Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning
Freeform unobscured multiple-mirror systems have been widely applied in high-precision optical fields due to their high imaging quality and no chromatic aberration and central obstruction. However, how to design a freeform unobscured multiple-mirror system with small system volume, imaging quality,...
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MDPI AG
2025-04-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/12/5/405 |
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| author | Yiwei Sun Yangjie Wei Ji Zhao |
| author_facet | Yiwei Sun Yangjie Wei Ji Zhao |
| author_sort | Yiwei Sun |
| collection | DOAJ |
| description | Freeform unobscured multiple-mirror systems have been widely applied in high-precision optical fields due to their high imaging quality and no chromatic aberration and central obstruction. However, how to design a freeform unobscured multiple-mirror system with small system volume, imaging quality, and low manufacturing difficulty is challenging. This study proposes an adaptive generation method for freeform unobscured three-mirror systems with small volume and ease of fabrication based on machine learning, considering the fabrication constraints, volume limitations, imaging quality, and design efficiency. First, an error function based on volume, fabrication, and imaging quality functions is constructed, and a dataset is generated using this error function. Then, a machine learning model is trained using this dataset, enabling efficient prediction of the parameters for small-volume, easy-to-fabricate freeform unobscured three-mirror systems. Finally, the parameters of the freeform unobscured three-mirror system are predicted using the trained model, and combined with the freeform surface generation method, a freeform unobscured three-mirror imaging system is automatically obtained. Experimental results demonstrate that our method can effectively generate freeform unobscured three-mirror systems that meet the requirements for small volume and easy fabrication, providing a new approach for optical design. |
| format | Article |
| id | doaj-art-7b412b2dc35d457eac24d6cea6e0add1 |
| institution | Kabale University |
| issn | 2304-6732 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj-art-7b412b2dc35d457eac24d6cea6e0add12025-08-20T03:47:57ZengMDPI AGPhotonics2304-67322025-04-0112540510.3390/photonics12050405Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine LearningYiwei Sun0Yangjie Wei1Ji Zhao2School of Computer Science and Engineering, Northeastern University, Shenyang 110819, ChinaSchool of Computer Science and Engineering, Northeastern University, Shenyang 110819, ChinaCollege of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, ChinaFreeform unobscured multiple-mirror systems have been widely applied in high-precision optical fields due to their high imaging quality and no chromatic aberration and central obstruction. However, how to design a freeform unobscured multiple-mirror system with small system volume, imaging quality, and low manufacturing difficulty is challenging. This study proposes an adaptive generation method for freeform unobscured three-mirror systems with small volume and ease of fabrication based on machine learning, considering the fabrication constraints, volume limitations, imaging quality, and design efficiency. First, an error function based on volume, fabrication, and imaging quality functions is constructed, and a dataset is generated using this error function. Then, a machine learning model is trained using this dataset, enabling efficient prediction of the parameters for small-volume, easy-to-fabricate freeform unobscured three-mirror systems. Finally, the parameters of the freeform unobscured three-mirror system are predicted using the trained model, and combined with the freeform surface generation method, a freeform unobscured three-mirror imaging system is automatically obtained. Experimental results demonstrate that our method can effectively generate freeform unobscured three-mirror systems that meet the requirements for small volume and easy fabrication, providing a new approach for optical design.https://www.mdpi.com/2304-6732/12/5/405freeform unobscured three-mirror systemsmall volumeeasy fabricationmachine learningoptical system design |
| spellingShingle | Yiwei Sun Yangjie Wei Ji Zhao Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning Photonics freeform unobscured three-mirror system small volume easy fabrication machine learning optical system design |
| title | Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning |
| title_full | Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning |
| title_fullStr | Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning |
| title_full_unstemmed | Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning |
| title_short | Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning |
| title_sort | adaptive generation method for small volume easy fabrication freeform unobscured three mirror systems based on machine learning |
| topic | freeform unobscured three-mirror system small volume easy fabrication machine learning optical system design |
| url | https://www.mdpi.com/2304-6732/12/5/405 |
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