- Volume 31 Issue 3
DOI QR Code
A Study on Cepstrum Analysis for Wheel Flat Detection in Railway Vehicles
차륜의 찰상결함 진단을 위한 켑스트럼 분석 방법 연구
- Kim, Geoyoung (Department of Rolling Stock System, Graduate School of Railway, Seoul National University of Science & Technology) ;
- Kim, Hyuntae (Department of Rolling Stock System, Graduate School of Railway, Seoul National University of Science & Technology) ;
- Koo, Jeongseo (Department of Rolling Stock System, Graduate School of Railway, Seoul National University of Science & Technology)
- 김거영 (서울과학기술대학교 철도전문대학원 철도차량시스템공학과) ;
- 김현태 (서울과학기술대학교 철도전문대학원 철도차량시스템공학과) ;
- 구정서 (서울과학기술대학교 철도전문대학원 철도차량시스템공학과)
- Received : 2016.04.11
- Accepted : 2016.05.20
- Published : 2016.06.30
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.
condition-based maintenance;wheel flat detection;cepstrum analysis;fault diagnosis;monitoring system
Supported by : 국토교통과학기술진흥원
- B. Liang et al., "Railway Wheel Flat and Rail Surface Defect Detection by Time-frequency Analysis", Chemical Engineering Transactions, Vol.33, pp. 745-750, 2013.
- J. C. Kim et al., "Analysis of Vibration Parameters for the Fault Diagnosis of Reduction Unit for Highspeed Train", Korean Society of Precision Engineering, Vol. 30, No. 7, pp. 679-686, 2013. https://doi.org/10.7736/KSPE.2013.30.7.679
- Y. C. Choi and Y. H. Kim, "Fault Detection in a Ball Bearing System using Minimum Variance Cepstrum", Measurement Science and Technology, Vol. 18, No. 5, pp. 1433-1440, 2007. https://doi.org/10.1088/0957-0233/18/5/031
- R. B. Randall and J. Antoni, "Rolling Element Bearing Diagnostics-A tutorial", Mechanical Systems and Signal Processing, Vol. 25, No. 2, pp. 485-520, 2011. https://doi.org/10.1016/j.ymssp.2010.07.017
- R. B. Randall, "Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications", 1st Edition, Wiley, pp. 103-110, 2011.
- J. Antoni and R. B. Randall, "Differential Diagnosis of Gear and Bearing Faults", ASME Journal of Vibration and Acoustics, Vol. 124, No. 2, pp. 165-171, 2002. https://doi.org/10.1115/1.1456906
- R. W. Ngigi et al., "Modern Techniques for Condition Monitoring of Railway Vehicle Dynamics", Journal of Physics: Conference Series, Vol. 364, 2012.
- J. S. Im et al., "Development of Diagnosis System for Hub Bearing Fault in Driving Vehicle", Transactions of KSAE, Vol. 19, No. 2, pp. 72-77, 2011.
- B. P. Bogert, M. J. R. Healy and J. W. Tukey, "The Quefrency Analysis of Time Series for Echoes: Cepstrum, Pseudo-Autocovariance, Cross-Cepstrum and Saphe Cracking", Proc. of the Symposium on Time Series Analysis, pp. 209-243, 1963.
- J. O. Hallquist, LS-DYNA R8.0 Keyword User's Manual Vol. 1, LSTC Co., 2015.
- 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