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相关实验视频

Updated: Jul 26, 2025

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
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通过主动温度学数据处理算法的三维打印地表缺陷检测.

Ézio Carvalho de Santana1, Wellington Francisco da Silva1, Marcella Grosso Lima2

  • 1Mechanical Engineering Department, Federal University of Sergipe, Sergipe, Brazil.

3D printing and additive manufacturing
|June 22, 2023
PubMed
概括

这项研究引入了一种先进的活性热像算法,用于检测增材制造 (AM) 材料中的地下缺陷. 与现有技术相比,新方法提供了优越的缺陷可视化和灵敏度.

关键词:
活动热图学 活动热图学添加剂制造 添加剂制造 添加剂制造算法算法是一种算法.图像处理是图像处理的过程.在地底的地下,地表的地下.热分析是一种热分析.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 非破坏性测试 不破坏性测试
  • 热分析 热分析

背景情况:

  • 增材制造 (AM) 可以实现复杂的几何形状,但可以引入地下缺陷.
  • 检测这些缺陷对于确保材料完整性和性能至关重要.
  • 现有的方法,如热图信号重建 (TSR),在灵敏度和图像清晰度方面存在局限性.

研究的目的:

  • 评估一种用于检测AM材料的地下缺陷的新型活性热像算法.
  • 将拟议的算法的性能与最先进的TSR技术进行比较.
  • 为了提高缺陷检测的可视化和灵敏度.

主要方法:

  • 该算法集成了热图信号重建 (TSR),热对比和热传递的原理.
  • 它分析了不同填充,深度和大小的地下缺陷.
  • 图像处理利用绝对差异而不是差异来提高清晰度.

主要成果:

  • 拟议的算法在检测3D打印材料中的地下缺陷方面表现出高性能.
  • 与传统的TSR相比,它实现了更高的对比度和更好的缺陷深度灵敏度.
  • 由此产生的热图像更清洁,噪音降低,清楚地表明缺陷位置.

结论:

  • 开发的主动热像算法为AM中地下缺陷检测提供了显著的改进.
  • 其增强的对比度,灵敏度和降低的噪音提供了更可靠的缺陷识别.
  • 这种方法对添加剂制造工艺的质量控制具有前景.