Measuring acoustic roughness of a longitudinal railhead profile using a multi-sensor integration technique

Dahae Jeong, Han Shin Choi, Yong Je Choi, Wootae Jeong

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

It is necessary to measure accurately the rolling noise generated by the friction between wheels and rails in railway transport systems. Although many systems have recently been developed to measure the surface roughness of wheels and rails, there exist large deviations in measurements between each system whose measuring mechanism is based on a single sensor. To correct the structural problems in existing systems, we developed an automatic mobile measurement platform, named the Automatic Rail Checker (ARCer), which measures the acoustic roughness of a longitudinal railhead profile maintaining a constant speed. In addition, a new chord offset synchronization algorithm has been developed. This uses three displacement sensors to improve the measuring accuracy of the acoustic roughness of a longitudinal railhead profile, thereby minimizing the limitations of mobile platform measurement systems and measurement deviation. We then verified the accuracy of the measurement system and the algorithm through field tests on rails with different surface wear conditions.

Original languageEnglish
Article number1610
JournalSensors (Switzerland)
Volume19
Issue number7
DOIs
Publication statusPublished - 2019 Apr 1

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All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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