Prediction of mineral liberation characteristics of comminuted particles of high grade ores

In mineral processing, the liberation of valuable mineral is of key importance in achieving high recoveries from downstream separation processes such as froth flotation and gravity concentration. To quantify mineral liberation, information on ore texture of the parent rock as well as properties of c...

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Main Authors: Zhang, Jian, Subasinghe, Nimal
Format: Journal Article
Published: Elsevier 2013
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/47965
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author Zhang, Jian
Subasinghe, Nimal
author_facet Zhang, Jian
Subasinghe, Nimal
author_sort Zhang, Jian
building Curtin Institutional Repository
collection Online Access
description In mineral processing, the liberation of valuable mineral is of key importance in achieving high recoveries from downstream separation processes such as froth flotation and gravity concentration. To quantify mineral liberation, information on ore texture of the parent rock as well as properties of comminuted particles is essential. These properties have been quantified by statistical measures such as the proximity function and covariance function, which were extracted from SEM images of parent rock and particle polished sections, using convenient and efficient image analysis techniques based on Labview™ software. To quantify fully liberated particles, a phase specific line segment function has been introduced and evaluated by placing random line segments on the image. It was also found that the ore texture assumptions made by Barbery are not valid for the high grade sulphide ore tested and the general applicability of these assumptions is therefore questionable. Using the measured information above, predictive liberation models to quantify volumetric grade distribution of particles in 1D and 3D have been developed based on Barbery’s work. Results show that the grade distributions of composite particles predicted from the proposed1D model is closest to measured data than those of Barbery’s 1D model. The predictions using the proposed3D model are similar to those predicted from Barbery’s model and are considered more realistic as the model does not rely on assumed ore texture but on measurements made on the parent rock and particle sections.
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spelling curtin-20.500.11937-479652017-09-13T15:57:40Z Prediction of mineral liberation characteristics of comminuted particles of high grade ores Zhang, Jian Subasinghe, Nimal Mineral liberation prediction In mineral processing, the liberation of valuable mineral is of key importance in achieving high recoveries from downstream separation processes such as froth flotation and gravity concentration. To quantify mineral liberation, information on ore texture of the parent rock as well as properties of comminuted particles is essential. These properties have been quantified by statistical measures such as the proximity function and covariance function, which were extracted from SEM images of parent rock and particle polished sections, using convenient and efficient image analysis techniques based on Labview™ software. To quantify fully liberated particles, a phase specific line segment function has been introduced and evaluated by placing random line segments on the image. It was also found that the ore texture assumptions made by Barbery are not valid for the high grade sulphide ore tested and the general applicability of these assumptions is therefore questionable. Using the measured information above, predictive liberation models to quantify volumetric grade distribution of particles in 1D and 3D have been developed based on Barbery’s work. Results show that the grade distributions of composite particles predicted from the proposed1D model is closest to measured data than those of Barbery’s 1D model. The predictions using the proposed3D model are similar to those predicted from Barbery’s model and are considered more realistic as the model does not rely on assumed ore texture but on measurements made on the parent rock and particle sections. 2013 Journal Article http://hdl.handle.net/20.500.11937/47965 10.1016/j.mineng.2013.05.005 Elsevier restricted
spellingShingle Mineral liberation
prediction
Zhang, Jian
Subasinghe, Nimal
Prediction of mineral liberation characteristics of comminuted particles of high grade ores
title Prediction of mineral liberation characteristics of comminuted particles of high grade ores
title_full Prediction of mineral liberation characteristics of comminuted particles of high grade ores
title_fullStr Prediction of mineral liberation characteristics of comminuted particles of high grade ores
title_full_unstemmed Prediction of mineral liberation characteristics of comminuted particles of high grade ores
title_short Prediction of mineral liberation characteristics of comminuted particles of high grade ores
title_sort prediction of mineral liberation characteristics of comminuted particles of high grade ores
topic Mineral liberation
prediction
url http://hdl.handle.net/20.500.11937/47965