Advances in subsurface defect detection techniques for fused silica optical components: A literature review
Fused silica is widely used in high-power laser systems, astronomy and military fields due to its excellent optical and physical properties. However, Subsurface defects(SSDs), such as microcracks, scratches, plastic deformation, and pits are often formed during mechanical processing, which can serio...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Journal of Materials Research and Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785425000456 |
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| author | Hongbing Cao Xing Peng Feng Shi Ye Tian Lingbao Kong Menglu Chen Qun Hao |
| author_facet | Hongbing Cao Xing Peng Feng Shi Ye Tian Lingbao Kong Menglu Chen Qun Hao |
| author_sort | Hongbing Cao |
| collection | DOAJ |
| description | Fused silica is widely used in high-power laser systems, astronomy and military fields due to its excellent optical and physical properties. However, Subsurface defects(SSDs), such as microcracks, scratches, plastic deformation, and pits are often formed during mechanical processing, which can seriously reduce the optical performance and durability of fused silica. This paper first discusses the formation mechanism of SSDs in fused silica due to mechanical stress, thermal effects, etc. during mechanical processing such as cutting, grinding, and polishing. Then, the commonly used destructive and non-destructive detection methods are reviewed, and the principles and latest progress of each technique are discussed. The potential of deep learning algorithms for SSD detection is also examined. Finally, future directions for research and development are proposed to provide a valuable reference for researchers in the field. |
| format | Article |
| id | doaj-art-52004f4561bb4c74a796a5ce67ebf91d |
| institution | Kabale University |
| issn | 2238-7854 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Materials Research and Technology |
| spelling | doaj-art-52004f4561bb4c74a796a5ce67ebf91d2025-01-17T04:49:33ZengElsevierJournal of Materials Research and Technology2238-78542025-03-0135809835Advances in subsurface defect detection techniques for fused silica optical components: A literature reviewHongbing Cao0Xing Peng1Feng Shi2Ye Tian3Lingbao Kong4Menglu Chen5Qun Hao6College of Intelligent Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China; Hunan Provincial Key Laboratory of Ultra-Precision Machining Technology, Changsha, Hunan 410073, ChinaCollege of Intelligent Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China; Hunan Provincial Key Laboratory of Ultra-Precision Machining Technology, Changsha, Hunan 410073, China; Corresponding author. College of Intelligent Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China.College of Intelligent Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China; Hunan Provincial Key Laboratory of Ultra-Precision Machining Technology, Changsha, Hunan 410073, ChinaCollege of Intelligent Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China; Hunan Provincial Key Laboratory of Ultra-Precision Machining Technology, Changsha, Hunan 410073, ChinaShanghai Engineering Research Center of Ultra-precision Optical Manufacturing, School of Information Science and Technology, Fudan University, Shanghai 200433, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China; Physics Department, Changchun University of Science and Technology, Changchun 130022, ChinaFused silica is widely used in high-power laser systems, astronomy and military fields due to its excellent optical and physical properties. However, Subsurface defects(SSDs), such as microcracks, scratches, plastic deformation, and pits are often formed during mechanical processing, which can seriously reduce the optical performance and durability of fused silica. This paper first discusses the formation mechanism of SSDs in fused silica due to mechanical stress, thermal effects, etc. during mechanical processing such as cutting, grinding, and polishing. Then, the commonly used destructive and non-destructive detection methods are reviewed, and the principles and latest progress of each technique are discussed. The potential of deep learning algorithms for SSD detection is also examined. Finally, future directions for research and development are proposed to provide a valuable reference for researchers in the field.http://www.sciencedirect.com/science/article/pii/S2238785425000456Fused silicaSubsurface damageDefect detectionDeep learning |
| spellingShingle | Hongbing Cao Xing Peng Feng Shi Ye Tian Lingbao Kong Menglu Chen Qun Hao Advances in subsurface defect detection techniques for fused silica optical components: A literature review Journal of Materials Research and Technology Fused silica Subsurface damage Defect detection Deep learning |
| title | Advances in subsurface defect detection techniques for fused silica optical components: A literature review |
| title_full | Advances in subsurface defect detection techniques for fused silica optical components: A literature review |
| title_fullStr | Advances in subsurface defect detection techniques for fused silica optical components: A literature review |
| title_full_unstemmed | Advances in subsurface defect detection techniques for fused silica optical components: A literature review |
| title_short | Advances in subsurface defect detection techniques for fused silica optical components: A literature review |
| title_sort | advances in subsurface defect detection techniques for fused silica optical components a literature review |
| topic | Fused silica Subsurface damage Defect detection Deep learning |
| url | http://www.sciencedirect.com/science/article/pii/S2238785425000456 |
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