A High-Precision Defect Quantification Method Using a Unilateral Oblique Focusing Guided Wave EMAT and a Theory-Informed Explainable Progressive Residual Deep Convolutional Network
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT（2024）
Key words
Acoustics,Feature extraction,Artificial neural networks,Focusing,Transducers,Convolutional neural networks,Visualization,Defect quantification,electromagnetic acoustic transducers (EMAT),Grad-CAM plus plus,progressive residual network,unilateral oblique focusing (UOF),visual explanation
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