TY - BOOK

T1 - Evaluation of lumpy iron carriers by image processing

AU - Kain-Bückner, Birgit

N1 - embargoed until 13-11-2023

PY - 2018

Y1 - 2018

N2 - Lumpy iron carriers are tested in many ways according to their physical, mechanical and chemical properties. However, the mineralogy and textural attributes are not part of a testing program for determination of the reducibility and behavior during the reduction process in the blast furnace. The mineral abundance, crystal size and shape, as well as the porosity play important roles for the reduction of lumpy iron carriers. The simplified pathway of the reduction is as follows: limonite -> hematite -> magnetite -> wuestite -> metallic iron. To determine the influence of the mineralogical and petrographic parameters on the reducibility, the image processing software VisuMet was developed. The algorithms are based on detailed microscopic investigations of twenty lumpy iron carrier samples before and after ISO-4695 testing. Eight iron ore samples derive from different banded iron formation deposits in Australia, Africa, South America, China and India. In addition, a magmatic iron ore from the Kiruna deposit, Sweden, was evaluated. The iron ore samples can be divided into three groups due to their contents of limonite, hematite and magnetite. One group consists of lumpy iron ores with a certain amount of limonite and hematite. Another group comprises high grade hematitic iron ores and the last group consists of a magnetite ore from Kiruna. The nine investigated pellet samples are from world-wide traded pellet brands and mainly consist of hematite, magnetite and glass. The major differences affecting the reducibility of the pellet samples are pore size and distribution. The two sinter samples from Austria comprise the phases hematite, magnetite, calcio- and silicioferrites and glass. VisuMet processes micro-images of polished sections of the samples and provides, beside the mineral abundance, a simulation of the reduction progress according to the shrinking core model and the Danielsson algorithm. It calculates the characteristic area degradation curve of lumpy iron ore samples and performs statistical analyses of pore sizes larger than 2 µm for pellet samples. The evaluations are compared to the results of ISO-4695 reduction tests of the respective samples. It was found that iron ores with a high proportion of limonite are reduced faster than pure hematite and magnetite ores. The rate of the area degradation of the lump ore samples correlates with the weight loss rate of the reduction test by a determination coefficient of 92 %. The mean equivalent pore diameter of the pellet samples and the time needed to reach 80 % reduction degree correlate with a coefficient of 91 %. However, the reduction rate correlates with a determination coefficient of 67 % with the mean equivalent pore diameter. The phase classification and quantification by VisuMet were compared to manual point counting of six polished sections from different lumpy iron carriers. The mineral abundance determination of VisuMet was well in accordance with optical microscopy.

AB - Lumpy iron carriers are tested in many ways according to their physical, mechanical and chemical properties. However, the mineralogy and textural attributes are not part of a testing program for determination of the reducibility and behavior during the reduction process in the blast furnace. The mineral abundance, crystal size and shape, as well as the porosity play important roles for the reduction of lumpy iron carriers. The simplified pathway of the reduction is as follows: limonite -> hematite -> magnetite -> wuestite -> metallic iron. To determine the influence of the mineralogical and petrographic parameters on the reducibility, the image processing software VisuMet was developed. The algorithms are based on detailed microscopic investigations of twenty lumpy iron carrier samples before and after ISO-4695 testing. Eight iron ore samples derive from different banded iron formation deposits in Australia, Africa, South America, China and India. In addition, a magmatic iron ore from the Kiruna deposit, Sweden, was evaluated. The iron ore samples can be divided into three groups due to their contents of limonite, hematite and magnetite. One group consists of lumpy iron ores with a certain amount of limonite and hematite. Another group comprises high grade hematitic iron ores and the last group consists of a magnetite ore from Kiruna. The nine investigated pellet samples are from world-wide traded pellet brands and mainly consist of hematite, magnetite and glass. The major differences affecting the reducibility of the pellet samples are pore size and distribution. The two sinter samples from Austria comprise the phases hematite, magnetite, calcio- and silicioferrites and glass. VisuMet processes micro-images of polished sections of the samples and provides, beside the mineral abundance, a simulation of the reduction progress according to the shrinking core model and the Danielsson algorithm. It calculates the characteristic area degradation curve of lumpy iron ore samples and performs statistical analyses of pore sizes larger than 2 µm for pellet samples. The evaluations are compared to the results of ISO-4695 reduction tests of the respective samples. It was found that iron ores with a high proportion of limonite are reduced faster than pure hematite and magnetite ores. The rate of the area degradation of the lump ore samples correlates with the weight loss rate of the reduction test by a determination coefficient of 92 %. The mean equivalent pore diameter of the pellet samples and the time needed to reach 80 % reduction degree correlate with a coefficient of 91 %. However, the reduction rate correlates with a determination coefficient of 67 % with the mean equivalent pore diameter. The phase classification and quantification by VisuMet were compared to manual point counting of six polished sections from different lumpy iron carriers. The mineral abundance determination of VisuMet was well in accordance with optical microscopy.

KW - lumpy iron carriers

KW - reducibility

KW - iron ore

KW - pellets

KW - image processing

KW - Eisenträger

KW - Reduzierbarkeit

KW - Eisenerze

KW - Pellets

KW - Bildverarbeitung

U2 - 10.34901/mul.pub.2024.035

DO - 10.34901/mul.pub.2024.035

M3 - Doctoral Thesis

ER -