Identification of Acoustic Emission Signals Based on Multi-Resolution Correlation Filtering
An approach of multi-resolution correlation filtering was presented to identify the transient responses of acoustic emission (AE). Two techniques were combined to avoid computational difficulties and obtain high identification efficiency. Wavelet multi-resolution analysis was first employed to decompose the original signal into a set of levels that correspond to different frequency bands. Using Mallat fast algorithm, the reconstructed signal in a certain level was obtained, which retained the main information of the original signal. These resulted in a considerable reduction in the data and a reduction in the computational time to perform correlation. Technique of Laplace correlation filtering was then used to identify frequency and damping characteristics of the reconstructed signal. Computational results demonstrated the accurate identification of the transient response of both a synthetically generated signal and actual acoustic emission testing signals. As a result, the approach of multi-resolution correlation filtering could be effectively utilized in AE detecting.
Yungang Li, Pengcheng Wang, Liqun Ai, Xiaoming Sang and Jinglong Bu
T. H. Zhang et al., "Identification of Acoustic Emission Signals Based on Multi-Resolution Correlation Filtering", Advanced Materials Research, Vols. 291-294, pp. 1994-2001, 2011