Intelligent inspection system framework for surface damage mitigation of large-aperture optics

Micron-level surface damages can seriously affect the optical and mechanical properties of large-aperture optics, so it is of great significance to perform high-precision inspection and mitigation of surface damages. Surface micro-damages are not only multi-category but also randomly distributed on the optics. Manual inspection and mitigation are not only time-consuming but also difficult to ensure the accuracy and reliability of mitigation, so it cannot meet the engineering requirements for large-volume mitigation of optics. In order to solve this problem, an intelligent inspection system framework for optics surface damage mitigation is proposed in this paper. The inspection system consists of an optics surface ranging fitting module, a dark-field rapid inspection module, and a multi-illumination micro-inspection module. Based on the above modules, a damage inspection process flow is established, including automatic alignment of optics surface, rapid dark-field inspection of flaws with large field of view, microscopic precision inspection of damages with small field of view, automatic configuration and execution of damage mitigation strategies, and quality control of mitigation structure. In order to realize the above flow, a predictive model library related to damage inspection is constructed, including: a dark field classification and size calibration model, a microscopy multi-classification model, and a mitigation quality inspection model. The automation and intelligence of the process flow is achieved by replacing the manual decision-making process with predictions from the model library. Based on the proposed framework, the working principle and workflow of the damage intelligent inspection system are explained, and the inspection efficiency and automation level of the system are evaluated in this paper. The intelligent inspection system framework proposed in this paper can provide technical support for future high-volume mitigation of large-aperture optics.

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Published
2024-11-20
DOI
https://doi.org/10.1117/12.3036079
Primary Topic
Advanced Measurement and Metrology Techniques
Type
article
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Intelligent inspection system framework for surface damage mitigation of large-aperture optics

Mingjun Chen, Tianhao Zhang, Zhaoyang Yin, Jian Ping Cheng et al.
Advanced Measurement and Metrology Techniques
article

Intelligent inspection system framework for surface damage mitigation of large-aperture optics

Mingjun Chen, Tianhao Zhang, Zhaoyang Yin, Jian Ping Cheng, Tianyuan Li, Linjie Zhao
article en

Abstract

Micron-level surface damages can seriously affect the optical and mechanical properties of large-aperture optics, so it is of great significance to perform high-precision inspection and mitigation of surface damages. Surface micro-damages are not only multi-category but also randomly distributed on the optics. Manual inspection and mitigation are not only time-consuming but also difficult to ensure the accuracy and reliability of mitigation, so it cannot meet the engineering requirements for large-volume mitigation of optics. In order to solve this problem, an intelligent inspection system framework for optics surface damage mitigation is proposed in this paper. The inspection system consists of an optics surface ranging fitting module, a dark-field rapid inspection module, and a multi-illumination micro-inspection module. Based on the above modules, a damage inspection process flow is established, including automatic alignment of optics surface, rapid dark-field inspection of flaws with large field of view, microscopic precision inspection of damages with small field of view, automatic configuration and execution of damage mitigation strategies, and quality control of mitigation structure. In order to realize the above flow, a predictive model library related to damage inspection is constructed, including: a dark field classification and size calibration model, a microscopy multi-classification model, and a mitigation quality inspection model. The automation and intelligence of the process flow is achieved by replacing the manual decision-making process with predictions from the model library. Based on the proposed framework, the working principle and workflow of the damage intelligent inspection system are explained, and the inspection efficiency and automation level of the system are evaluated in this paper. The intelligent inspection system framework proposed in this paper can provide technical support for future high-volume mitigation of large-aperture optics.

Harbin Institute of Technology (CN)
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Advanced Measurement and Metrology Techniques
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