multivariate calibration model cannot be effectively applied to spectra observed under new environmental conditions or spectra collected by different instruments. The recalibration method can overcome this limitation, but it needs to rebuild the model every time, which is quite expensive and time-consuming. [0003] model transfer [1] It is an effective method to solve the...

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Application Information

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IPC IPC(8): G01N21/25G01J3/28
Inventor 刘军王海燕姜久英
Owner JIANGSU PROVINCE INST OF QUALITY & SAFETY ENG
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