The use of machine vision to predict flotation performance

Author:

Morar Sameer H.,Harris Martin C.,Bradshaw Dee J.

Publisher

Elsevier BV

Subject

Mechanical Engineering,Geotechnical Engineering and Engineering Geology,General Chemistry,Control and Systems Engineering

Reference19 articles.

1. Froth imaging, air recovery and bubble loading to describe flotation bank performance;Barbian;International Journal of Mineral Processing,2007

2. Characterisation of the flotation froth structure and color by machine vision (ChaCo);Bonifazi;Developments in Mineral Processing,2000

3. Prediction of complex sulfide flotation performances by a combined 3d fractal and colour analysis of the froths;Bonifazi;Minerals Engineering,2000

4. Forbes, G., 2007. Texture and bubble size measurements for modelling concentrate grade in flotation froth systems. Ph.D. thesis, University of Cape Town.

5. Gorain, B., 2005. Optimisation of floation circuits with large flotation cells. In: Proceedings of Centenary of Flotation Symposium. AUSIMM, Brisbane, Australia, pp. 843–851.

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