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ArticleName Development of ore types processing classification principles on the basis of flotation process parameters control and neural network modeling
ArticleAuthor Mashevsky G. N., Petrov A. V., Romanenko S. A., Sufyanov F. S.

Outotec (St. Petersburg):

Mashevsky G. N., Chief Process Adviser,

Petrov A. V., Head of Department,

Romanenko S. A., Leading Process Engineer,


Russkaya Mednaya Kompaniya (Russia):

Sufyanov F. S., Deputy General Director,


The article considers a new approach to the development of a method and a system for monitoring of processed ore blend technological type in floatation concentration. The technical solutions of this problem, that have been developed earlier, are analyzed. By way of example of the named after the 50th October anniversary deposit copper-pyrite ores processing, a necessity to form new information database, that will include the Courier express analysis subsystem measurements results, as well as FrothMaster video system results that permit to control froth product flow rate into concentrate launder, bubbles size in froth layer, and its color characteristics, is substantiated. In order to solve the task of processed ore technological type monitoring, the method of Fourier analysis of harmonic oscillation is applied. Main factors that determine technological properties of processed ores are revealed: pyritiferous factor, impregnation factor, oxidation factor and flotoactive silicates' presence factor. A new methodology of mathematical treatment of measurement results is proposed, that includes Kohonen topologic map generation and its interpretation by the factor analysis method, projection of identified neurons on Fi-Fj main components plane and applying to them measured parameters physical vectors' values and output function isolines. The developed model of processed ores technological types classification shows a high variability of run-of-mine feed material, delivered to concentrating plant, and a necessity to develop flotation process computerized control algorithms.

keywords Ores technological types classification, flotation, neural network modeling, flotation process control, real-time monitoring, copper-pyrite ores

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12. Mashevskiy G. N., Petrov A. V., Lamberg P., Lura M. Obogashchenie Rud, 2009, No. 6, pp. 22–27.

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