首页 | 本学科首页   官方微博 | 高级检索  
     


Prediction of mineral liberation characteristics of comminuted particles of high grade ores
Affiliation:1. University of Liège, GeMMe, Laboratory of Minerals Engineering and Recycling, Sart-Tilman Campus-B52, 4000 Liège, Belgium;2. Dundee Precious Metals Chelopech, 2087 Village of Chelopech, Bulgaria;1. School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China;2. College of Zijin Mining, Fuzhou University, Fuzhou 350116, China;1. Université Laval, Département de génie des mines, de la métallurgie et des matériaux, LOOP, Centre E4m, Pavillon Adrien-Pouliot, 1065 avenue de la médecine, Québec, Québec G1V 0A6, Canada;2. Université Laval, Département de génie chimique, LOOP, Centre E4m, Pavillon Adrien-Pouliot, 1065 avenue de la médecine, Québec, Québec G1V 0A6, Canada;3. Université Laval, Département de génie électrique et de génie informatique, LOOP, Centre E4m Pavillon Adrien-Pouliot, 1065 avenue de la médecine, Québec, Québec G1V 0A6, Canada
Abstract: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 proposed 1D model is closest to measured data than those of Barbery’s 1D model. The predictions using the proposed 3D 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.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号