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A Study on Cepstrum Analysis for Wheel Flat Detection in Railway Vehicles

차륜의 찰상결함 진단을 위한 켑스트럼 분석 방법 연구

  • Received : 2016.04.11
  • Accepted : 2016.05.20
  • Published : 2016.06.30

Abstract

Since defects in the wheels of railway vehicles, which occur due to wears with the rail, cause serious damage to the running device, the diagnostic monitoring system for condition-based maintenance is required to secure the driving safety. In this paper, we studied to apply a useful Cepstrum analysis to detect periodic structure in spectrum among the vibration signal processing techniques for the fault diagnosis of a rotating body such as wheel. In order to analyze in variations of train velocity, the Cepstrum analysis was performed after a domain change of the vibration signal from time domain to rotation angle domain. When domains change, it is important to use a interpolation for a uniform interval of the rotation angle. Finally, the Cepstrum analysis for wheel flat detection was verified by using the vibration signal including the disturbance resulting from the rail irregularities and the vibration of bogie components.

Keywords

condition-based maintenance;wheel flat detection;cepstrum analysis;fault diagnosis;monitoring system

References

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Cited by

  1. Detection of Air-conditioner Blower Noise Defect in the Assembly Line Using Cepstrum vol.28, pp.5, 2018, https://doi.org/10.5050/KSNVE.2018.28.5.608

Acknowledgement

Supported by : 국토교통과학기술진흥원