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Issue 31, 2019
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Fast determination of oxide content in cement raw meal using NIR spectroscopy with the SPXY algorithm

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Abstract

NIR spectroscopy combined with the partial least squares (PLS) algorithm has been investigated to yield a new analytical method for the fast determination of CaO, SiO2, Al2O3 and Fe2O3 in cement raw meal samples in the process of cement production. An improved algorithm based on Kennard–Stone (KS), named sample set partitioning based on joint xy distance (SPXY), which takes into account both x (spectral variables) and y (chemical values) spaces, was applied to divide cement raw meal samples into calibration and prediction subsets, and the effect of SPXY was compared with that of random sampling (RS), KS and Duplex. Optimal predictions were obtained in most cases with the SPXY method, and the average prediction errors were 0.1430%, 0.1206%, 0.0667% and 0.0306% for CaO, SiO2, Al2O3 and Fe2O3, respectively, showing that the calibration subset selected by the SPXY method is superior to that of the other three methods, and NIR spectroscopy coupled with SPXY and PLS algorithms can achieve rapid and accurate determination of oxide content in cement raw meal samples.

Graphical abstract: Fast determination of oxide content in cement raw meal using NIR spectroscopy with the SPXY algorithm

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Article information


Submitted
09 May 2019
Accepted
29 Jun 2019
First published
01 Jul 2019

Anal. Methods, 2019,11, 3936-3942
Article type
Paper

Fast determination of oxide content in cement raw meal using NIR spectroscopy with the SPXY algorithm

Z. Yang, H. Xiao, L. Zhang, D. Feng, F. Zhang, M. Jiang, Q. Sui and L. Jia, Anal. Methods, 2019, 11, 3936
DOI: 10.1039/C9AY00967A

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