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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Author(s)
Eugene Donskoi1, Andrei Poliakov2, Keith Vining3 and Sarath Hapugoda4
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DOI:10.17265/1934-8975/2017.01.003
Affiliation(s)
1. Project Leader, Mineral Processing Modelling, CSIRO Mineral Resources, PO Box 883, Kenmore QLD 4069, Australia
2. Senior Experimental Scientist, CSIRO Mineral Resources, PO Box 883, Kenmore QLD 4069, Australia
3. Group Leader – Carbon Steel Futures, CSIRO Mineral Resources, PO Box 883, Kenmore QLD 4069, Australia
4. Process Mineralogist, CSIRO Mineral Resources, PO Box 883, Kenmore QLD 4069, Australia
ABSTRACT
OIA (optical image
analysis) has traditionally been used for reliable identification of different iron
oxides and oxyhydroxides in iron ore. The automated CSIRO OIA system Mineral 4/Recognition 4 was created for rapid
mineral and textural characterisation of iron ore providing identification of different minerals and different
morphologies. The technique has further been applied to processed iron ore products
such as iron ore sinter to determine key parameters such as porosity, different
morphologies of hematite (primary and secondary), and different morphologies of
SFCA (silicon ferrite of calcium and
aluminium). Application of textural identification has recently been extended to coke characterisation where the software gives
comprehensive characterisation of porosity, IMDC (inert material derived components),
RMDC (reactive material derived components)
and the boundaries between IMDC and RMDC. The software also has many unique features needed for iron ore research including characterisation of large
objects like pellets and ore lumps; automated gangue (including quartz) identification; automated particle separation; multiple
image set processing and on-line measurements. All these features make the Mineral 4/Recognition 4 OIA system a unique,
reliable, industry/research focused tool for ore, sinter, pellet and coke characterisation.
KEYWORDS
Image analysis, automated, characterisation, iron ore, sinter, coke.
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