Acoustic monitoring of DC placma arcs

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dc.contributor.advisorEksteen, J. J.en_ZA
dc.contributor.advisorNiesler, T. R.en_ZA
dc.contributor.advisorAldrich, C.en_ZA
dc.contributor.authorBurchell, John Jamesen_ZA
dc.contributor.otherStellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
dc.date.accessioned2012-08-27T11:31:44Z
dc.date.available2012-08-27T11:31:44Z
dc.date.issued2008-03
dc.descriptionThesis (MScIng) -- University of Stellenbosch, 2008.
dc.description.abstractENGLISH ABSTRACT: The arc, generated between the cathode and slag in a dc electric arc furnace (EAF), constitutes the principal source of thermal energy in the furnace. Steady state melting conditions rely on efficient control of the arc's power. This is achieved by keeping the arc's length constant, which is currently not directly measured in the industry, but relies on an external voltage measurement. This voltage measurement is often subject to inaccuracies since it may be influenced by voltage fluctuations that are not necessarily related to the arc itself, such as the variable impedance of the molten bath and the degradation of the graphite electrode. This study investigated whether or not it is possible to develop a sensor for the detection of arc length from the sound that is generated by the arc during operation. Acoustic signals were recorded at different arc lengths using a 60 kW dc electric arc furnace and 600 g of mild steel as melt. Using a filterbank kernel (FB) based Fisher discriminant analysis (KFD) method, nonlinear features were extracted from these signals. The features were then used to train and test a k nearest neighbour (kNN) classifier. Two methods were used to evaluate the performance of the kNN classifier. In the first, both test and train features were extracted from acoustic signals recorded during the same experimental run and used a ten fold bootstrap method for integrity. The second method tested the generalized performance of the classifier. This involved training the kNN classifier with features extracted from the acoustic recordings made during a single or multiple experimental runs and then testing it with features drawn from the remaining experimental runs. The results from this study shows that there exists a relationship between arc length and arc acoustic which can be exploited to develop a sensor for the detection of arc length from arc acoustics in the de EAF. Indications are that the performance of such a sensor would rely strongly on how statistically representative the acoustic data are, used to develop the sensor, to the acoustics generated by industrial dc EAFs during operation.
dc.description.abstractAFRIKAANSE OPSOMMING: Die boog tussen die katode en slak in 'n gelykstroom boogoond, is die hoofbron van termiese energie in die oond. Bestendige smelttoestande in die oond hang sterk af van die effektiewe beheer van die lengte van die boog wat tans nie direk gemeet word nie. Die booglengte is op die oomblik afhanklik van 'n eksterne spanningsmeting en is dus dikwels onakkuraat deurdat die meting be"invloed word deur wisselende spanningsvlakke wat nie noodwendig iets te doen het met 'n verandering in booglengte nie (soos die wisselvaligheid van die bad se impedansie en die konstante verwering van die katode tydens oondwerking). Die studie het die lewensvatbaarheid van 'n meetinstrument ondersoek wat die booglengte bepaal het vanaf die akoestiek van die boog in 'n gelykstroom boogoond. Akoestiese seine is opgeneem by verskillende booglengtes deur gebruik te maak van 'n 60 kW gelykstroom boogoond met 600 g weekstaal as gesmelte lading. 'n Filterbank (FB) - kerngebaseerde Fisher diskriminant analise (KFD) is gebruik om eienskappe of komponente uit die akoestiese seine uit te haal. Hierdie komponente is toe gebruik om 'n k naaste buurman (kNN) klassifiseerder mee te leer. Iv Twee metodes is gebruik om die prestasie van die kNN klassifiseerder te ontleed. In die eerste metode is die komponente waarmee die klassifiseerder geleer en getoets is uit 'n enkele eksperiment se data geneem. In die tweede metode was die leerkomponente uit verskillende eksperimente geneem as die toetskomponente om sodoende die algemene prestasie van die klassifiseerder te toets. Die resultate van die studie toon dat daar 'n verhouding bestaan tussen die lengte van 'n boog en die klank wat die boog opwek, asook dat 'n meetinstrument ontwikkel kan word wat die verhouding kan gebruik om die lengte van die boog te meet. Die studie dui aan dat die prestasie van so 'n meetinstument sterk sal afhang van hoe statisties verteenwoordigend die data is waarmee die meetinstrument geleer sal word t.o.v. die data wat dit sal teekom in die industrie.
dc.format.extent99 leaves : ill.
dc.identifier.urihttp://hdl.handle.net/10019.1/49406
dc.language.isoen_ZA
dc.publisherStellenbosch : Stellenbosch University
dc.rights.holderStellenbosch University
dc.subjectElectric arcen_ZA
dc.subjectFurnacesen_ZA
dc.subjectSound -- Measurementen_ZA
dc.subjectAcoustical engineeringen_ZA
dc.subjectDissertations -- Process engineeringen_ZA
dc.titleAcoustic monitoring of DC placma arcsen_ZA
dc.typeThesis
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