Smart Structures and Systems

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Acoustic emission source location and noise cancellation for crack detection in rail head

  • Kuanga, K.S.C. (Department of Civil and Environmental Engineering, National University of Singapore) ;
  • Li, D. (Department of Civil and Environmental Engineering, National University of Singapore) ;
  • Koh, C.G. (Department of Civil and Environmental Engineering, National University of Singapore)
  • Received : 2015.12.03
  • Accepted : 2016.07.27
  • Published : 2016.11.25
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Abstract

Taking advantage of the high sensitivity and long-distance detection capability of acoustic emission (AE) technique, this paper focuses on the crack detection in rail head, which is one of the most vulnerable parts of rail track. The AE source location and noise cancellation were studied on the basis of practical rail profile, material and operational noise. In order to simulate the actual AE events of rail head cracks, field tests were carried out to acquire the AE waves induced by pencil lead break (PLB) and operational noise of the railway system. Wavelet transform (WT) was first utilized to investigate the time-frequency characteristics and dispersion phenomena of AE waves. Here, the optimal mother wavelet was selected by minimizing the Shannon entropy of wavelet coefficients. Regarding the obvious dispersion of AE waves propagating along the rail head and the high operational noise, the wavelet transform-based modal analysis location (WTMAL) method was then proposed to locate the AE sources (i.e. simulated cracks) respectively for the PLB-induced AE signals with and without operational noise. For those AE signals inundated with operational noise, the Hilbert transform (HT)-based noise cancellation method was employed to improve the signal-to-noise ratio (SNR). Finally, the experimental results demonstrated that the proposed crack detection strategy could locate PLB-simulated AE sources effectively in the rail head even at high operational noise level, highlighting its potential for field application.

Keywords

Acknowledgement

Supported by : National University of Singapore Academic

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