Application of Sample Selection and PDS-PLS Algorithms in Near Infrared Spectra Analysis Model Transfer

doi:10.3969/j.issn.1000-1093.2016.01.014

Abstract

Abstract: A transfer method of near infrared (NIR) spectra analysis model is studied in order to enable one instrument (reference instrument) and the other one (target instrument) to share the model. The transfer set samples are selected with Mahalanobis distances by taking an analysis model of mixed-amine fuel for example, and the algorithm of piecewise direct standardization (PDS) combined partial least squares (PLS) is used to set the spectral correction matrix between the reference and target instruments. The number of transfer samples, the number of prime factors of PLS regression and the window width of PDS are confirmed based on the average of root mean square (ARMS) of corrected spectra of transfer samples. The corrected rate of spectra of transfer samples reachs 96.5% with transfer sample number of 12 and prime factor number of 1 and window width of 39. Standard deviation of prediction set (SEP) of every analysis item on target instrument is near SEP on reference instrument after the analysis model of mixed-amine is transferred, the transferred model can predicate triethylamine content, xylidine content, water content and density accurately. The results indicate that the sample selection based on Mahalanobis distances and PDS-PLS algorithms can deduct the difference of NIR spectra among instruments and improve the analytical accuracy of NIR model.

Key words: optics, spectral analysis, near infrared spectra, model transfer, Mahalanobis distance, piecewise direct standardization, partial least squares, mixed amine

CLC Number:

O657.33

WANG Ju-xiang, MENG Fan-lei， LIU Lin-mi， CUI Wei-cheng. Application of Sample Selection and PDS-PLS Algorithms in Near Infrared Spectra Analysis Model Transfer[J]. Acta Armamentarii, 2016, 37(1): 91-96.

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