• DocumentCode
    3532878
  • Title

    Data characterization for automatic selection of valve stiction detection algorithms

  • Author

    Zakharov, A. ; Zattoni, Elena ; Lei Xie ; Pozo, Octavio ; Jamsa-Jounela, Sirkka-Liisa

  • Author_Institution
    Dept. of Biotechnol. & Chem. Technol., Aalto Univ., Aalto, Finland
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    4355
  • Lastpage
    4360
  • Abstract
    This paper proposes a valve stiction detection system which selects applicable valve stiction detection algorithms based on characterization of the data. Additionally, the proposed system computes the final detection decision, weighting, by means of suitably-defined reliability indexes, the individual decisions provided by the selected algorithms. The paper demonstrates the effectiveness of the proposed valve stiction detection system with benchmark industrial data.
  • Keywords
    stiction; valves; data characterization; reliability indexes; valve stiction detection algorithm automatic selection; Correlation; Feature extraction; Histograms; Indexes; Robustness; Valves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760559
  • Filename
    6760559