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    On-line monitoring of hydrocyclones by use of image analysis

    Access Status
    Fulltext not available
    Authors
    van Vuuren, J.
    Aldrich, Chris
    Bezuidenhoudt, C.
    De Jager, C.
    Date
    2010
    Type
    Conference Paper
    
    Metadata
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    Citation
    van Vuuren, J. and Aldrich, C. and Bezuidenhoudt, C. and De Jager, C. 2010. On-line monitoring of hydrocyclones by use of image analysis, in Janse van Vuuren M J, Aldrich C, Auret L, Bezuidenhudt C, De Jager C (ed), The 13th Symposium on Automation in Mining, Mineral and Metal Processing, Aug 2 2010, pp. 87-91. Cape Town, South Africa: Elsevier.
    Source Title
    Proceedings of the 13th Symposium on Automation in Mining, Mineral and Metal Processing
    Source Conference
    The 13th Symposium on Automation in Mining, Mineral and Metal Processing
    URI
    http://hdl.handle.net/20.500.11937/10110
    Collection
    • Curtin Research Publications
    Abstract

    Hydrocyclones are widely applied in both chemical and mineral processing industries. Despiteits simple design, the flow behaviour that governs separation within the device is quite complex andtherefore difficult to control. Overall process efficiency, together with economics, promotes thedevelopment of an effective monitoring technique. In the past, numerous techniques have been tried, with varied success, but none have found broad adoption yet. The reasons for this are that the techniques lack robustness, while others are intrusive to the process or completely uneconomical.Previous work has indicated that there exists a relationship between the underflow and the operating state of a hydrocyclone, which could be exploited for monitoring purposes. In view of this, the use of image analysis of the underflow is evaluated as an on-line monitoring technique.Underflow widths are determined from video recordings of two different data sets: gold ore and PGM(Platinum Group Metals) ore. Time series analysis of the data indicates identifiable clusters which relateto normal operating conditions as well as troublesome states like roping and blocking. Groups ofscattered clusters further correspond to the oscillatory behaviour experienced during the transition fromnormal to roping (or blocking). The predictive potential of the gold ore data set was also investigated, and suggests that the technique can be used to forecast the onset of such troublesome states.

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