Author(s)

Shengfang Li ¹, Hao Zhou ¹

Affiliation(s)

¹ Xihua University, Chengdu, Sichuan, 611730, China

Corresponding Author

Shengfang Li

ABSTRACT

Under the background of the vigorous development of the electronics industry, printed circuit boards, as one of the important components of the electronics industry, provide more support for the production and research and development of many electronic devices. Electrical interconnection of electronic devices requires printed circuit boards as the carrier, its appearance directly reduces the workload of connecting conductive lines, simplifies the wiring work, and its quality can directly affect the performance of electronic products, which makes the defect detection of printed circuit boards is crucial. The application of machine vision not only improves the efficiency and quality of inspection, but also brings new opportunities and challenges to related industries. In view of this, in order to study the key technology of PCB defect detection based on machine vision, this paper based on the generation of PCB defects, analyzed the working principle and calibration principle of the relevant system, and finally proposed the nine-point calibration method, and expounded the image processing method, hoping to provide reference for relevant people.

KEYWORDS

Machine Vision, Printed Circuit Board, Key Technology, Defect Detection, Basic Principle

CITE THIS PAPER

Shengfang Li, Hao Zhou, Analysis of Key Techniques of PCB Defect Detection Based on Machine Vision. Automation and Machine Learning (2024) Vol. 5: 97-103. DOI: http://dx.doi.org/10.23977/autml.2024.050112.

REFERENCES

[1] Xu Liqing. Design of Parts Surface defect detection System based on Machine vision. Shihezi Science and Technology, 2024, (02): 43-45.
[2] Yang Jiang, Sun Fucai, Zhao Peijiang, et al. Research on Key technologies of PCB defect Detection based on Machine vision. Journal of Heilongjiang Institute of Technology (General Edition), 2024, 24 (02): 110-115. (in Chinese)
[3] Wu Shaofeng, Baiyun Jiao. Key technology of Surface defect Detection based on Machine vision. Agricultural Technology and Equipment, 2023,(10): 66-69.
[4] Cao Heng. Application of Machine vision technology in PCB automatic inspection. Journal of Integrated Circuit Applications, 2022, 39 (12): 258-259.
[5] Li Sen, Wan Gang, Wei Ziyuan, et al. Application of 5G+AI machine vision technology in PCB industry. Information and Communication Technology, 2021, 15 (06): 56-60. (in Chinese)
[6] Wang Yuping, Guo Fenglin. Research on Key technologies of PCB Board defect detection system based on machine vision. Chinese Science and Technology Bulletin, 2017, 33 (01): 101-105.

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