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相关概念视频

Corrosion02:49

Corrosion

24.0K
The degradation of metals due to natural electrochemical processes is known as corrosion. Rust formation on iron, tarnishing of silver, and the blue-green patina that develops on copper are examples of corrosion. Corrosion involves the oxidation of metals. Sometimes it is protective, such as the oxidation of copper or aluminum, wherein a protective layer of metal oxide or its derivatives forms on the surface, protecting the underlying metal from further oxidation. In other cases, corrosion is...
24.0K

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相关实验视频

Updated: Jun 23, 2025

Applicability Analysis of Assessment Methods for Morphological Parameters of Corroded Steel Bars
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Applicability Analysis of Assessment Methods for Morphological Parameters of Corroded Steel Bars

Published on: November 1, 2018

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在钢结构中基于图像的自主腐蚀检测,使用深度学习.

Amrita Das1, Sattar Dorafshan1, Naima Kaabouch2

  • 1Department of Civil Engineering, College of Engineering & Mines, University of North Dakota, Grand Forks, ND 58202, USA.

Sensors (Basel, Switzerland)
|June 19, 2024
PubMed
概括
此摘要是机器生成的。

这项研究使用神经网络自动检测钢铁腐蚀. EfficientNetB7实现了98.5%的准确性,在识别腐蚀的像素和结构完整性方面的表现优于其他模型.

关键词:
人工智能的人工智能是人工智能.腐蚀腐蚀是一种腐蚀.语义细分 语义细分 语义细分 语义细分钢结构结构的钢结构是什么转移学习转移学习

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Experimental Protocol to Determine the Chloride Threshold Value for Corrosion in Samples Taken from Reinforced Concrete Structures
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相关实验视频

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算机视觉 计算机视觉
  • 结构工程 结构工程

背景情况:

  • 钢结构面临环境腐蚀,造成结构故障的风险.
  • 目前的非破坏性测试方法需要手动检查,并且可以忽略隐藏的缺陷.
  • 自主腐蚀检测对于主动维护和安全至关重要.

研究的目的:

  • 评估不同的编码器-解码器神经网络架构,用于自动化腐蚀细分.
  • 确定最佳的培训策略,以准确检测钢结构中腐蚀的像素.
  • 为了比较各种深度学习模型在从视觉图像中识别腐蚀的性能.

主要方法:

  • 研究了使用DenseNet121,EfficientNetB7,ResNet34和UNet骨干的编码器解码器神经网络.
  • 对比转移学习与在细分的腐蚀像素上的完整培训策略.
  • 在不同的数据集上使用像素级准确度,真正值和假正值率评估模型性能.

主要成果:

  • EfficientNetB7实现了最高的平均像素级精度,达到98.5%.
  • ResNet34表现出比原来的UNet更好的性能,特别是在各种腐蚀类型和颜色的外部数据集上.
  • 转移学习被证明比深度网络的全面培训更有效,特别是在较小的数据集.

结论:

  • 深度学习模型,特别是EfficientNetB7和ResNet34,显示出对自主钢铁腐蚀检测的重大前景.
  • ResNet34提供了一个强大而准确的解决方案,用于在各种现实场景中识别腐蚀.
  • 优化的培训策略和网络架构是提高自动结构健康监测可靠性的关键.