An automatic search and alignment method for crystal's self-alignment based on machine learning on high power laser facility

Yaohan Kang; Daizhong Liu; Xiuqing Jiang; Lei Gong

doi:10.1117/12.3047827

13 December 2024 An automatic search and alignment method for crystal's self-alignment based on machine learning on high power laser facility

Yaohan Kang, Daizhong Liu, Xiuqing Jiang, Lei Gong

Author Affiliations +

Proceedings Volume 13492, AOPC 2024: Laser Technology and Applications; 1349213 (2024) https://doi.org/10.1117/12.3047827
Event: Applied Optics and Photonics China 2024 (AOPC2024), 2024, Beijing, China

Abstract

The process of online crystal alignment in high-power laser facilities is both challenging and labor-intensive. We propose an automated method for self-alignment of crystals on these facilities, utilizing machine learning. This method employs a machine learning algorithm running on a Raspberry Pi to automatically locate the reflective spot from the crystal's back surface and adjust its position to achieve self-alignment. The proposed scheme comprises two modules: a rectangular spiral spot scanning search method module and an automatic spot aligning method module based on the open-source machine learning algorithm M-LOOP. Initially, the rectangular spiral spot scanning search method is used to position the laser spot within the field of view of the CCD camera. The M-LOOP algorithm then automatically adjusts the laser spot to align with the reference center. The hardware system includes a crystal alignment optical system, motors, a CCD camera, and a Raspberry Pi. Offline experiments have demonstrated that this method can accomplish the automatic search and alignment of the crystal return spot of a He-Ne laser in approximately 10 minutes. This solution addresses the issue of traditional technology requiring manual search and adjustment of the crystal's reflection spot for self-alignment.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yaohan Kang, Daizhong Liu, Xiuqing Jiang, and Lei Gong "An automatic search and alignment method for crystal's self-alignment based on machine learning on high power laser facility", Proc. SPIE 13492, AOPC 2024: Laser Technology and Applications, 1349213 (13 December 2024); https://doi.org/10.1117/12.3047827

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KEYWORDS

Crystals

Laser crystals

Machine learning

Automatic alignment

CCD cameras

High power lasers

Charge-coupled devices

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