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Wavelet Transform Signal Processing to Distinguish Different Acoustic Emisson Sources

Published

Author(s)

K S. Downs, Marvin A. Hamstad, E P. Baars

Abstract

A database of wideband acoustic emission (AE) modeled signals were used to continue to examine the use of wavelet transform (WT) results to accomplish identification of AE sources. The AE signals in the database were created by use of a validated three-dimensional finite element code. These signals represented the out-of-plane displacements from buried dipole sources in aluminum plates 4.7 mm thick with large lateral dimensions. The surface displacement signals at three far-field distances were filtered with a 40 kHz high-pass filter prior to applying the WT. The WTs were calculated with a free software program. The WT peak magnitudes were calculated a three key frequencies (i.e., 60, 270, and 522 kHz) for all the signals generated by three different source types (i.e., in-plane dipole, microcrack initiation, and balanced shear). The signal database covered seven different radiation angles (from 0 degrees to 90 degrees) and six or seven depths for each source type. The fundamental Lamb modes that correspond to the WT peak magnitudes were also determined. It was concluded that the variation of the normalized peak WT magnitudes as a function of the radiation angle was effectively constant for the various source depths. This effective independence of source depth was demonstrated for a fixed source type, propagation distance, and key frequency-mode combination. Use of the fact that the radiation-angle dependence varied among source types for particular frequency-mode combinations allowed ratios of the WT peak magnitudes at different radiation angles to be used to uniquely distinguish the different source types.
Citation
Journal of Acoustic Emission
Volume
21

Keywords

acoustic emission, acoustic emission modeling, AE, far-field, finite element modeling, source identification, wavelet transform, wideband acoustic emission, WT

Citation

Downs, K. , Hamstad, M. and Baars, E. (2003), Wavelet Transform Signal Processing to Distinguish Different Acoustic Emisson Sources, Journal of Acoustic Emission, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=851337 (Accessed April 19, 2024)
Created December 31, 2002, Updated October 12, 2021