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Rail monitoring using in-service vehicles enables the fast detection of surface defects, which are often responsible for high noise emission. In this paper a processing sequence is presented that converts axle box accelerations into rail condition indicators based on spectral characteristics of the rail surface. The methodology is exemplified with data acquired with a shunter locomotive operating at an inland harbour in the city of Braunschweig, Germany.

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Spectral Characterization of the Rail Surface in Urban Environments Using in-Service Vehicles

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Benjamin Baasch,
  • Judith Heusel,
  • Alexander Lähns,
  • Michael Roth,
  • Jörn Groos

摘要

Rail monitoring using in-service vehicles enables the fast detection of surface defects, which are often responsible for high noise emission. In this paper a processing sequence is presented that converts axle box accelerations into rail condition indicators based on spectral characteristics of the rail surface. The methodology is exemplified with data acquired with a shunter locomotive operating at an inland harbour in the city of Braunschweig, Germany.