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相关概念视频

Microcracking in Concrete01:20

Microcracking in Concrete

93
Microcracking in concrete refers to the tiny cracks that can form within the material even before any external load is applied. These microcracks typically occur at the interface between the coarse aggregate and the hydrated cement paste, often as a result of differential volume changes prompted by variations in stress-strain behavior, as well as thermal and moisture movement. Initially, these microcracks remain stable and do not grow substantially until the concrete is stressed to about 30...
93

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相关实验视频

Updated: May 17, 2025

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
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路面裂识别方法基于IOtsu-Dd算法.

Yang Yang1, Lin Wang2, Qinghua Xiong1

  • 1School of Road and Bridge Engineering, Guangxi Transport Vocational and Technical College, Nanning, China.

PloS one
|May 14, 2025
PubMed
概括

本研究介绍了一种改进的Otsu方法,用于使用无人机 (UAV) 图像进行高速公路自动裂识别. 开发的方法显著提高了确定道路裂的准确性和效率,以更好地维护高速公路.

科学领域:

  • 土木工程 土木工程是指土木工程.
  • 计算机视觉 计算机视觉
  • 图像处理 图像处理

背景情况:

  • 高速公路的维护依赖于及时识别道路裂.
  • 无人驾驶飞行器 (UAV) 越来越多地用于道路表面成像.
  • 从无人机图像中自动识别裂是一个活跃的研究领域.

研究的目的:

  • 利用无人机图像开发一种准确有效的道路裂识别方法.
  • 改进现有的基于Otsu的分段技术,用于路面裂纹检测.
  • 使用损坏密度构建路面裂识别模型.

主要方法:

  • 无人机图像的预处理,包括灰度转换和均等.
  • 使用改进的Otsu方法进行图像细分,以增强裂检测.
  • 开发一种包含损坏密度的路面裂识别模型.

主要成果:

  • 开发的方法在裂识别方面实现了98.2%的平均准确性.
  • 该模型的召回率为0.75,F1得分为0.85.
  • 拟议的方法有效地从无人机图像中提取和识别路面裂纹特征.

结论:

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  • 改进的Otsu方法为道路裂识别提供了高效率和准确性.
  • 这种方法为使用无人机技术的自动化公路维护提供了强大的解决方案.
  • 该方法成功地识别了无人驾驶飞行器捕获的图像中的路面裂.