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Advances in Acoustics and Vibration
Volume 2012, Article ID 957379, 10 pages
Research Article

Ultrasonic Flaw Detection and Imaging through Reverberant Layers via Subspace Analysis and Projection

1Center for Advanced Communication, Villanova University, Villanova, PA 19085, USA
2School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 201418, China

Received 12 March 2012; Revised 30 May 2012; Accepted 31 May 2012

Academic Editor: Erdal Oruklu

Copyright © 2012 Ramazan Demirli et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Ultrasonic flaw detection and imaging through reverberant layers are challenging problems owing to the layer-induced reverberations and front surface reflections. These undesired signals present a strong clutter and mask the flaw echoes. In this paper, a subspace-based approach is developed for removing, or significantly reducing, the unwanted reverberations, enabling proper flaw detection and imaging. The technique utilizes a set of independent clutter-only reference measurements of the material through the layer. If these measurements are not available, array measurements of the material with flaws are used instead. The clutter, due to its high strength relative to the flaw reflections, forms a subspace spanned by the eigenvectors corresponding to the dominant eigenvalues of the data covariance matrix. The clutter subspace is estimated and removed using orthogonal subspace projection. The clutter usually occupies multidimension subspace that is dependent on the level of coupling, material inhomogeneity, surface roughness, and the sampling rate of the measurements. When the clutter-only reference is not available, information theoretic techniques are used to estimate the dimension of the clutter subspace so that clutter signals are sufficiently suppressed without distorting the flaw signals. The effectiveness of the proposed approach is demonstrated using simulations and real measurement results.