Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/161983
Title: Image reconstruction of immersed ultrasonic testing for strongly attenuative materials
Authors: Jin, Haoran
Zheng, Zesheng
Liao, Xinqin
Zheng, Yuanjin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Jin, H., Zheng, Z., Liao, X. & Zheng, Y. (2022). Image reconstruction of immersed ultrasonic testing for strongly attenuative materials. Mechanical Systems and Signal Processing, 168, 108654-. https://dx.doi.org/10.1016/j.ymssp.2021.108654
Journal: Mechanical Systems and Signal Processing
Abstract: With the development of industrial materials, the objects of ultrasonic non-destructive evaluation (UNDE) have been expanded from metals to composite and polymer materials. However, composite and polymer materials are elastoplastic. The elastoplastic induced strong acoustic attenuation and dispersion affect the phases and waveforms of ultrasound waves. If overlooking these effects, the ultrasound reconstruction image will generate position deviation, resolution degradation and detail loss. To overcome this kind of deficiency, this paper introduces an ultrasound reconstruction that takes account of attenuation and dispersion compensation for the UNDE applications. It is derived from phase shift migration (PSM) by modifying the phase shift term with compensations of the attenuation and dispersion. This method can resolve imaging of layered media with depth-variant attenuation, such as commonly used immersed ultrasonic testing cases, while inheriting the high computational efficiency of PSM. Based on simulation and experimental results, the proposed method corrects the reconstruction deviation, improves image resolution, and restore details caused by depth variant attenuation and dispersion which literature methods cannot. For reconstructing a 3D image data sized of 4000 × 140 × 300 pixels, the memory cost can be controlled under 300 MB using recursive implementation, and the time cost can be reduced to 0.4 s using parallelization implementation.
URI: https://hdl.handle.net/10356/161983
ISSN: 0888-3270
DOI: 10.1016/j.ymssp.2021.108654
Rights: © 2021 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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