The use of machine vision to describe and evaluate froth phase behaviour and performance in mineral flotation systems

Includes synopsis.Includes bibliographical references (leaves 179-190).Within froth flotation, it is widely acknowledged that froth stability affects flotation performance. As a result, it is expected that through the effective management of froth stability, it would be possible to both control and optimise a flotation cell and bank. However, for this to be possible, the relationships between the operating conditions, froth stability behaviour and flotation performance attributes need to be well understood. In addition, froth stability would need to be measured using a robust method suitable for on-line operation. Within the literature, no robust methods are available to measure either the concentration of solids on the froth surface, or froth stability in a manner suitable for on-line operation. Thus, two novel non-intrusive machine vision measurements have been developed in this work to quantify these attributes

Automatic estimation of bubble size distributions in flotation froths by use of a mean shift algorithm and watershed transforms

Flotation is a process used in the mineral industry to concentrate valuable minerals. The efficiency of the process is influenced by among other the bubble size distribution of the flotation froth. In this investigation, we propose a new method for automatic estimation of the bubble size distribution using the mean shift algorithm and watershed transform. The mean shift algorithm is used to find pixel clusters of particular modes of the probability density function of the image data. Pixel clusters of which the modes are above a given threshold are used as markers for the watershed transform. Experimental results show that the proposed method was fast and robust for determining the size distribution of different classes of flotation froth