Research on optical microstructure machining based on artificial intelligence

Jianwen Zhang

doi:10.1117/12.2659643

30 November 2022 Research on optical microstructure machining based on artificial intelligence

Jianwen Zhang

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 124560D (2022) https://doi.org/10.1117/12.2659643
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

As an important part of today's optoelectronic products, optical microstructure components are bound to restrict their development if they are still processed by traditional methods. Therefore, in order to promote the development of optical microstructure components, artificial intelligence technology is applied to make up for the insufficiency of manual processing methods and promote the development of optical microstructures in aerospace, information and other fields. Specifically, in the context of artificial intelligence, a single-point diamond is used to conduct machining experiments on micro-V grooves to explore the influence of spindle speed, depth of cut and feed speed on the machining accuracy of micro-V grooves, and to select appropriate cutting parameters. Finally, using these cutting parameters, the micro-V groove workpiece is processed, and it is found that the workpiece has the following characteristics: smooth surface, clear structure, clear array, etc. It has good consistency and can meet the requirements of optical microstructure machining accuracy. It can be seen that artificial intelligence can promote the development of optical microstructure processing and has a positive role in practice.

Citation Download Citation

Jianwen Zhang "Research on optical microstructure machining based on artificial intelligence", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 124560D (30 November 2022); https://doi.org/10.1117/12.2659643

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