基于深度学习的PCB微焊接状态检测系统研究

Proceedings of the 2022 5th Artificial Intelligence and Cloud Computing Conference Pub Date : 2022-12-17 DOI:10.1145/3582099.3582104

J. Shim, Y. Ha, JiHee Park, Yeung-hak Lee

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引用次数: 0

摘要

在半导体工艺中，焊接状态是重要的工艺之一。这个错误可能是对其他电子元件造成致命影响的主要原因之一。到目前为止，所有的焊接状态都是由人工检查的。这会导致许多误报错误。本研究利用人工智能进行了微焊接状态检测，该检测具有一级和二级复合缩放。实验结果表明，pcb焊接状态检测在一级检测器(YOLOv5)中显示出与其他物体不同的低误报。

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PCB Micro-Soldering Status Inspection System Research based on Deep Learning

In the semiconductor process, the soldering state is one of the important processes. This error can be one of the main causes of fatal effects on other electronic components. Until now, all soldering status have been inspected by humans. This causes many false positive errors. This study experimented with micro-soldering status inspection using artificial intelligence which has 1-stage and 2-stage compound scaling. As a result of the experiment, PCB-soldering condition inspection showed low false positives in 1-stage detector (YOLOv5) unlike other objects.

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Proceedings of the 2022 5th Artificial Intelligence and Cloud Computing Conference

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