Estimation of ore mineralogy from analytical analysis of iron ore

Mohanan, Srijith; Bhoja, Sharath Kumar; Kumar, C. Raghu; Kumar, Abhishek; Venugopalan, T.

doi:10.1007/bf03402426

Cited by 4 publications

(5 citation statements)

References 2 publications

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“…It was originally developed to reduce the dimensionality of samples by grouping standard features into clusters and to produce a set of new features with a dimensional space (R) reduced to the number of neurons the operator decided to use based on his knowledge of the analyzed sample. In our case, the input space consisted of 25 two-dimensional images (R 25 ), while the output space was set to 4 (R 4 ) after several tests. The computational time for a single image processing is approximately 5′:35″ with a Ryzen 7 processor and 32 Gb RAM.…”

Section: Self-organized Mapsmentioning

confidence: 99%

“…Until a few years ago, RLM was the primary technique used to observe and study ore minerals [14][15][16][17][18][19][20], but in the last 20 years, it has been integrated and/or replaced by modern and expensive automated mineralogy (AM) systems, used for both opaque and nonopaque minerals, that take advantage of the analytical potential of the Scanning Electron Microscopy (SEM) combined with Energy Dispersive X-ray Spectroscopy (EDX) [21][22][23][24][25][26][27]. AM Systems, such as QEMSCAN ® , MLA, Mineralogic, and TIMA-X [2,[28][29][30], allow obtaining very high-resolution micro-photos and use automated image analysis (IA) tools to quantify the mineral phases and obtain statistical information on grain and particle sizes, morphology, texture, liberation degree, etc., by rastering electron beams and X-rays on specimen surfaces [31][32][33].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method for Evaluation of Ore Minerals Based on Optical Microscopy and Image Analysis: Preliminary Results

et al. 2022

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Natural or artificial light allows us to see and analyze matter with our eyes, which are the first tools used in several experiments. In geosciences, particularly in mineralogy, light is used for optical microscopy observations. Reflected and transmitted light applied to the study of ore deposits can be useful to discriminate between gangue from precious phases. Knowledge of the structural and morphological characteristics, combined with the quantitative evaluation of mineral abundance, is fundamental for determining the grade of ore deposits. The accuracy and reliability of the information are closely linked to the ability of the mineralogist, who more and more often uses Scanning Electron technology and automated mineralogy systems to validate the observations or solve complex mineralogy. While highly accurate, these methods are often prohibitively expensive. The use of image analysis using standard algorithms and artificial intelligence, available as open source, and commercial packages (such as ImageJ, Fiji or MATLAB), can provide advantages in fast, cost-effective, and robust mineral analysis. Recently, the application of neural networks provided increasingly effective image analysis and, among the different types of neural networks available today, the self-organizing maps of Kohonen (SOM) seem to be among the most promising, given their capacity to receive many images as inputs and reduce them to a low number of neuronal outputs that represent all the input characteristics in a lower-dimensional space. In this work, we will show the preliminary results of a new method based on SOM and the combined use of images acquired in transmitted and reflected light to reconstruct false 3D surfaces, which were able to show the presence of intergrow between gangue phases and precious minerals.

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Section: Self-organized Mapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Method for Evaluation of Ore Minerals Based on Optical Microscopy and Image Analysis: Preliminary Results

et al. 2022

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“…Manganese mineral is an essential raw material in the steel making process; hence, its demand is proportional to steel production. The steel industry consumes over 95% of manganese ore production, and the remaining 5% is used by the other sectors, including chemical, paint, fertilizer, and battery industries [11]. Furthermore, manganese mineral has been extensively used for different low carbon technologies [12].…”

Section: Introductionmentioning

confidence: 99%

Influence of Mineralogy on the Dry Magnetic Separation of Ferruginous Manganese Ore—A Comparative Study

et al. 2021

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Magnetic separation is often considered pertinent for manganese ore beneficiation when the ore is abundant with siliceous rich gangue mineral phases. However, the process is deemed to be inapposite for the ferruginous type of ore, and remains a grey area of research. In the present investigation, two different types of manganese ore were studied in detail to understand the influence of mineralogy on their magnetic separation performance. Detailed experiments were performed by varying the critical variables of the dry magnetic separator, and the separation features were studied. The ore samples were thoroughly characterized by various techniques, including an automated advanced mineralogical tool. The mineralogical results revealed that primary manganese bearing minerals in both the ores are rich in cryptomelene, pyrolusite, psilomelane, and bixybyite. Similarly, the major gangue minerals were alumina-bearing minerals and iron-bearing phases (hematite and goethite). The optimum grade that could be obtained from single-stage dry magnetic separation was 35.52% Mn, and with a Mn:Fe ratio of 1.77, and 44% Mn recovery in the case of sample 1; whereas, a 33.75% Mn grade, with a Mn:Fe ratio of 1.66 at Mn recovery of 44% was reported for Sample 2. It was observed that both samples had a similar input chemistry (~28% Mn, ~1 Mn: Fe ratio) however, they had distinctive mineralogical assemblages. Furthermore, it was observed that the liberation of manganese mineral was in a course size range, i.e., 300 to 450 µm, while the association of iron and manganese bearing phases was lower in sample 1 when compared to sample 2.

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“…More attention has been given in recent years to use fluxed pellets in blast furnace due to their excellent strength and improved reducibility, swelling and softening-melting characteristics (Firth, Garden and Douglas 2008). The quality of pellets are influenced by the nature of ore or concentrate, associated gangue, types of binder, type and amount of fluxes added and their subsequent treatment to produce pellets (Halt and Kawatra 2014;Halt, Roache and Kawatra 2014;Mohanan et al 2015). These factors in turn result in the variation of physicochemical properties of the coexisting phases and their distribution during pellet indurations (Semberg, Andersson and Bjorkman 2014).…”

Section: Introductionmentioning

confidence: 99%

“…The quality of pellets are influenced by the nature of ore or concentrate, associated gangue, types of binder, type and amount of fluxes added and their subsequent treatment to produce pellets (Halt and Kawatra 2014; Halt, Roache and Kawatra 2014; Mohanan et al . 2015). These factors in turn result in the variation of physico-chemical properties of the coexisting phases and their distribution during pellet indurations (Semberg, Andersson and Bjorkman 2014).…”

Section: Introductionmentioning

confidence: 99%

Effective utilisation of waste fines in preparation of high-basicity double-layer DRI pellets for minimisation of sticking

Mandal

Sinha

2016

Mineral Processing and Extractive Metallurgy

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Sinter of high basicity is well known for affecting the permeability of the burden in the lower portion of the blast furnace due to the formation of more viscous slag. The high-basicity pellets possess less weather resistance if hardened below 1200°C due to the presence of free lime particles. When hardened above 1200°C, the weather resistance increases with increasing sticking tendency among the pellets due to the formation of low-melting eutectics. In the present investigation, efforts were made to make composite-coated iron ore-fluxed pellets to minimise the problems mentioned above. Lime addition to the core of pellets varied from 5 to 100%. The composite pellets subsequently were fired at 1150, 1200 and 1250°C for 30 min. Increasing lime content in the pellets resulted in increasing crushing and drop strength of the green pellets. The percent of reduction and cold crushing strength were found comparable to the conventional pellets with varying lime content up to 30% (core basicity 4.68). Weathering resistance was also found increasing trends with increasing firing temperature. XRD analysis revealed the presence of free lime particles inside the core of composite pellets with increasing lime content. From the present work, it could be concluded that the composite-fluxed pellet made with 20% lime in the core (core basicity 3.0) has enough physical strength (187 kg), a high percentage of reduction (96%) and excellent weather resistance properties.

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Estimation of ore mineralogy from analytical analysis of iron ore

Cited by 4 publications

References 2 publications

A Novel Method for Evaluation of Ore Minerals Based on Optical Microscopy and Image Analysis: Preliminary Results

A Novel Method for Evaluation of Ore Minerals Based on Optical Microscopy and Image Analysis: Preliminary Results

Influence of Mineralogy on the Dry Magnetic Separation of Ferruginous Manganese Ore—A Comparative Study

Effective utilisation of waste fines in preparation of high-basicity double-layer DRI pellets for minimisation of sticking

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