On-stream and quantitative mineral identification of tailing slurries using LIBS technique

Mineral flotation processes are controlled by monitoring the grade of the present minerals. The performance of flotation can be greatly optimized by online assaying of the minerals in the slurry flows. However, online and quantitative mineral identification of the slurries is challenging. The major focus of this research is about measuring mineral contents from the elemental concentrations acquired by an on-stream slurry analyzer operating based on laser-induced breakdown spectroscopy (LIBS). A multivariate statistical method called partial least squares regression is employed to perform the elemental to mineral conversion. In this work, the samples under study come from an iron concentrator where knowledge about the grade of silicates and iron-oxides are important for controlling the flotation plant. In total, the concentrations of six out of ten minerals were successfully estimated. This accomplishment provides quantitative knowledge about mineral contents from the nearly real-time assay data without any modification on the measurement setup or further instrumentation. This can lead to many benefits such as rapid control of concentrate quality, enhanced recovery and savings in money, time, energy and manpower. The proposed technique is applicable to all types of slurry samples.