Prediction of Depth of Defect from Phased Array Ultrasonic Testing Data Using Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0918-2_9
Reference11 articles.
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2. Taheri H, Bocanegra MG, Taheri M (2022) Artificial intelligence, machine learning and smart technologies for nondestructive evaluation. Sensors 20(11):4055
3. Sun H, Ramuhalli P, Jacob RE (2023) Machine learning for ultrasonic nondestructive examination of welding defects: a systematic review. Ultrasonics 127:106854
4. Chinchilla SC, Wilcox PD, Croxford AJ (2022) Deep learning in automated ultrasonic NDE—developments, axioms and opportunities. NDT E Int 131:102703
5. Amiri N, Farrahia GH, Kashyzadeha KR, Chizarib M (2020) Applications of ultrasonic testing and machine learning methods to predict the static & fatigue behavior of spot-welded joints. J Manuf Process 52:26–34
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