All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F18%3A39911358" target="_blank" >RIV/00216275:25510/18:39911358 - isvavai.cz</a>

  • Result on the web

    <a href="http://journals.sagepub.com/doi/10.1177/0954409717745201" target="_blank" >http://journals.sagepub.com/doi/10.1177/0954409717745201</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1177/0954409717745201" target="_blank" >10.1177/0954409717745201</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

  • Original language description

    Monitoring the conditions of railway vehicle systems plays an important role in the maintenance of safety and performance of railway vehicles. Rolling radius is one of the properties that should be monitored continuously for the predictive maintenance of a railway vehicle since it changes with time due to wheel wear. In this study, a model-based condition monitoring methodology, which is based on an unscented Kalman filter, is proposed. The model includes the torsional dynamics of an independently rotating tram wheel with a traction motor and a contact model. The rolling radius is estimated by considering the traction effort of the motor and the angular velocity measurements. The proposed methodology is tested on a tram wheel test stand (roller rig), which has a wheel on roller configuration. First, a mathematical model is validated by the measurements taken from the test stand. Second, the unscented Kalman filter is applied as a parameter estimator. The results demonstrate that the proposed scheme is a promising option to be used in the predictive condition monitoring of the wheel profile for traction vehicles.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20104 - Transport engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit

  • ISSN

    0954-4097

  • e-ISSN

  • Volume of the periodical

    232

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    17

  • Pages from-to

    1686-1702

  • UT code for WoS article

    000436065400009

  • EID of the result in the Scopus database

    2-s2.0-85043342621