A critical review of artificial intelligence in mineral concentration

A Gomez-Flores, S Ilyas, GW Heyes, H Kim - Minerals Engineering, 2022 - Elsevier
Although various articles have reviewed the application of artificial intelligence (AI) in froth
flotation (summarized in this article), other unit operations for mineral concentration in …

Rock lithological classification by hyperspectral, range 3D and color images

FJ Galdames, CA Perez, PA Estévez… - … and Intelligent Laboratory …, 2019 - Elsevier
Mine operations in the future will require automatic rock characterization at many different
stages, since it can be used to supervise and optimize various processes in the laboratory …

A machine vision approach to on-line estimation of run-of-mine ore composition on conveyor belts

J Tessier, C Duchesne, G Bartolacci - Minerals Engineering, 2007 - Elsevier
Variations in run-of-mine ore properties such as size, composition, and grindability strongly
affect AG and SAG mills performance. In the past, most efforts to track and control these …

Development of a new soft sensor method using independent component analysis and partial least squares

H Kaneko, M Arakawa, K Funatsu - AIChE Journal, 2009 - Wiley Online Library
Soft sensors are used widely to estimate a process variable which is difficult to measure
online. One of the crucial difficulties of soft sensors is that predictive accuracy drops due to …

Ore grade estimation by feature selection and voting using boundary detection in digital image analysis

CA Perez, PA Estévez, PA Vera, LE Castillo… - International Journal of …, 2011 - Elsevier
In mining, rock classification plays a crucial role at different stages of the extraction process
ranging from the design of the mine to mineral grading and plant control. In this paper we …

Development of machine vision-based ore classification model using support vector machine (SVM) algorithm

AK Patel, S Chatterjee, AK Gorai - Arabian Journal of Geosciences, 2017 - Springer
The product of the mining industry (ore) is considered to be the raw material for the metal
industry. The destination policy of the raw materials of iron mine is highly dependent on the …

Practical way to quantify minerals from chemical assays at Malmberget iron ore operations–An important tool for the geometallurgical program

C Lund, P Lamberg, T Lindberg - Minerals Engineering, 2013 - Elsevier
This is the first step in establishing a geometallurgical program for the Malmberget iron ore
deposit, northern Sweden. Geometallurgy captures geological and metallurgical …

Rock lithological instance classification by hyperspectral images using dimensionality reduction and deep learning

FJ Galdames, CA Perez, PA Estevez… - … and Intelligent Laboratory …, 2022 - Elsevier
The mining operations are part of the industry 4.0 revolution, and there is a need in
developing new ways to produce a flow of information among all the processes of a plant. In …

Rock lithological classification using multi-scale Gabor features from sub-images, and voting with rock contour information

CA Perez, JA Saravia, CF Navarro, DA Schulz… - International Journal of …, 2015 - Elsevier
Estimation of rock composition in mining plants is important for determining rock size and
grindability which, in turn, may improve control of the grinding process. Variations in ore …

Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization

M Arrieta, ZX Zhang - Acta Geotechnica, 2024 - Springer
The strength of rockfills and waste materials is significantly influenced by their particle size
distribution (PSD). For large waste rockfills, PSD is fundamental to determine the shear …