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For: Xu W, Li X, Zhang J, Xue Z, Cao J. Ultrasonic signal enhancement for coarse grain materials by machine learning analysis. Ultrasonics 2021;117:106550. [PMID: 34399134 DOI: 10.1016/j.ultras.2021.106550] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/29/2021] [Accepted: 08/07/2021] [Indexed: 06/13/2023]
Number Cited by Other Article(s)
1
Rawicki Ł, Krawczyk R, Słania J, Peruń G, Golański G, Łuczak K. Analysis of the Suitability of Ultrasonic Testing for Verification of Nonuniform Welded Joints of Austenitic-Ferritic Sheets. MATERIALS (BASEL, SWITZERLAND) 2024;17:4216. [PMID: 39274606 PMCID: PMC11396049 DOI: 10.3390/ma17174216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Revised: 06/30/2024] [Accepted: 07/02/2024] [Indexed: 09/16/2024]
2
Prabhakara P, Lay V, Mielentz F, Niederleithinger E, Behrens M. Enhancing the Performance of a Large Aperture Ultrasound System (LAUS): A Combined Approach of Simulation and Measurement for Transmitter-Receiver Optimization. SENSORS (BASEL, SWITZERLAND) 2023;24:100. [PMID: 38202962 PMCID: PMC10781345 DOI: 10.3390/s24010100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024]
3
Xie L, Zhang S, Wang L, Cheng C, Li X. Modeling ultrasonic wave fields scattered by flaws using a quasi-Monte Carlo method: Theoretical method and experimental verification. ULTRASONICS 2023;132:107002. [PMID: 37037127 DOI: 10.1016/j.ultras.2023.107002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 02/17/2023] [Accepted: 03/31/2023] [Indexed: 05/29/2023]
4
Sun H, Ramuhalli P, Jacob RE. Machine learning for ultrasonic nondestructive examination of welding defects: A systematic review. ULTRASONICS 2023;127:106854. [PMID: 36215762 DOI: 10.1016/j.ultras.2022.106854] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 08/29/2022] [Accepted: 09/20/2022] [Indexed: 06/16/2023]
5
Allam A, Alfahmi O, Patel H, Sugino C, Harding M, Ruzzene M, Erturk A. Ultrasonic testing of thick and thin Inconel 625 alloys manufactured by laser powder bed fusion. ULTRASONICS 2022;125:106780. [PMID: 35716606 DOI: 10.1016/j.ultras.2022.106780] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 06/15/2023]
6
Bowler AL, Pound MP, Watson NJ. A review of ultrasonic sensing and machine learning methods to monitor industrial processes. ULTRASONICS 2022;124:106776. [PMID: 35653984 DOI: 10.1016/j.ultras.2022.106776] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 04/29/2022] [Accepted: 05/26/2022] [Indexed: 06/15/2023]
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