Vibration characterization analysis of rail induced by surface pits using Hilbert-Huang Transform

This paper reports the application of the Hilbert-Huang Transform (HHT) to the dynamic characterization of rail vibration induced by surface pits. A different acceleration signal of rail induced by surface pits is adaptively decomposed into Intrinsic Mode Functions (IMFs) through the use of Empirical Mode Decomposition (EMD) methods. Based on the EMD, the associated time-frequency-energy distribution, i.e., the Hilbert spectrum is obtained for the analysis of the rail vibration signal and subsequent identification of its corresponding energy characteristics. In order to assess the effectiveness of the approach, the results obtained using the HHT are compared with those from wavelet based methods. It is found that the extracted energy characteristics give a good indication of the dynamic state of raU high frequency vibration and thus can be used for rail pits recognition. The proposed method is a useful tool for the in depth understanding and subsequent quantitative characterization of rail high frequency vibration.