2019
DOI: 10.1080/25726641.2019.1699359
|View full text |Cite
|
Sign up to set email alerts
|

Microwave infrared ore sorting of screen rejected rocks based on their content of iron and copper sulfide in Sarcheshmeh copper complex, Iran, Kerman

Abstract: Feasibility study using microwave-IRT sorting technique for preconcentration of oversize screen rejected ores in primary mills of concentration units of Sarcheshmeh copper complex was investigated in this study. Three size fraction samples were exposed to microwave radiation followed by thermography imaging. Temperature rise of samples were compared with their element grades as provided by XRF analysis. Sortability performance index was computed for each size fraction and cumulative mass copper recovery was pl… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2020
2020
2020
2020

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 6 publications
0
1
0
Order By: Relevance
“…The detection unit is key section to guarantee the separation accuracy. The advanced sensors in mineral engineering within the past decades have achieved great developments, including machine vision [1][2][3][4], X-ray transmission (XRT) [5,6], laser-induced breakdown spectroscopy (LIBS) [7], X-ray fluorescence (XRF) [8,9], radiometric sorting [10], hyperspectral analysis [11,12] and near-infrared (NIR) sensing [13,14]. Each detection sensor has its own merit in ore sorting, but machine vision is the one with higher cost performance and good identification accuracy at present stage, which enable it to have a wilder application market.…”
Section: Introductionmentioning
confidence: 99%
“…The detection unit is key section to guarantee the separation accuracy. The advanced sensors in mineral engineering within the past decades have achieved great developments, including machine vision [1][2][3][4], X-ray transmission (XRT) [5,6], laser-induced breakdown spectroscopy (LIBS) [7], X-ray fluorescence (XRF) [8,9], radiometric sorting [10], hyperspectral analysis [11,12] and near-infrared (NIR) sensing [13,14]. Each detection sensor has its own merit in ore sorting, but machine vision is the one with higher cost performance and good identification accuracy at present stage, which enable it to have a wilder application market.…”
Section: Introductionmentioning
confidence: 99%