IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-030-62472-9_2.html
   My bibliography  Save this book chapter

Statistical Approach to Model Track Dynamics Towards the Monitoring of Railway Turnouts

In: Intelligent Quality Assessment of Railway Switches and Crossings

Author

Listed:
  • Pegah Barkhordari

    (Technical University of Denmark)

  • Roberto Galeazzi

    (Technical University of Denmark)

Abstract

This paper proposes a method for the automatic generation of statistical models that describe the track stiffness in terms of the first and second track resonance frequencies, which are associated with the dynamic behavior of the ballast and rail pad layers. The method combines the empirical mode decomposition and a subspace identification method to estimate the track resonance frequencies from track vibrations induced during train passage. The generalized extreme value distribution is found to be a robust descriptor of the estimates of the first and second track resonance frequencies across time and space. The method is demonstrated on track acceleration data collected over a period of two years at fixed locations along a turnout for three different types of trains, and models are built for the switch panel, the closure/crossing panel and a transition zone. Further, it is shown that the degradation of track components is captured through the recursive generation of such statistical models, which can then become the basis for the development of condition monitoring systems.

Suggested Citation

  • Pegah Barkhordari & Roberto Galeazzi, 2021. "Statistical Approach to Model Track Dynamics Towards the Monitoring of Railway 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 19-41, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-62472-9_2
    DOI: 10.1007/978-3-030-62472-9_2
    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_2. 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.