Wavelet threshold de-noising of rock acoustic emission signals subjected to dynamic loads

The discrete wavelet transform theory was used to process non-stationary rock acoustic emission signals recorded in split Hopkinson pressure bar tests. Wavelet basis db10 was selected as the optimum wavelet for processing such signals by calculating the reconstruction root mean square error (RMSE) of each wavelet basis candidate, and the unbiased estimation procedure SURE was used to determine the threshold value for each decomposition level. Denoising by wavelet thresholding and conventional low-pass filter were compared by evaluating the signal to noise ratio and RMSE. Results show that discrete wavelet transform has a favorable denoising effect and better signal reconstruction capability, and also indicate that the wavelet technique is especially suitable for denoising non-stationary signals like the transient signals of rock acoustic emission under impact loading.

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