IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-030-62472-9_8.html
   My bibliography  Save this book chapter

CoMPAcT-Data Based Condition Monitoring and Prediction Analytics for Turnouts

In: Intelligent Quality Assessment of Railway Switches and Crossings

Author

Listed:
  • Michael Fellinger

    (Graz University of Technology, Institute of Railway Engineering and Transport Economy)

  • Petra A. Wilfling

    (Graz University of Technology, Institute of Railway Engineering and Transport Economy)

  • Stefan Marschnig

    (Graz University of Technology, Institute of Railway Engineering and Transport Economy)

Abstract

Unloaded measurements of turnouts guarantee the adherence of safety critical geometric limits but do not allow behaviour forecasting. To push maintenance strategies for turnouts up to a preventive level, performance prediction is required. Therefore, it was necessary to identify data, being suitable to describe the condition of a turnout, based on loaded measurements. The measurement data from the standard track recording car EM250 of the Austrian Federal Railways are best suited for this purpose. Due to the limited length and the varying stiffness of a turnout, the measurement data must be positioned much more precisely. In this context, it was necessary to develop a methodology for a defined and comprehensible measurement data positioning. This method enables the positioning of all available measurement signals with a maximum deviation of one measurement point (25 cm) and ensures the synchronicity between each single measurement signal. Applying this positioning algorithm to the measurement data, it is possible to describe the behaviour of turnouts quite well. Different methods for describing the necessary tamping actions as well as the actual condition of the ballast are presented. These methodologies enable describing the present condition of turnout components and deliver statistical values, required for prediction algorithms.

Suggested Citation

  • Michael Fellinger & Petra A. Wilfling & Stefan Marschnig, 2021. "CoMPAcT-Data Based Condition Monitoring and Prediction Analytics for Turnouts," Springer Series in Reliability Engineering, in: Roberto Galeazzi & Hilmar Kjartansson Danielsen & Bjarne Kjær Ersbøll & Dorte Juul Jensen & Ilmar Sa (ed.), Intelligent Quality Assessment of Railway Switches and Crossings, pages 129-148, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-62472-9_8
    DOI: 10.1007/978-3-030-62472-9_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:ssrchp:978-3-030-62472-9_8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.