The Prediction of Incremental Damage on Optics from the Final Optic Assembly in an ICF High-Power Laser Facility
| Autor: | Xueyan Hu, Wei Zhou, Huaiwen Guo, Xiaoxia Huang, Bowang Zhao, Wei Zhong, Qihua Zhu, Zhifei Chen |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Applied Sciences, Vol 14, Iss 12, p 5226 (2024) |
| Druh dokumentu: | article |
| ISSN: | 14125226 2076-3417 |
| DOI: | 10.3390/app14125226 |
| Popis: | High-power laser facilities necessitate predicting incremental damage to final optics to identify evolving damage trends. In this study, we propose a surface damage detection method utilizing image segmentation employing ResNet-18 and a damage area estimation network employing U-Net++. Paired sets of online and offline images of optics obtained from a large laser facility are used to train the network. The trends of varying damage could be identified by incorporating additional experimental parameters. A key advantage of the proposed method is that the network can be trained end to end on small samples, eliminating the need for manual labeling or feature extraction. The software developed based on these models can facilitate the daily inspection and maintenance of optics in large laser facilities. By effectively applying deep learning techniques, we successfully addressed the challenges faced by traditional methods in handling complex environments, achieving the accurate identification and prediction of damages on optics. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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