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相关实验视频

Updated: Jun 27, 2026

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses
07:26

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses

Published on: December 5, 2019

集成自动光学检查和图像处理程序用于生产线中的智能传感.

Rong-Qing Qiu1, Mu-Lin Tsai2, Yu-Wen Chen1

  • 1Institute of NanoEngineering and MicroSystems, National Tsing Hua University, Hsinchu 300044, Taiwan.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
概括

为印刷电路板 (PCB) 制造开发了一种新的集成自动光学检查 (iAOI) 系统和程序. 该系统提供高效,明确的模式质量判断,有助于在生产过程中检测缺陷.

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科学领域:

  • 电气工程 电气工程
  • 材料科学 材料科学 材料科学
  • 计算机视觉 计算机视觉

背景情况:

  • 印刷电路板 (PCB) 制造容易发生工艺变化,导致模式扭曲.
  • 确保PCB的图案质量和性能一致性对于电子设备的可靠性至关重要.
  • 现有的检查方法可能缺乏标准化和有效处理工艺引起的缺陷.

研究的目的:

  • 为PCB生产线提出一个集成的自动光学检查 (iAOI) 系统和程序.
  • 提高PCB制造中的缺陷检测和模式质量评估能力.
  • 为识别模式扭曲和性能偏差提供统一有效的解决方案.

主要方法:

  • 开发一个iAOI系统模块与摄像头和镜头,支持商业硬件.
  • 实现连续工作流程,包括图像注册,值设置,图像梯度,标记器对齐和几何转换.
  • 创建一个用户友好的图形用户界面 (GUI),用于显示图像处理结果和分析的特征.

主要成果:

  • iAOI系统证明了对商业硬件的支持性有所改善.
  • 拟议的程序允许高效和标准化的图像处理操作.
  • 使用自补的阿基米德螺旋天线 (SCASA) 样本与故意扭曲来验证有效性.
关键词:
自动光学检查自动光学检查图像处理是图像处理的过程.线边的粗度 线边的粗度机器学习是机器学习.印刷电路板的使用情况螺旋天线 螺旋天线

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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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相关实验视频

Last Updated: Jun 27, 2026

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses
07:26

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses

Published on: December 5, 2019

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
05:57

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Published on: April 1, 2020

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

  • 该系统提供了科学和明确的模式质量判断,优于现有方法.

    • 结论:

    • 开发的IAOI系统和程序为PCB质量检查提供了一种高效和标准化的方法.
    • 该系统促进对模式质量的明确判断,这对于识别过程变异至关重要.
    • 未来与人工智能模型的整合可以通过GUI实现SCASA等组件的电磁特征投影.