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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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基于机器视觉的钢骨架尺寸的自动检测系统.

Huaxue Jin1, Wei Fan1, Xiaoya Chen1

  • 1School of Mechanical and Electrical Engineering and Automation, Huaqiao University, Xiamen 361021, China.

The Review of scientific instruments
|March 21, 2024
PubMed
概括

这项研究引入了一种使用机器视觉测量混凝土板的钢骨架尺寸的自动化系统,从而避免了昂贵的施工错误. 该系统确保了精确的尺寸,提高了效率,减少了预制板生产中的浪费.

科学领域:

  • 建筑工程工程 建筑工程
  • 制造业 制造技术 制造技术
  • 计算机视觉 计算机视觉

背景情况:

  • 传统建筑依赖于手工测量预制混凝土板的钢骨架,由于尺寸错误而面临大量材料浪费的风险.
  • 在混凝土倒后检测到的不准确的钢架尺寸需要废弃整个预制板块,导致巨大的经济损失.
  • 目前的方法缺乏自动化质量控制,以确保混凝土造前精确的骨架尺寸.

研究的目的:

  • 开发和验证一个自动化系统,用于精确测量钢骨架框架尺寸的钢筋混凝土预制板.
  • 实施一种能够检测钢架尺寸差异的机器视觉系统,防止昂贵的施工错误.
  • 为预制混凝土元件的生产提供可靠的,自动化的质量保证解决方案.

主要方法:

  • 使用 LabVIEW 软件与 NI Vision 库集成,用于机器视觉功能.
  • 使用电荷合装置 (CCD) 摄像头捕捉钢骨架的整体图像.
  • 实现图像处理算法来提取特征,测量尺寸,并将它们与设计规格进行比较.

主要成果:

  • 自动化系统准确测量钢骨架尺寸,将其与设计规格进行比较,警告值为0.5厘米.
  • 实验验证显示,最大测量误差为2.7%,根平均平方误差为0.66%.

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  • 该系统成功地满足了现场施工应用的准确性要求.

    • 结论:

    • 拟议的自动化机器视觉系统为预制混凝土板生产中精确检测钢骨架尺寸提供了可行的解决方案.
    • 这项技术显著降低了材料浪费的风险,并通过早期检测错误来提高施工效率.
    • 该系统作为一个有价值的科学参考,用于推进预制混凝土行业的自动化质量控制.