Abstract
ABSTRACTThe present article describes an attempt made to study the possibility of beneficiating low-grade iron ore fines of Barbil Area of Orissa state, India, using multi-gravity separator (MGS) after grinding the −10 mm fines to < 75 micron size and prepare a pellet feed of 65% Fe content. For the performance analysis, an artificial neural network (ANN) mathematical modeling approach was attempted. A three-layer feedforward neural network with a backpropagation method has been adopted, considering the three significant parameters of MGS, mainly drum inclination, drum speed, and shake amplitude, were varied and the results were evaluated for grade, recovery, and separation efficiency. The results of beneficiation studies showed that good recovery of hematite is possible with simultaneous increase in Fe(T) grade from 50.74% to 65.26% with 71.25% recovery. The predicted value obtained by ANN shows good agreement with the experimental values.
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