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27 April 2020 Non-contact super-resolution guided wave array imaging of subwavelength defects using deep learning (Conference Presentation)
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Abstract
We present an ultrasonic array imaging approach based on deep learning to characterize structural defects. The proposed deep learning-based approach takes a raw ultrasonic defect image as an input and gives an output of a quantitative defect image. The test results obtained using finite element (FE) simulation and experimental data demonstrate that the fine structural features defects are successfully restored and visualized by the proposed deep learning approach.
Conference Presentation
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Homin Song and Yongchao Yang "Non-contact super-resolution guided wave array imaging of subwavelength defects using deep learning (Conference Presentation)", Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 1137910 (27 April 2020); https://doi.org/10.1117/12.2557451
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