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ArtistShot sku_373107_140 sku_373107_140 sku_373107_140 Janse van Vuuren, Magrieta Jeanette (2011-03)
ENGLISH ABSTRACT: Hydrocyclones are separation devices that are widely used throughout the chemical engineering and mineral processing industries. Although simple in design, the intricate flow structure of the device complicates control. As an alternative to conventional empirical and theoretical modelling, process state monitoring methods have recently been employed as a means to control hydrocyclones. The purpose of process state monitoring methods is to distinguish between the desired operating state with favourable separation, the transition state, and the troublesome operating state of dense flow separation.
In comparison to previously employed monitoring techniques, image analysis of the underflow is regarded as a promising approach. Preliminary studies have indicated that the technique complies with hydrocyclone monitoring requirements: sensitivity, non-invasiveness, sampling times less than one second, robustness and low cost. The primary objective of this study was therefore defined as investigating the feasibility of image analysis of hydrocyclone underflow as a monitoring technique.
Data collection entailed the recording of hydrocyclone underflow for different operating states. Six case studies were performed in total: Gold, Ilmenite, Platreef, Merensky 1, Merensky 2 and Merensky 3 (with the case study names indicating the different ore types used). An image analysis technique, consisting of feature extraction through motion detection, as well as various noise reduction methods, was consequently developed and applied to the video data. Classification of the various operating states was attempted by performing modelling by one-class support vector machines (SVM).
Results indicated that the developed image analysis technique effectively addresses background noise, random noise and system vibration through image enhancement and a motion threshold. Extremely low contrast differences and foreground noise did, however, prove problematic in Ilmenite and Merensky 1 case studies respectively. For the remaining case studies, it was found that the various operating states were identified with high accuracy through one-class SVM classification. This is particularly true for the identification of the troublesome dense flow separation for which extremely low missing alarm rates were obtained (0 % in most cases). In terms of practicality, the technique proved to be sensitive, non-intrusive and economical. The sampling time of 30 frames per second and estimated processing to video time ratio of 1:1, is furthermore satisfactory. Ultimately, the results indicate that the image analysis of hydrocyclone underflow is a viable monitoring technique.
The robustness of the technique might further be improved by use of backlighting and an air-knife. It is also recommended that future work should focus on testing the monitoring technique on an industrial hydrocyclone setup.
AFRIKAANSE OPSOMMING: Hidrosiklone is skeidingsapparate wat algemeen gebruik word in chemiese ingenieurswese en mineraalprosesserings industrieë. Alhoewel die apparaat ‘n eenvoudige ontwerp het, bemoeilik die komplekse interne vloeistruktuur die beheer daarvan. Prosestoestandmoniteringsmetodes is vir hidrosikloonbeheer toegepas as alternatief vir konvensionele empiriese en teoretiese modellering. Die doel van prosestoestandmoniteringsmetodes is om te onderskei tussen die gewenste bedryfstoestand met gunstige skeiding, die oorgangstoestand, en die moeilike bedryfstoestand van digtevloeiskeiding.
In vergelyking met vorige toegepaste moniteringstegnieke, word beeldverwerking van die ondervloei beskou as ‘n belowende tegniek. Voorlopige studies het aangedui dat die tegniek voldoen aan die hidrosikloonmoniteringvereistes: sensitiwiteit, nie-indringendheid, monsternemingstydperke laer as een sekonde, robuustheid en lae koste. Die primêre doelwit van hierdie studie is daarom gedefineer as die ondersoek van die doenlikheid van beeldverwerking van hidrosikloon ondervloei as ‘n moniteringstegniek.
Die data versameling het die afneem van hidrosikloon ondervloei vir verskillende bedryfstoestande behels. Ses gevallestudies is in totaal uitgevoer: Goud, Ilmeniet, Platreef, Merensky 1, Merensky 2 en Merensky 3 (die gevallestudie name dui die verskillende erts tipes wat gebruik is aan). ‘n Beeldverwerkingstegniek, wat bestaan uit kenmerkekstraksie deur bewegingsopsporing, asook verskeie geruisverlagingsmetodes, is gevolglik ontwikkel en toegepas op die video data. Klassifikasie van die verskeie bedryfstoestande is beproef deur modellering met enkelklassteunvektormasjiene.
Resultate het aangedui dat die ontwikkelde beeldverwerkingstegniek agtergrond geruis, onreëlmatige geruis en sisteem vibrasie suksesvol aanspreek deur beeldversterking en ‘n bewegingslimiet. Beduidende lae kontrasverskille en voorgrond geruis blyk wel problematies in die Ilmeniet en Merensky 1 gevallestudies onderskeidelik. Vir die orige gevallestudies is gevind dat die verskillinde bedryfstoestande met hoë akkuraatheid geïdentifiseer is deur enkelklassteunvektormasjiene klassifisering. Dit is veral waar vir die identifisering van die moeilike digtevloeiskeiding waarvoor beduidende lae vermiste-alarmmaatstawwe behaal is (0 % in die meeste gevalle). Aangaande die praktiese aspekte, blyk die tegniek sensitief, nie-indringend en ekonomies. Die monsternemingstydperk van 30 raampies per sekonde en die beraamde prosesserings- tot videotyd verhouding van 1:1, is ook voldoende. Ten slotte dui die resultate daarop dat die beeldverwerking van hidrosikloon ondervloei ‘n uitvoerbare moniteringstegniek is.
Die robuustheid van die tegniek sou verder verbeter kon word deur gebruik te maak van agtergrondverligting en ‘n lugspuit. Dit word ook aanbeveel dat toekomstige werk op die toetsing van die moniteringstegniek op ‘n industriële hidrosikloon toestel moet fokus.
Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/6619
This item appears in the following collections: Masters Degrees (Process Engineering)175