Application of Empirical Mode Decomposition for Ultrasonic Testing of Coarse-grained Materials

Abstract In ultrasonic testing of coarse-grained materials, signal to noise ratio (SNR) of testing signals is reduced seriously for the structure noise, and echoes from defects are difficult to be identified. In order to improve the SNR and the reliability of ultrasonic testing of coarse-grained materials, empirical mode decomposition (EMD) is introduced to process the testing signal here. Signal envelope can be formed by using cubic spline interpolation, and nonlinear and non-stationary signal can be decomposed self-adaptive into the sum of several intrinsic mode functions (IMF) by using characteristic time scale of the signals, and then higher order and tendency of the original signals can be obtained. The denoising experiment with low SNR simulated signal are achieved according to the feature of EMD, and SNR is enhanced more by comparison with the wavelet analysis method. And testing signal collected from coarse-grained materials is used to finish denoising experiment, and it is shown from the experiment result that the EMD has better adaptive ability in decomposing noise-polluted signals and less empirical information is required in the denoising process.