4.7 Article

Ultrasonic imaging of damage in plates in spectral ripple frequency domain

Journal

MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 195, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2023.110312

Keywords

Composite; Defect imaging; Barely Visible Impact Damage; Ultrasonic testing; Spectral ripple frequency

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This paper proposes a C-scan imaging technique in the spectral ripple frequency domain, which improves the evaluation of complex and distributed defects in multilayer heterogeneous materials. The method processes the full A-scan signal without time gate, making it suitable for curved or tilted parts. It has been successfully demonstrated on carbon fiber reinforced polymer laminates with barely visible impact damage, showing its capability to resolve neighboring delaminations and small defects.
The ultrasonic C-scan method is a well-known non-destructive inspection method which typically analyzes ultrasound echoes in time domain. Although demonstrated for a variety of defects and materials, it has certain challenges in correctly assessing complex and distributed defects in multilayer heterogeneous materials, e.g. barely visible impact damage in composite laminates. This paper proposes a C-scan imaging technique in the spectral ripple frequency domain by exploiting interference phenomena between multiple ultrasonic echoes in the response signal. The spectral ripple frequency domain imaging method processes the full A-scan signal without having to define an evaluation time gate. As such, it is highly suited for inspection of curved or tilted parts, or parts having different thickness sections. The method is demonstrated on several 5.5 mm thick carbon fiber reinforced polymer laminates with barely visible impact damage, revealing its capability to resolve neighboring delaminations and small defect fragments over the entire depth of the sample. The spectral ripple frequency domain imaging method shows good performance on datasets with high noise levels and/or low sampling rates, and is computationally very efficient, allowing real-time defect imaging.

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