Spectral Characterization of Copper and Iron Sulfide Combustion: A Multivariate Data Analysis Approach for Mineral Identification on the Blend

Abstract

The pyrometallurgical processes for primary copper production have only off-line and time-demanding analytical techniques to characterize the in and out streams of the smelting and converting steps. Since these processes are highly exothermic, relevant process information could potentially be obtained from the visible and near-infrared radiation emitted to the environment. In this work, we apply spectral sensing and multivariate data analysis methodologies to identify and classify copper and iron sulfide minerals present in the blend from spectra measured during their combustion in a laboratory drop-tube setup, in which chemical reactions that take place in flash smelting furnaces can be reproduced. Controlled combustion experiments were conducted with two industrial concentrates and with high-grade mineral species as well, with a focus on pyrite and chalcopyrite. Exploratory analysis by means of Principal Component Analysis (PCA) applied on the spectral data depicted high correlation features among species with similar elemental compositions. Classification algorithms were tested on the spectral data, and a classification accuracy of 95.3% with a support vector machine (SVM) algorithm with a Gaussian kernel was achieved. The results obtained by the described procedures are shown to be very promising as a first step in the development of a predictive and analytical tool in search of fitting the current need for real-time control of pyrometallurgical processes.

On the Detection of Spectral Emissions of Iron Oxides in Combustion Experiments of Pyrite Concentrates

“…As reported in the literature [2,[4][5][6], spectroscopy and optical techniques are suitable, nondestructive and contactless sensing alternatives to characterize combustion processes. In particular, some authors have reported the FeO spectral emission pattern in the visible (VIS) spectral range as reported by West and Broida in their work [7].…”

“…Arias et al [2] reported some spectral features found in radiation emitted from copper concentrate flash smelting and applied optical pyrometry techniques for temperature estimation. Diaz et al [6] applied multivariate data analysis methods to describe and to classify spectral information from the combustion of pure copper and iron sulfide minerals. The present work aims to provide new insights on the spectral characterization of such processes, and it is specifically focused on the detection of weak FeO and Fe 3 O 4 spectral emission signals.…”

A Radiometric Technique for Monitoring the Desulfurization Process of Blister Copper

“…Specifically, among the factors that must be considered there are multiple chemical reactions, changes in the temperature, and the formation of gases and other intermediate species. In order to overcome these issues, many techniques have been proposed for characterizing and monitoring pyrometallurgical processes based on the measurement of optical properties such as the visible-near-infrared (VIS-NIR) spectral emissions [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. On the one hand, in the iron and steel industry, several optical studies based on radiometry and spectral imaging have measured molten-phase temperature, the steel emissivity, and the slag absorption and reflection coefficients.…”

“…[ 17 , 18 , 19 , 20 , 21 ]. On the other hand, only few developments based on optical technology for control and monitoring of copper pyrometallurgical processes have been reported [ 10 , 11 , 12 , 13 , 14 , 15 , 22 ]. Nowadays, there is only one instrument [ 22 ] commercially available for this industry, and it is only intended for monitoring the first stage of the process through the measurement of exhaust gases concentration such as PbS, PbO, and CuOH.…”

“…Nowadays, there is only one instrument [ 22 ] commercially available for this industry, and it is only intended for monitoring the first stage of the process through the measurement of exhaust gases concentration such as PbS, PbO, and CuOH. As a consequence, many of the methods used to control and monitor the processes in this industry are still qualitative, lack of accuracy, and, in many cases, depend on the decisions taken by an operator [ 10 , 11 , 13 , 15 ].…”