PDF

Minerals 2022, 12, 1052. https://doi.org/10.3390/min12081052

Jacek Galas, Dariusz Litwin

2022Englishmineral processingbeneficiationcomminutionflotationphysical separationmachine learning

Abstract

Language:

The paper is focused on the analysis of the relation between the stability of the flotation process and the efficiency of Machine Learning (ML) algorithms based on the flotation froth images. An ML process should enable researchers to construct Artificial Intelligence (AI) algorithms for flotation process control. The image of the flotation froth includes information characterizing the flotation process. The information can be extracted with the aid of the Image Recognition (IR) algorithms based on the ML. This enables construction of a flotation process control system in the mineral processing plant, which is based on the recognition of images of the flotation froth. The IR algorithms do not provide stable image recognition results and are not efficient in the situation where the parameters of the flotation process are highly unstable. The classification results were equal to 75.11% and 69.62% for a stable and unstable process, respectively. The experimental data collected at the Polish Pb/Zn mineral processing plant provided better insight to the relationships between the flotation process parameters and ML efficiency. These relationships were analyzed, and guidelines for the construction of the ML process for flotation process control have been formulated.

Download

Cite This Work

@article{8d52aa53-36be-4c1d-95d9-b9ee1bcd3d36,
  title={Minerals 2022, 12, 1052. https://doi.org/10.3390/min12081052},
  author={Jacek Galas and Dariusz Litwin},
  year={2022},
  language={English}
}
TY  - JOUR
TI  - Minerals 2022, 12, 1052. https://doi.org/10.3390/min12081052
AU  - Jacek Galas
AU  - Dariusz Litwin
PY  - 2022
LA  - English
ER  -

Similar Items

Enhanced accumulation of bitumen residue in a highly concentrated tailings flow by microbubbles from in-situ catalytic decomposition of hydrogen peroxide

Kaiyu Zhou, Somasekhara Goud Sontti

The massive volume of oil sands tailings has been one of the most challenging environmental issues. In this work, we experimentally explore a simple a

2022EnglishPDF

Experimental implementation of an economic model

Paulina Quintanilla, Daniel Navia

We present the implementation of a novel economic model predictive control (E-MPC) strategy for froth flotation, the largest tonnage mineral separatio

2021EnglishPDF

SME Author Guidelines

Franziska Strube, Thomas Wilhelm

The demand for lithium, as well as other critical resources, needed for electrochemical energy storage is expected to grow significantly in the future

2021EnglishPDF

HYDRODYNAMIC EFFECTS ON THE FLOTATION OF PLATINUM ORE IN A PILOT FLOTATION PLANT

Erika van Tonder

This thesis investigates the effect of ore blends on milling and flotation performance. Anglo Platinum’s Waterval UG2 concentrator in Rustenburg proce

2004EnglishPDF

Optimization of the SAG Grinding Process Using Statistical Analysis and Machine Learning: A Case Study of the Chilean Copper Mining Industry

Manuel Saldaña, Edelmira Gálvez

Considering the continuous increase in production costs and resource optimization, more than a strategic objective has become imperative in the copper

2023EnglishPDF

Gold Extraction - Bigger and better

John Chadwick

This article surveys contemporary technological developments aimed at enhancing the efficiency, selectivity, and sustainability of gold extraction and

2007enPDF