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    Monitoring of Mineral Processing Operations based on Multivariate Similarity Indices

    Access Status
    Fulltext not available
    Authors
    Auret, L.
    Aldrich, Chris
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Auret, L. and Aldrich, C. 2011. Monitoring of Mineral Processing Operations based on Multivariate Similarity Indices, in L Auret, C Aldrich (ed), The 18th World Congress The International Federation of Automatic Control, Aug 28 2011, pp. 9923-9928. Milano, Italy: Elsevier.
    Source Title
    Proceedings of the 18th World Congress The International Federation of Automatic Control
    Source Conference
    The 18th World Congress The International Federation of Automatic Control
    URI
    http://hdl.handle.net/20.500.11937/35838
    Collection
    • Curtin Research Publications
    Abstract

    Multivariate process monitoring through covariance control charts considers changes in the relationships among process variables, but is limited by linearity assumptions. In this paper two nonlinear indicators of multivariate structure are considered, viz. mutual information and random forest proximity measures. Similarity matrices are constructed from data encapsulated by sliding windows of different sizes across the time series data associated with process operations. Diagnostic metrics reflect the differences between stationary base windows representative of normal operating conditions and test windows containing new process data. A case study in mineral processing shows that better results can be obtained with these nonlinear methods.

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