Sparse wavefield reconstruction based on Physics-Informed neural networks
文献类型：期刊论文
| 作者 | Xu, Bin1; Zou, Yun1; Sha, Gaofeng2; Yang, Liang3; Cai, Guixi3; Li, Yang1 |
| 刊名 | ULTRASONICS
 |
| 出版日期 | 2025-05-01 |
| 卷号 | 149页码:12 |
| 关键词 | Physics-Informed Neural Networks Wavefield Reconstruction Laser Ultrasonic Non-destructive Testing |
| ISSN号 | 0041-624X |
| DOI | 10.1016/j.ultras.2025.107582 |
| 通讯作者 | Li, Yang(yangli@zzu.edu.cn) |
| 英文摘要 | In recent years, the widespread application of laser ultrasonic (LU) devices for obtaining internal material information has been observed. However, this approach demands a significant amount of time to acquire complete wavefield data. Hence, there is a necessity to reduce the acquisition time. In this work, we propose a method based on physics-informed neural networks to decrease the required sampling measurements. We utilize sparse sampling of full experimental data as input data to reconstruct complete wavefield data. Specifically, we employ physics-informed neural networks to learn the propagation characteristics from the sparsely sampled data and partition the complete grid to reconstruct the full wavefield. We achieved 95% reconstruction accuracy using four hundredth of the total measurements. The proposed method can be utilized not only for sparse wavefield reconstruction in LU testing but also for other wavefield reconstructions, such as those required in online monitoring systems. |
| 资助项目 | National Natural Science Founda-tion of China[51705470] ; Henan Provincial Key Scientific Research Project of Higher Education Institutions[222102220025] |
| WOS研究方向 | Acoustics ; Radiology, Nuclear Medicine & Medical Imaging |
| 语种 | 英语 |
| WOS记录号 | WOS:001409822300001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Founda-tion of China ; Henan Provincial Key Scientific Research Project of Higher Education Institutions |
| 源URL |  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Li, Yang |
| 作者单位 | 1.Zhengzhou Univ, Sch Mech & Power Engn, Zhengzhou 450001, Peoples R China 2.Clover Pk Tech Coll, Sch Adv Mfg, Lakewood, WA 98499 USA 3.Chinese Acad Sci, Inst Met Res, Shenyang 110016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Bin,Zou, Yun,Sha, Gaofeng,et al. Sparse wavefield reconstruction based on Physics-Informed neural networks[J]. ULTRASONICS,2025,149:12. |
| APA | Xu, Bin,Zou, Yun,Sha, Gaofeng,Yang, Liang,Cai, Guixi,&Li, Yang.(2025).Sparse wavefield reconstruction based on Physics-Informed neural networks.ULTRASONICS,149,12. |
| MLA | Xu, Bin,et al."Sparse wavefield reconstruction based on Physics-Informed neural networks".ULTRASONICS 149(2025):12. |
入库方式： OAI收割
来源：金属研究所
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