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Detection of ultrasonic flaw signals using wavelet transform techniques
Conference proceeding

Detection of ultrasonic flaw signals using wavelet transform techniques

J Xin, R Murthy, X Li and N.M Bilgutay
IEEE 1992 Ultrasonics Symposium Proceedings, v 1992-, pp 1211-1215 vol.2
1992

Abstract

Background noise Band pass filters Bandwidth Frequency diversity Grain boundaries Narrowband Nondestructive testing Signal processing Signal resolution Wavelet transforms
Ultrasonic detection and identification of flaws embedded in large-grained materials is often limited by the presence of high amplitude interfering echoes due to unresolvable grain boundaries. The split spectrum processing (SSP) technique using nonlinear algorithms is very effective in grain noise suppression and flaw detection. The wavelet transform technique is used to perform spectral decomposition, followed by the application of various nonlinear algorithms to obtain the output signal. The wavelet transform is based on the principle of constant Q or constant relative bandwidth frequency. Experimental results for the constant-Q SSP technique are presented. The experimental data indicate improved performance in identifying and extracting multiple targets compared to the conventional fixed bandwidth SSP.< >

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Web of Science research areas
Acoustics
Engineering, Electrical & Electronic
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