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Monitoring of a High-Speed Train Bogie Using the EMD Technique

  • A. BustosEmail author
  • H. Rubio
  • C. Castejón
  • J. C. García-Prada
Conference paper
Part of the Applied Condition Monitoring book series (ACM, volume 15)

Abstract

A proper maintenance of train basic systems is a key aspect in the comfort and safety of that train, especially in high-speed rail. One of the most critical systems in the operation of a train is the bogie, a very complex mechanical system made up of several elements that interact between them. Bogie vibrations are the result of multiple mechanical connections, which are generated by the different components involved in the dynamic or structural behavior of the bogie. The axle box is the element in which the sensors of the monitoring system are located and whose information is the essence of the predictive maintenance process of the train. In this work, it is studied the vibratory behavior of the railway running gear system of a high speed train, in commercial service, after a maintenance operation. Vibration signals are from sensors located in the axle box and will be processed using the Empirical Mode Decomposition (EMD) technique. The EMD technique decomposes the temporal signal into some elementary intrinsic mode functions (IMF), which are the result of progressive envelopes of the temporal signal and that work as bandpass filters. The spectral power of each IMF reflects the frequency behavior of the vibratory signal for the frequency band associated with each IMF. The evolution of these IMF spectral powers will be studied before and after the maintenance intervention, so we can determine if this evolution can be used as an indicator of the operating state of the railway mechanical system.

Keywords

High-speed train Vibratory behavior Empirical Mode Decomposition Spectral power 

Notes

Acknowledgements

This work is supported by the Spanish Government through the MAQ-STATUS DPI2015-69325-C2-1-R project. The authors also gratefully acknowledge the help of the participating companies (Renfe, Alstom Spain, SKF Spain and Dano-Rail - Danobatgroup Railway).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • A. Bustos
    • 1
    Email author
  • H. Rubio
    • 1
  • C. Castejón
    • 1
  • J. C. García-Prada
    • 1
  1. 1.Universidad Carlos III de MadridLeganes-MadridSpain

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