DocumentCode
3254236
Title
The tracking of changes in chemical processes using computer vision and self-organizing maps
Author
Van Deventer, Jannie S J ; Aldrich, Chris ; Moolman, Derick W.
Author_Institution
Dept. of Chem. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume
6
fYear
1995
fDate
Nov/Dec 1995
Firstpage
3068
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
Keywords
chemical industry; computer vision; computerised monitoring; feature extraction; image texture; real-time systems; self-organising feature maps; Kohonen layer; change detection; chemical processes; computer vision; diagnostic leaching; feature extraction; froth flotation; monitoring; online systems; self-organizing maps; textural analysis; Africa; Chemical engineering; Chemical processes; Computer vision; Leaching; Minerals; Mining industry; Ores; Self organizing feature maps; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487273
Filename
487273
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