Abstract
According to the acousto elastic effect, the residual stress on the surface of the rail can be evaluated by measuring the change in the propagation velocity of ultrasonic waves, such as longitudinal critically refracted (LCR) waves on the surface of the rail. The LCR wave signal is often polluted by a variety of noise sources, coupled with the influence of the poor surface condition of the inspected component, which greatly reduces the detectability and online measurement ability of the LCR wave signal. This paper proposes the application of the lifting scheme wavelet packet transform (LSWPT) denoising method to solve the noise suppression problem of LCR wave signal. The traditional wavelet transform (WT), wavelet packet transform (WPT), as well as the lifting scheme wavelet transform (LSWT) and lifting scheme wavelet packet transform are compared and analyzed in the soft thresholding and hard thresholding processing of denoising ability and efficiency of the noisy LCR wave signal. The experimental results show that the LSWPT method has the characteristics of fast calculation speed and a good denoising effect, and it is an efficient method of denoising signals for on-line ultrasonic measurement of residual stress on the rail surface.
Highlights
Residual stresses in the surface layer of steel rails are generated during production and use
In order to relate ultrasonic velocities to residual stress, the ultrasonic method generally requires higher-order elastic constants [5]. These constants which are dependent on the metallurgical texture [6], the type of wave and the direction of wave propagation relative to the direction of stress [7] must be experimentally determined for a particular material being examined
The denoising method based on lifting scheme wavelet packet transform (LSWPT) is similar to lifting scheme wavelet transform (LSWT), both of which achieve the purpose of denoising by threshold quantization of the high-frequency coefficients of the wavelet decomposition
Summary
Residual stresses in the surface layer of steel rails are generated during production and use. Wavelet transform (WT) denoising can suppress the interference of high-frequency noise, effectively distinguish high-frequency information from high-frequency noise and protect the spikes and sudden changes of useful signals. The WPT has the characteristics of adaptive narrowband filtering, full frequency domain taper resolution capability, complete reconstruction characteristics, and optimal time-frequency representation of signals under different criteria It has been widely used in ultrasonic detection signal denoising [15,16], the signal-to-noise ratio (SNR) of the ultrasonic testing signal has been significantly improved [17]. Li et al [22] proposed a wavelet packet singular-value decomposition (WPSD) denoising method to reduce the noise of the ultrasonic echo signal of the thick-walled oil pipeline, which effectively improves the SNR of the signal.
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