Image recognition for defect screening of circuit board plug-in solder joints

Yufeng Luo; Li Shen

doi:10.1117/12.2667302

1 March 2023 Image recognition for defect screening of circuit board plug-in solder joints

Yufeng Luo, Li Shen

Proceedings Volume 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022); 1258802 (2023) https://doi.org/10.1117/12.2667302
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 2022, Chongqing, China

Abstract

For small and medium-sized electronic enterprises to produce plug-in circuit boards, due to the size of the enterprise, order requirements and other reasons, small and medium-sized electronic enterprises usually use manual visual inspection of plug-in circuit boards for inspection. Based on the Vision Developments Module of LabView software, we can detect the solder joint defects of plug-in circuit boards. According to the actual production of different types of circuit boards, the solder joints are classified, and then the representative qualified solder joints are extracted to make standard solder joint templates, which are matched with the images of the plug-in circuit boards to be tested through multiple template geometry matching to achieve automatic detection of solder joints with 93% detection accuracy.

Citation Download Citation

Yufeng Luo and Li Shen "Image recognition for defect screening of circuit board plug-in solder joints", Proc. SPIE 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 1258802 (1 March 2023); https://doi.org/10.1117/12.2667302

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