scholarly journals Automated Optical Image Analysis of Iron Ore Sinter

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 562
Author(s):  
Eugene Donskoi ◽  
Sarath Hapugoda ◽  
James Robert Manuel ◽  
Andrei Poliakov ◽  
Michael John Peterson ◽  
...  
Keyword(s):  
Image Analysis ◽  
Iron Ore ◽  
Deep Understanding ◽  
Furnace Operation ◽  
Optical Image ◽  
Phase Identification ◽  
X Ray Diffraction ◽  
X Ray ◽  
Iron Ore Sinter ◽  
Very High

Sinter quality is a key element for stable blast furnace operation. Sinter strength and reducibility depend considerably on the mineral composition and associated textural features. During sinter optical image analysis (OIA), it is important to distinguish different morphologies of the same mineral such as primary/secondary hematite, and types of silico-ferrite of calcium and aluminum (SFCA). Standard red, green and blue (RGB) thresholding cannot effectively segment such morphologies one from another. The Commonwealth Scientific Industrial Research Organization’s (CSIRO) OIA software Mineral4/Recognition4 incorporates a unique textural identification module allowing various textures/morphologies of the same mineral to be discriminated. Together with other capabilities of the software, this feature was used for the examination of iron ore sinters where the ability to segment different types of hematite (primary versus secondary), different morphological sub-types of SFCA (platy and prismatic), and other common sinter phases such as magnetite, larnite, glass and remnant aluminosilicates is crucial for quantifying sinter petrology. Three different sinter samples were examined. Visual comparison showed very high correlation between manual and automated phase identification. The OIA results also gave high correlations with manual point counting, X-ray Diffraction (XRD) and X-ray Fluorescence (XRF) analysis results. Sinter textural classification performed by Recognition4 showed a high potential for deep understanding of sinter properties and the changes of such properties under different sintering conditions.

Novel developments in optical image analysis for iron ore, sinter and coke characterisation

2015 ◽  
Vol 124 (4) ◽  
pp. 227-244 ◽  
Author(s):  
E. Donskoi ◽  
A. Poliakov ◽  
J. R. Manuel ◽  
M. Peterson ◽  
S. Hapugoda
Keyword(s):  
Image Analysis ◽  
Iron Ore ◽  
Optical Image ◽  
Iron Ore Sinter

In situX-ray diffraction analysis of iron ore sinter phases

2004 ◽  
Vol 37 (3) ◽  
pp. 362-368 ◽  
Author(s):  
Nicola V. Y. Scarlett ◽  
Ian C. Madsen ◽  
Mark I. Pownceby ◽  
Axel N. Christensen
Keyword(s):  
Iron Ore ◽  
Rietveld Method ◽  
Structural Type ◽  
X Ray Diffraction ◽  
X Ray ◽  
Intermediate Phases ◽  
Iron Ore Sinter ◽  
Phase Quantification ◽  
Bonding Phase

Owing to the depletion of world lump iron ore stocks, pre-treated agglomerates of fine ores are making up a growing proportion of blast-furnace feedstock (∼80%). These agglomerations, or `sinters', are generally composed of iron oxides, ferrites (most of which are silicoferrites of calcium and aluminium, SFCAs), glasses and dicalcium silicates (C2S). SFCA is the most important bonding phase in iron ore sinter, and its composition, structural type and texture greatly affect its physical properties. Despite its prevalence and importance, the mechanism of SFCA formation is not fully understood.In situpowder X-ray diffraction investigations have been conducted into the formation of SFCA, allowing the study of the mechanism of its formation and the observation of intermediate phases with respect to time and temperature. Studies have been carried out to investigate the effects of changing the substitution levels of aluminium for iron. The use of the Rietveld method for phase quantification gives an indication of the order and comparative rates of phase formation throughout the experiments.

scholarly journals Advances in Optical Image Analysis Textural Segmentation in Ironmaking

2020 ◽  
Vol 10 (18) ◽  
pp. 6242 ◽  
Author(s):  
Eugene Donskoi ◽  
Andrei Poliakov
Keyword(s):  
Image Analysis ◽  
Chemical Composition ◽  
Software Package ◽  
Iron Ore ◽  
Optical Image ◽  
Point Counting ◽  
Analysis Software ◽  
Image Analysis Software ◽  
Iron Ore Sinter ◽  
Feedstock Material

Optical image analysis is commonly used to characterize different feedstock material for ironmaking, such as iron ore, iron ore sinter, coal and coke. Information is often needed for phases which have the same reflectivity and chemical composition, but different morphology. Such information is usually obtained by manual point counting, which is quite expensive and may not provide consistent results between different petrologists. To perform accurate segmentation of such phases using automated optical image analysis, the software must be able to identify specific textures. CSIRO’s Carbon Steel Futures group has developed an optical image analysis software package called Mineral4/Recognition4, which incorporates a dedicated textural identification module allowing segmentation of such phases. The article discusses the problems associated with segmentation of similar phases in different ironmaking feedstock material using automated optical image analysis and demonstrates successful algorithms for textural identification. The examples cover segmentation of three different coke phases: two types of Inert Maceral Derived Components (IMDC), non-reacted and partially reacted, and Reacted Maceral Derived Components (RMDC); primary and secondary hematite in iron ore sinter; and minerals difficult to distinguish with traditional thresholding in iron ore.

Structural Analysis of Sinter with Titanium Addition / Analiza Strukturalna Spieku Z Dodatkiem Tytanu

2013 ◽  
Vol 58 (1) ◽  
pp. 179-185 ◽  
Author(s):  
M. Fröhlichová ◽  
R. Findorák ◽  
J. Legemza
Keyword(s):  
Phase Composition ◽  
Chemical Composition ◽  
Iron Ore ◽  
Strength Properties ◽  
X Ray Diffraction ◽  
Sinter Production ◽  
Titanium Addition ◽  
X Ray ◽  
Iron Ore Sinter ◽  
The Relationship

Paper presents the results from the study of the effect of materials with titanium addition on the strength properties of the iron ore sinter. The sinters with TiO2 addition or without TiO2 addition prepared in laboratory were applied in this research and were compared based on the structural and phase composition. Exploited was the method of the X-ray diffraction and method of elemental EDX analysis applying the electron raster microscope with the energo-dispersion analyser. Confirmed was the relationship between the sinter structure and its strength. Higher strength of the sinter without TiO2 addition is the result of the different phase composition of the compared sinters. In the sinter production considered should be not only the chemical composition of the entry components of the charge and the chemical composition of the final product but also its structural and phase composition.

Predicting iron ore sinter strength through partial least square regression (PLSR) analysis of X-ray diffraction patterns

2017 ◽  
Vol 32 (S2) ◽  
pp. S66-S69
Author(s):  
Nathan A.S. Webster ◽  
Mark I. Pownceby ◽  
Natalie Ware ◽  
Rachel Pattel
Keyword(s):  
Process Control ◽  
Iron Ore ◽  
Partial Least Square ◽  
Least Square ◽  
Process Conditions ◽  
X Ray Diffraction ◽  
X Ray ◽  
Sinter Strength ◽  
Iron Ore Sinter

The decrease in quality of Australian iron ore, coupled with the demand for more efficient energy use, means that closer monitoring and optimisation of process conditions for iron ore sinter production is required. Here, the suitability of using partial least-squares regression analysis of powder X-ray diffraction data, collected for iron ore sinter samples, for the prediction of iron ore sinter strength has been further assessed. In addition, a preliminary assessment of the effect of 2θ range on the quality of prediction has been made. For the purposes of process control, the level of correlation between predicted strength and actual sinter strength would inform an operator whether or not the process was operating within the acceptable limits, or whether there was a potential problem requiring further investigation or rapid intervention. Reducing the 2θ range was found to reduce the level of correlation between predicted and actual strength, to a point where the particular analysis may no longer be suitable for process control.

Defect-Mediated Conductivity Enhancements in Na3-xPn1-xWxS4 (Pn = P, Sb) using Aliovalent Substitutions

2019 ◽  
Author(s):  
Till Fuchs ◽  
Sean Culver ◽  
Paul Till ◽  
Wolfgang Zeier
Keyword(s):  
Ionic Conductivity ◽  
Vacancy Concentration ◽  
Sodium Ion ◽  
High Ionic Conductivity ◽  
Ionic Conductors ◽  
X Ray Diffraction ◽  
X Ray ◽  
Solid State Batteries ◽  
Ion Conducting ◽  
Very High

<p>The sodium-ion conducting family of Na<sub>3</sub><i>Pn</i>S<sub>4</sub>, with <i>Pn</i> = P, Sb, have gained interest for the use in solid-state batteries due to their high ionic conductivity. However, significant improvements to the conductivity have been hampered by the lack of aliovalent dopants that can introduce vacancies into the structure. Inspired by the need for vacancy introduction into Na<sub>3</sub><i>Pn</i>S<sub>4</sub>, the solid solutions with WS<sub>4</sub><sup>2-</sup> introduction are explored. The influence of the substitution with WS<sub>4</sub><sup>2-</sup> for PS<sub>4</sub><sup>3-</sup> and SbS<sub>4</sub><sup>3-</sup>, respectively, is monitored using a combination of X-ray diffraction, Raman and impedance spectroscopy. With increasing vacancy concentration improvements resulting in a very high ionic conductivity of 13 ± 3 mS·cm<sup>-1</sup> for Na<sub>2.9</sub>P<sub>0.9</sub>W<sub>0.1</sub>S<sub>4</sub> and 41 ± 8 mS·cm<sup>-1</sup> for Na<sub>2.9</sub>Sb<sub>0.9</sub>W<sub>0.1</sub>S<sub>4</sub> can be observed. This work acts as a stepping-stone towards further engineering of ionic conductors using vacancy-injection via aliovalent substituents.</p>

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