Resumen

KARIMI, M.; DEHGHANI, A.; NEZAMALHOSSEINI, A.  y  TALEBI, Sh.. Prediction of hydrocyclone performance using artificial neural networks. J. S. Afr. Inst. Min. Metall. [online]. 2010, vol.110, n.5, pp.207-212. ISSN 2411-9717.

Artificial neural networks (ANNs) have found their applications in the modelling of unit operations of mineral processing plants. In this research, laboratory-scale tests were conducted, using a three-inch diameter Mozley hydrocyclone. Main parameters included pressure drop at inlet, solid per cent, vortex and apex diameter were adjusted. The corrected cut size (d_50c) and the flow rates of underflow and overflow were determined. Multi layers perceptron (MLP) feed forward network architectures were designed to predict the responses. The results showed a good correlation between experimental and network output, for corrected cut size and flow rates.

Palabras clave : hydrocyclone; artificial neural network; corrected cut size; flow rates.

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