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Use of X-ray Micro-computed Tomography (µCT) for 3-D Ore Characterization: A Turning Point in Process Mineralogy
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering. (Mineralteknik)ORCID iD: 0000-0002-8693-1054
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.ORCID iD: 0000-0002-5228-3888
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.ORCID iD: 0000-0003-4861-1903
2019 (English)In: IMCET 2019 - Proceedings of the 26th International Mining Congress and Exhibition of Turkey, Baski , 2019, p. 1044-1054Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, automated mineralogy has become an essential enabling technology in the field of process mineralogy, allowing better understanding between mineralogy and the beneficiation process. Recent developments in X-ray micro-computed tomography (μCT) as a non-destructive technique have indicated great potential to become the next automated mineralogy technique. μCT’s main advantage lies in its ability to allow 3-D monitoring of internal structure of the ore at resolutions down to a few hundred nanometers, thereby eliminating the stereological error encountered in conventional 2-D analysis. Driven by the technological and computational progress, the technique is continuously developing as an analysis tool in ore characterization and subsequently it foreseen thatμCT will become an indispensable technique in the field of process mineralogy. Although several software tools have been developed for processing μCT dataset, but the main challenge in μCT data analysis remains in the mineralogical analysis, where μCT data often lacks contrast between mineral phases, making segmentation difficult. In this paper, an overview of some current applications of μCT in ore characterization is reviewed, alongside with it potential implications to process mineralogy. It also describes the current limitations of its application and concludes with outlook on the future development of 3-D ore characterization.

Place, publisher, year, edition, pages
Baski , 2019. p. 1044-1054
Keywords [en]
X-ray micro-tomography (µCT), process mineralogy, ore characterization
National Category
Metallurgy and Metallic Materials
Research subject
Mineral Processing
Identifiers
URN: urn:nbn:se:ltu:diva-73716Scopus ID: 2-s2.0-85074175797OAI: oai:DiVA.org:ltu-73716DiVA, id: diva2:1306121
Conference
26th International Mining Congress and Exhibition (IMCET 2019), Antalya, Turkey, April 16-19, 2019
Funder
EU, Horizon 2020Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2023-12-19Bibliographically approved
In thesis
1. X-ray microcomputed tomography (µCT) as a potential tool in Geometallurgy
Open this publication in new window or tab >>X-ray microcomputed tomography (µCT) as a potential tool in Geometallurgy
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In recent years, automated mineralogy has become an essential tool in geometallurgy. Automated mineralogical tools allow the acquisition of mineralogical and liberation data of ore particles in a sample. These particle data can then be used further for particle-based mineral processing simulation in the context of geometallurgy. However, most automated mineralogical tools currently in application are based on two-dimensional (2D) microscopy analysis, which are subject to stereological error when analyzing three-dimensional(3D) object such as ore particles. Recent advancements in X-ray microcomputed tomography (µCT) have indicated great potential of such system to be the next automated mineralogical tool. µCT's main advantage lies on its ability in monitoring 3D internal structure of the ore at resolutions down to few microns, eliminating stereological error obtained from 2D analysis. Aided with the continuous developments of computing capability of 3D data, it is only the question of time that µCT system becomes an interesting alternative in automated mineralogy system.

This study aims to evaluate the potential of implementing µCT as an automated mineralogical tool in the context of geometallurgy. First, a brief introduction about the role of automated mineralogy in geometallurgy is presented. Then, the development of µCT system to become an automated mineralogical tool in the context of geometallurgy andprocess mineralogy is discussed (Paper 1). The discussion also reviews the available data analysis methods in extracting ore properties (size, mineralogy, texture) from the 3D µCT image (Paper 2). Based on the review, it was found that the main challenge inperforming µCT analysis of ore samples is the difficulties associated to the segmentation of the mineral phases in the dataset. This challenge is adressed through the implementation of machine learning techniques using Scanning Electron Microscope (SEM) data as a reference to differentiate the mineral phases in the µCT dataset (Paper 3).

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2019. p. 74
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
Keywords
X-ray microcomputed tomography, geometallurgy, automated mineralogy, ore characterization
National Category
Mineral and Mine Engineering Metallurgy and Metallic Materials
Research subject
Mineral Processing
Identifiers
urn:nbn:se:ltu:diva-76576 (URN)978-91-7790-492-2 (ISBN)978-91-7790-493-9 (ISBN)
Presentation
2019-12-13, F531, Luleå University of Technology, Luleå, 10:00 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020, 722677
Available from: 2019-10-30 Created: 2019-10-30 Last updated: 2023-12-19Bibliographically approved
2. X-ray microcomputed tomography (µCT) as a potential tool in particle-based geometallurgy
Open this publication in new window or tab >>X-ray microcomputed tomography (µCT) as a potential tool in particle-based geometallurgy
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In recent years, automated mineralogy has become an essential tool in geometallurgy. Automated mineralogical tools allows the acquisition of mineralogical, textural, and liberation information of ore samples. Such information is essential in the context of geometallurgy where it is needed for estimating the process response of the ores. Most automated mineralogical tools currently in application are based on two-dimensional (2D) microscopy analysis, which are subject to stereological error when analyzing three-dimensional (3D) object such as ore particles. Recent advancements in X-ray microcomputed tomography (μCT) have indicated great potential of such system to be the next automated mineralogical tool. μCT’s main advantage lies in its ability in monitoring 3D internal structure of the ore at resolutions down to few microns, eliminating stereological error obtained from 2D analysis. Aided with the continuous developments of computing capability of 3D data, it is only the question of time that μCT system becomes an interesting alternative automated mineralogical tool for ore characterization.

This study systematically evaluates the applicability of μCT as an alternative tool for ore characterization in the context of geometallurgy. The focus has been to assess the potential strengths of 3D data generated from μCT as well as how such data can offer a new perspective in characterizing the ore. Some of the limitations of 3D μCT data in describing the ore were also discussed, with alternative methods proposed to address these limitations. The main hypothesis of the study is that 3D data generated from μCT can be of a value in a geometallurgical program. This study has been conducted in three different parts in order to systematically test the hypothesis. The first part of the study evaluated the use of μCT to obtain mineralogical characteristics of the ore. Mineralogy of the ore is the cornerstone information needed to proceed with further characterization of the ore. It is therefore important to establish whether μCT are capable to obtain such information. The study demonstrated the well-known limitation of μCT, namely its difficulty when dealing with minerals of similar attenuation. The study demonstrated how machine-learning based methods complemented with 2D data from automated mineralogy could address the limitation.

The capability of μCT for ore texture characterization was evaluated in the second part of the study. The main strength of μCT for core scanning is highlighted in the study, in which the possibility of using μCT for automated drill core recognition was demonstrated. Some of the popular texture analysis methods in 2D such as Local Binary Pattern (LBP) and Association Index Matrix (AIM) were extended to 3D in order to capture the textural pattern in drill core samples. Furthermore, a classification scheme based on these textural characteristics was devised for the automated recognition of the drill cores. An accuracy of 84-88% was achieved in the classification scheme, illustrating the potential of μCT for such task.

The last part of the study concerns the use of μCT for mineral liberation modeling. Combining both mineralogical and textural information obtained from the previous parts of the study, a liberation model to forecast particle population from the 3D ore texture was created. The model was based on various breakage types such as preferential, phase boundary, and random breakage. The contribution of each breakage type to the final particle population could then be adjusted with actual particles produced from experimental comminution. Accurate forecasting of particle population is one of the key componentin the particle-based geometallurgy, in which the particle carries the ore characteristics to the beneficiation process. Utilizing these particles in a process modeling and simulation would give some idea about the process response of the ore. The integration of 3D data from μCT with the liberation model could potentially complete the link from ore characteristics to the process behavior in the framework of particle-based geometallurgy.

Combination of these three parts of the study can open up a 3D path of particle-based geometallurgy. The study has demonstrated the efficient extraction of crucial ore characteristics such as texture, mineralogy, and mineral liberation using μCT. Key limitations and potential measures to address them have also been discussed in the study. Coupled with a framework for process simulation using such ore characteristics as an input, the 3D path of particle-based geometallurgy can be realized. Future research should be dedicated to develop such framework, as the establishment of μCT as an alternative ore characterization tool should also be motivated by from the downstream processes, i.e.whether the 3D μCT data can unlock a new perspective in process modeling and simulation compared to the conventional 2D data. This new perspective can help to build more accurate process prediction and production forecasting, which can ultimately guide the decision-making process for efficient resource management as the essential core of a geometallurgical program.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2020
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
X-ray microcomputed tomography, Mineralogy, Texture, Liberation, Geometallurgy
National Category
Metallurgy and Metallic Materials
Research subject
Mineral Processing
Identifiers
urn:nbn:se:ltu:diva-81042 (URN)978-91-7790-673-5 (ISBN)978-91-7790-674-2 (ISBN)
Public defence
2020-12-02, F1031, Campus Luleå, Luleå University of Technology, Luleå, 10:00 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020, 722677
Available from: 2020-10-07 Created: 2020-10-06 Last updated: 2023-12-19Bibliographically approved

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