The Depression of Noise in AE Signals Based on sym8 Wavelet Analysis

To improve the signal-to-noise ratio of the fiber-optic Fabry-Perot acoustic emission sensors, the depression of noise in acoustic emission signals based on sym8 wavelet analysis is introduced. In the process of denoising the signal inspected by fiber-optic Fabry-Perot acoustic emission sensors, most noise of acoustic emission signals is eliminated by using the global soft-threshold filtering. Through analyzing and comparing figures of acoustic emission signals, the Sym8 wavelet of Sym wavelet series and the dasiaMinimaxipsila of threshold selection rules are selected and used to denoise the inspection signal. Test results show that acoustic emission signals can be denoised effectively and discernment to the AE signal is greatly improved by selecting basic wavelet, resolving level and de-noising threshold. Thus the wavelet soft-threshold filtering is an ideal denoising means for acoustic emission signals.