Numerically Trained Ultrasound AI for Monitoring Tool Degradation-Reference-Cited by-同舟云学术

Numerically Trained Ultrasound AI for Monitoring Tool Degradation

Published:2022-01-13 Issue:5 Volume:4 Page:2100215
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Jin Yuqi¹²,Wang Xinyue³,Fox Edward A.³,Xie Zhiwu⁴,Neogi Arup²,Mishra Rajiv S.⁵,Wang Tianhao⁶^ORCID

Affiliation:

1. Center for Agile and Adaptive Additive Manufacturing University of North Texas Denton TX 76207 USA

2. Department of Physics University of North Texas P.O. Box 311427 Denton TX 76203 USA

3. Department of Computer Science Virginia Tech Blacksburg VA 24061 USA

4. University Libraries Virginia Tech Blacksburg VA 24061 USA

5. Advanced Materials and Manufacturing Processes Institute Center for Friction Stir Processing University of North Texas Denton TX 76207 USA

6. Energy and Environment Directorate Pacific Northwest National Laboratory 902 Battelle Blvd. Richland WA 99352 USA

Funder

National Science Foundation

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202100215

Reference22 articles.

1. W. M.Thomas E. D.Nicholas J. C.Needham M. G.Murch P.Temple-Smith C. J.Dawes Patent PCT/GB92/02203; US9125978.8 1991.

2. C.Smith Global Friction Stir Welding Market to Exceed US$ 1.04 Bn by 2026 Credence Research [Online].https://www.credenceresearch.com/press/global-friction-stir-welding-market.

3. Heat Transfer in Friction Stir Welding—Experimental and Numerical Studies

4. Heat Input and Temperature Distribution in Friction Stir Welding

5. P.Colegrove M.Painter D.Graham T.Miller inProc. of the Second Int. Symp. on Friction Stir Welding Gothenburg Sweden 2000.

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