Monitoring of Flotation Systems by Use of Multivariate Froth Image Analysis

Froth image analysis has been considered widely in the identification of operational regimes flotation circuits, characterisation froths terms bubble size distributions, froth stability and local velocity patterns, or as a basis for development inferential online sensors chemical species froth. Relatively few studies have unsupervised process monitoring applications. In this study, it is shown that can be combined with traditional multivariate statistical methods reliable industrial platinum metal group plants. This accomplished well-established analysis, such Haralick feature set derived from grey level co-occurrence matrices binary patterns were investigation.