Machine learning-based high-precision and real-time focus detection for laser material processing systems

Date
2022-05-17
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Source Title
SPIE - International Society for Optical Engineering. Proceedings
Print ISSN
0277-786X
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S P I E - International Society for Optical Engineering
Volume
12138
Issue
Pages
1 - 7
Language
English
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Abstract

This work explores a real-time and high precision focus finding for the ultrafast laser material processing for a different types of materials. Focus detection is essential for laser machining because an unfocused beam cannot affect the material and, at worst, a destructive effect. Here, we compare CNN and non-CNN-based approaches to focus detection, ultimately proposing a robust CNN model that can achieve high performance when only trained on a portion of the dataset. We use an ordinary lens (11 mm focal length, 0.25 NA) and a CMOS camera. Our robust CNN model achieved a focus prediction accuracy of 95% when identifying focus distances in -150, -140,...,0,...,150 µm, each step is about 7% of the Rayleigh length, and a high processing speed of 1000+ Hz on a CPU.

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