On-Line Bias And Froth Depth Measurement In Flotation Columns : A Promising Tool For Automatic Control And Real-Time Optimization

The metallurgical performance of column flotation is determined by the concentrate grade and recovery. Although the former can be continuously measured using an on-stream analyzer, the latter must be estimated by a material balance calculation based on seldom verified steady-state assumptions. Consequently, the automatic control and optimization of flotation columns should be performed using secondary variables having a strong influence on the metallurgical performance, such as froth depth, gas hold-up or bubble surface area flux and bias. The aim of this paper is to present a method to get froth depth and bias measurements using virtual sensors. Fractional factorial experiment design for the neural network calibration of the bias sensor, pilot plant results, and eventual industrial applications – including the possibility of achieving effective real-time optimization from bias and froth depth measurements – will also be discussed.