Issue 27, 2019

Rapid quantitative analysis of the acidity of iron ore by the laser-induced breakdown spectroscopy (LIBS) technique coupled with variable importance measures-random forests (VIM-RF)

Abstract

Rapid and online analysis of the acidity of iron ore is extremely important for reasonable and efficient utilization of mineral resources. In this study, the laser-induced breakdown spectroscopy (LIBS) technique coupled with variable importance measures-random forests (VIM-RF) was proposed and applied for rapid and effective analysis of acidity in iron ore. LIBS spectra of 50 iron ore samples were collected, and the characteristic spectral lines of major elements (Ca, Mg, Si and Al) in iron ore samples were identified based on the National Institute of Standards and Technology (NIST) database. Different pre-processing methods, input variables and RF calibration model parameters were investigated and optimized by 5-fold cross validation (CV), and variable importance measurement (VIM) was used to optimize the input variables of the RF calibration model. In order to further verify the predictive ability and robustness of the VIM-RF calibration model, three calibration models of VIM-RF, partial least squares (PLS) and least squares support vector machine (LS-SVM) were applied for the quantitative analysis of acidity in iron ore, and the correlation coefficient (R2) and root mean squared error (RMSE) were evaluation indices. The results show that the VIM-RF model exhibits an excellent predictive performance compared with the other two calibration models both for the calibration set and prediction set. Therefore, the LIBS technique combined with VIM-RF can achieve a rapid acidity analysis of iron ores, and it will provide a new method and technology for selection and quality control of iron ore in the metallurgical industry.

Graphical abstract: Rapid quantitative analysis of the acidity of iron ore by the laser-induced breakdown spectroscopy (LIBS) technique coupled with variable importance measures-random forests (VIM-RF)

Supplementary files

Article information

Article type
Paper
Submitted
03 May 2019
Accepted
04 Jun 2019
First published
04 Jun 2019

Anal. Methods, 2019,11, 3419-3428

Rapid quantitative analysis of the acidity of iron ore by the laser-induced breakdown spectroscopy (LIBS) technique coupled with variable importance measures-random forests (VIM-RF)

P. Wang, N. Li, C. Yan, Y. Feng, Y. Ding, T. Zhang and H. Li, Anal. Methods, 2019, 11, 3419 DOI: 10.1039/C9AY00926D

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements