IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v43y2012i10p1826-1841.html
   My bibliography  Save this article

Fault detection and isolation in manufacturing systems with an identified discrete event model

Author

Listed:
  • Matthias Roth
  • Stefan Schneider
  • Jean-Jacques Lesage
  • Lothar Litz

Abstract

In this article a generic method for fault detection and isolation (FDI) in manufacturing systems considered as discrete event systems (DES) is presented. The method uses an identified model of the closed-loop of plant and controller built on the basis of observed fault-free system behaviour. An identification algorithm known from literature is used to determine the fault detection model in form of a non-deterministic automaton. New results of how to parameterise this algorithm are reported. To assess the fault detection capability of an identified automaton, probabilistic measures are proposed. For fault isolation, the concept of residuals adapted for DES is used by defining appropriate set operations representing generic fault symptoms. The method is applied to a case study system.

Suggested Citation

  • Matthias Roth & Stefan Schneider & Jean-Jacques Lesage & Lothar Litz, 2012. "Fault detection and isolation in manufacturing systems with an identified discrete event model," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(10), pages 1826-1841.
    • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:10:p:1826-1841
    DOI: 10.1080/00207721.2011.649369
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2011.649369
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2011.649369?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Olfa Fakhfakh & Armand Toguyeni & Ouajdi Korbaa, 2018. "On-line fault diagnosis of FMS based on flows analysis," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1891-1904, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tsysxx:v:43:y:2012:i:10:p:1826-1841. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.