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Proceedings Papers

Structures Inversion and Optimization in Cased-Wells Based on Deep Learning

Zhang Zhang, Zhoumo Zeng, Xiaocen Wang, Shili Chen, Yang Liu
Proc. ASME. QNDE2022, 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T07A007, July 25–27, 2022
Paper No: QNDE2022-98591
DOI: https://doi.org/10.1115/QNDE2022-98591
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Topics: Acoustical properties, Acoustics, Artificial neural networks, Filtration, Finite difference time-domain analysis, Imaging, Machine learning, Modeling, Optimization, Rocks
Proceedings Papers

High-Resolution Thickness Mapping with Deepfit and Lamb Guided Waves

Junkai Tong, Min Lin, Jian Li, Shili Chen, Yang Liu
Proc. ASME. QNDE2022, 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T07A001, July 25–27, 2022
Paper No: QNDE2022-98221
DOI: https://doi.org/10.1115/QNDE2022-98221
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Topics: Artificial neural networks, Imaging, Resolution (Optics), Waves
Proceedings Papers

Development of a Convolutional Neural Network Assisted Fiber Optics Based Passive Structural Health Monitoring System

Ainulla Khan, Krishnan Balasubramaniam
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T16A003, July 28–30, 2021
Paper No: QNDE2021-75192
DOI: https://doi.org/10.1115/QNDE2021-75192
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Topics: Artificial neural networks, Fiber Bragg gratings, Noise (Sound), Optical fiber, Sensors, Structural health monitoring
Proceedings Papers

Benefit of Neural Network for the Optimization of Defect Detection on Composite Material Using Ultrasonic Non Destructive Testing

P. Trouvé-Peloux, B. Abeloos, A. Ben Fekih, C. Trottier, J.-M. Roche
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T07A007, July 28–30, 2021
Paper No: QNDE2021-75925
DOI: https://doi.org/10.1115/QNDE2021-75925
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Topics: Artificial neural networks, Composite materials, Flaw detection, Nondestructive evaluation, Optimization, Databases, Image segmentation, Machine learning, Semantics, Ultrasonic testing
Proceedings Papers

Application of Artificial Intelligence for Automated Detection of Defects in Nuclear Energy Domain

Eleftherios Anagnostopoulos, Yann Kernin
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T07A002, July 28–30, 2021
Paper No: QNDE2021-74889
DOI: https://doi.org/10.1115/QNDE2021-74889
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Topics: Artificial intelligence, Artificial neural networks, Flaw detection, Nozzles, Nuclear power, Nuclear power stations, Reactor vessels, Pressurized water reactors, Circuits, Crack detection
Proceedings Papers

Robust Guided Wave Tomography Method for Large and Irregular Defects

Junkai Tong, Min Lin, Xiaocen Wang, Jiahao Ren, Jian Li, Yang Liu
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T11A007, July 28–30, 2021
Paper No: QNDE2021-75023
DOI: https://doi.org/10.1115/QNDE2021-75023
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Topics: Artificial neural networks, Diffraction, Imaging, Waves, Resolution (Optics), Algorithms, Corrosion, Errors, Nondestructive evaluation, Shapes
Proceedings Papers

Guided Wave Imaging Based on Fully Connected Neural Network for Quantitative Corrosion Assessment

Xiaocen Wang, Min Lin, Junkai Tong, Lin Liang, Jian Li, Zhoumo Zeng, Yang Liu
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T11A006, July 28–30, 2021
Paper No: QNDE2021-75020
DOI: https://doi.org/10.1115/QNDE2021-75020
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Topics: Artificial neural networks, Corrosion, Damage, Imaging, Waves
Proceedings Papers

Enhancing Vibration-Based Structural Health Monitoring via Edge Computing: A Tiny Machine Learning Perspective

Federica Zonzini, Francesca Romano, Antonio Carbone, Matteo Zauli, Luca De Marchi
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T07A004, July 28–30, 2021
Paper No: QNDE2021-75153
DOI: https://doi.org/10.1115/QNDE2021-75153
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Topics: Machine learning, Structural health monitoring, Vibration, Artificial neural networks, Accuracy and precision, Artificial intelligence, Bridges (Structures), Sensors
Proceedings Papers

Estimating Guided Wave Velocity Variation With Neural Networks

Ori Leibovici, Kang Yang, Joel B. Harley
Proc. ASME. QNDE2021, 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, V001T07A003, July 28–30, 2021
Paper No: QNDE2021-75080
DOI: https://doi.org/10.1115/QNDE2021-75080
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Topics: Artificial neural networks, Waves, Machine learning, Damage, Signals, Structural health monitoring, Temperature, Feedforward control, Safety, Sensors