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Monitoring Rail Condition Based on Sound and Vibration Sensors Installed on an Operational Train

  • T. JensenEmail author
  • S. Chauhan
  • K. Haddad
  • W. Song
  • S. Junge
Part of the Notes on Numerical Fluid Mechanics and Multidisciplinary Design book series (NNFM, volume 126)

Abstract

The paper presents a measurement setup capable of collecting wheel/rail contact noise and vibration signals from a passenger train. A data analysis method based on machine learning is developed for detecting events from the acquired data and classifying them according to relevant railway track components and noise phenomena. A classification rate higher than 84 % is achieved.

Keywords

False Positive Rate Gaussian Mixture Model Sound Pressure Level True Positive Rate Validation Dataset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • T. Jensen
    • 1
    Email author
  • S. Chauhan
    • 2
  • K. Haddad
    • 2
  • W. Song
    • 2
  • S. Junge
    • 3
  1. 1.BanedanmarkCopenhagenDenmark
  2. 2.Bruel & Kjaer Sound & Vibration Measurement A/SNaerumDenmark
  3. 3.Grontmij A/SGlostrupDenmark

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