The Use of a Colour Parameter in a Machine Vision System, SmartFroth, to Evaluate Copper Flotation Performance at Rio TintoÆs Kennecott Utah Copper Concentrator

Traditionally, operators on mineral flotation plants have relied on visual inspection of the froth surface when making adjustments to process set-points. Machine vision systems are being developed to relate froth surface descriptors, which can be consistently measured in real time, to flotation performance. By investigating the impact of various selected operating variables on both froth surface characteristics and metallurgical performance it is possible to develop a management strategy for the control and optimisation of the process. This paper presents the results of testwork conducted at Kennecott copper mine which investigates the relationship between the froth colour and the concentrate grade and discusses the factors which affect the froth colour. This work shows that the main factors that influence the froth colour in this system are molybdenum, copper and iron concentrate grade, pulp and concentrate per cent solids and pulp iron grade.It goes on to develop models to predict the concentrate grade based on colour information and velocity and stability information. It also shows that the most accurate prediction is made with combined colour and stability information.