The tracking of changes in chemical processes using computer vision and self-organizing maps

Abstract

Frequently, chemical processes involve so many independent and dependent variables that the plant operator finds it difficult to visualise or even observe a change in process conditions. In froth flotation the operator is supposed to visually observe process changes from the appearance of the froth, which is an unreasonable demand under industrial conditions. An online computer vision system based on a textural analysis of the froth phase has been developed in South Africa and has been in operation on an industrial flotation plant since the end of 1994. This system determines textural parameters online, and tracks the changes in process conditions via a self-organizing map (SOM) incorporating a Kohonen layer. This monitoring system warns the operator about fluctuations in reagent addition, and gives an idea of the type of froth encountered. In a further example, changes in the mineralogical characteristics of gold ores are represented on an SOM map, based on the diagnostic leaching behaviour of such ores.