Electromagnetic Acoustic Signal Processing Methods for Rail Surface Detection

To increase the amplitude and the SNR(Signal Noise Ratio) of electromagnetic acoustic signals in rail surface detection, proper signal processing methods were studied. Wavelet transform was used to denoise the signals and the signal envelopes were extracted through Hilbert transform algorithm. The ultrasonic images of the rail surface were presented, making the detection results more clearly. A hybrid programming language between LabWindows/CVI and Matlab was used to develop the software. Experiments indicated that the methods could improve the SNR of electromagnetic acoustic signals significantly, thus leading to the effective detection and location of rail surface defects.