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Issue 5, 2020
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The high-accuracy prediction of carbon content in semi-coke by laser-induced breakdown spectroscopy

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Semi-coke, as a kind of special coal resource with a relatively high concentration of carbon and low volatility, plays an important role in the coal chemical industry and in creating clean cities. Laser-induced breakdown spectroscopy (LIBS) has been proved to be an effective way to conduct online analysis of coal products. However, the lower volatility of semi-coke makes it hard to press into a slice to obtain a smooth surface for uniform laser-irradiation. Therefore, it is necessary to find an effective way to realize high-accuracy LIBS detection for semi-coke applications. Herein, two feasible methods of sample preparation are attempted, one easy way involves directly painting semi-coke powder onto tape that is suitable for online fast monitoring, and the other more complicated way is to mix a binder into the semi-coke powder so that uniform and tight coal slices are obtained, to improve the repeatability of the measurements. Moreover, a totally new algorithm, a support vector machine (SVM) combined with partial least square (PLS) regression (SVM-PLS), was utilized to establish an effective prediction model to give a high predictive accuracy. The coefficient of determination (R2), root mean square error of prediction (RMSEP), and average relative error (ARE) are 0.944, 0.90%, and 0.80%, respectively. In comparison with the results from the traditional PLS model, SVM residual correction greatly improves the quality of the calibration curve and the RMSEP and ARE values are reduced to 0.17%, thus improving the prediction accuracy, which is much better than the basic PLS regression. Meanwhile, the prediction error from the binder mixed semi-coke slice is significantly reduced compared to that of the directly painted samples on tape. The maximum relative errors (MREs) are 2.71% and 5.19%, and the average RSD values of the characteristic peaks are 12.1% and 16.2%, respectively, indicating that the easy way of painting a sample on tape has some prediction uncertainties. Finally, in a three-day random test, the average RMSEP was found to be 1.89% and the average ARE was 1.74%, which also proves that the binder additive can effectively reduce the matrix effect and enhance the stability of the spectrum for semi-coke measurements. The results indicate that appropriate LIBS analysis on semi-coke is a feasible and promising approach for online predictions using this kind of coal sample.

Graphical abstract: The high-accuracy prediction of carbon content in semi-coke by laser-induced breakdown spectroscopy

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Article information

25 Dec 2019
23 Mar 2020
First published
24 Mar 2020

J. Anal. At. Spectrom., 2020,35, 984-992
Article type

The high-accuracy prediction of carbon content in semi-coke by laser-induced breakdown spectroscopy

X. Xu, A. Li, X. Wang, C. Ding, S. Qiu, Y. He, T. Lu, F. He, B. Zou and R. Liu, J. Anal. At. Spectrom., 2020, 35, 984
DOI: 10.1039/C9JA00443B

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