Study on the Denoising Processing of Ultrasonic Testing Signal for Standing Trees Based on Wavelet Transform

Abstract

To remove the impact of noise on the ultrasonic testing signals of standing trees, wavelet transform method was used to eliminate the noise in the collected ultrasonic signals in the field. In order to achieve the best denoising effect, four kinds of wavelet base denoising parameters including Daubechies (db), Symlets (sym), Coiflets (coif), and Discrete Meyer (dmey) were compared, and the best denoising effect was obtained with db3 wavelet base. The variations of denoising parameters corresponding to the number of db3 wavelet decomposition levels (1- 8) were further analyzed and the decomposition level 4 was demonstrated the best. Meanwhile, the effects of wavelet denoising under different threshold states were compared and the hard rigrsure threshold was demonstrated the best. Experimental results showed that the wavelet transform can effectively remove noise hidden in the ultrasonic signal and improve the denoising effect by selecting reasonable parameters, which laid some initial groundwork for efficient extraction of useful information from the ultrasonic signals.