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    Acoustic Monitoring of Plasma Arcs in Direct Current Electric Arc Furnaces

    Access Status
    Fulltext not available
    Authors
    Burchell, J.
    Aldrich, Chris
    Eksteen, Jacques
    Niesler, T.
    Jemwa, G.
    Date
    2009
    Type
    Journal Article
    
    Metadata
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    Citation
    Burchell, J. and Aldrich, C. and Eksteen, J. and Niesler, T. and Jemwa, G. 2009. Acoustic Monitoring of Plasma Arcs in Direct Current Electric Arc Furnaces. Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science. 40: pp. 886-891.
    Source Title
    Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
    DOI
    10.1007/s11663-009-9287-2
    ISSN
    1073-5615
    URI
    http://hdl.handle.net/20.500.11937/29168
    Collection
    • Curtin Research Publications
    Abstract

    In this article, the extraction of features from acoustic signals generated by a 60-kW direct current electric arc furnace and the use of these features to infer the arc length of the plasma jets in the furnace were considered. A sensor capable of such measurements would be more robust to the unobservable fluctuations of the arc length and would, in principle, allow better control of smelting operations. The collected data comprised sets of five separate 10-second recordings of the acoustic signal, furnace current, and voltage, each at nominal arc lengths of 5, 15, and 25 mm. In the approach, time-frequency features initially were obtained through filter bank analysis of the signals. Reduction of the dimensionality of these filter bank features was then performed using a nonlinear subspace method called kernel Fisher discriminant analysis.Finally, kernel discriminant features were used to infer the arc length via a nearest neighborclassification model that associated three classes of arc lengths (5, 15, and 25 mm) with theircorresponding features. The results of the small number of experiments suggest that a significantstatistical relationship exists between the length of a plasma arc and its acoustic signal despitepotentially large variations in arc phenomena inside the furnace.

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