Signal De-noising in Ultrasonic Testing Based on Stationary Wavelet Transform

In ultrasonic testing, the quality of flaw echo-signals is a foundation for locating, quantitative and qualitative analysis. Thus, signal de-noising and increasing of the signal-to-noise ratio (SNR) are a key to successful application of ultrasonic NDT and AIDE In this paper, the theory of discrete wavelet transform (DWT) and stationary wavelet transform (SWT) is introduced Moreover, differences are compared between DWT and SWT in signal decomposition and reconstruction. And according to the characteristics of ultrasonic flaw echo-signals, the principle and method of de-noising via thresholding based on SWT are studied Finally, the experiment of signal de-noising v DWT and SWT are carried out for actual defect echo-signals. The experimental results show that SWT has the advantage of translation invariance after signal de-noising This method not only can greatly remove the noises, but also provide the exact data for accurate localization of flaw