Estimation of Bias and Entrainment in Flotation Columns Using Conductivity Measurements

Abstract The cleaning action of the wash water in the flotation column froth is enhanced by a net downward flow of water, called the bias . The evaluation of this variable in industrial columns, through a water balance over the lower part of the collection zone, presents some serious deficiencies since it requires extensive instrumentation and the calculated value is usually unreliable, particularly in transient operation which renders the implementation of automatic control very difficult. In this work, the relationship between the bias and the conductivity profile across the interface has been modelled using a neural network algorithm, a non-linear model whose performance in interpreting complicated patterns has been widely demonstrated. A 5.8 cm diameter column equipped with a series of conductivity electrodes in its uppermost section was used in an initial series of experiments designed to train the neural network with two-phase data. The excellent results obtained led to new series of experiments in both the 5.8 cm column with a three-phase (slurry-air) system and in a 30.48 cm diameter column with a two-phase system.