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Volumn 87, Issue 3-4, 2008, Pages 106-119

Modelling and optimization of hydrocyclone for iron ore fines beneficiation - using optical image analysis and iron ore texture classification

Author keywords

Classification; Hydrocyclone; Image analysis; Iron ore; Modeling; Texture

Indexed keywords

BENEFICIATION; CYCLONE SEPARATORS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; MATHEMATICAL MODELS; PARTICLE SIZE ANALYSIS; TEXTURES;

EID: 43949143491     PISSN: 03017516     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.minpro.2008.02.006     Document Type: Article
Times cited : (43)

References (18)
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    • Automated textural classification of iron ores using 'Recognition' - A specialised software package for studying ores
    • AusIMM, Fremantle
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    • Donskoi, E.1    Clout, J.M.F.2
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    • Prediction of hydrocyclone performance in iron ore beneficiation using virtual modelling
    • AusIMM, Fremantle
    • Donskoi E., Suthers S.P., Clout J.M.F., and Campbell J.J. Prediction of hydrocyclone performance in iron ore beneficiation using virtual modelling. Proceedings, Iron Ore 2005 (2005), AusIMM, Fremantle 321-330
    • (2005) Proceedings, Iron Ore 2005 , pp. 321-330
    • Donskoi, E.1    Suthers, S.P.2    Clout, J.M.F.3    Campbell, J.J.4
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    • Cyclone modelling: a review of present technology
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    • Reid A.F., Gottlieb P., MacDonald K.J., and Miller R.R. In: Parks W.C., Hausen D.H., and Hagni R.D. (Eds). QEM-SEM image analysis of ore minerals: volume fraction, liberation and observational variances. Applied Mineralogy (1985), TMS-AIME, Littleton, Colorado 191-204
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.