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相关概念视频

Design Example: Joints in Concrete Pavements01:28

Design Example: Joints in Concrete Pavements

182
Concrete pavement joints are essential for maintaining the structural integrity and longevity of pavement by controlling where and how the pavement cracks. These joints can be categorized based on their functions, such as contraction or control joints, construction joints, isolation joints, and expansion joints.
Contraction joints are typically formed by sawing a groove into the concrete shortly after it has hardened. This creates a weakened vertical plane, deliberately encouraging cracking at...
182
Microcracking in Concrete01:20

Microcracking in Concrete

117
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...
117
Types of Non-structural Cracks in Concrete01:28

Types of Non-structural Cracks in Concrete

154
Non-structural cracks are primarily of three types: plastic, early-age thermal, and drying shrinkage cracks. Plastic cracks are further classified into plastic shrinkage cracks and plastic settlement cracks.
Plastic shrinkage cracks typically form within hours after the concrete is poured. The concrete's surface dries faster than the bottom, creating tensile stress that the still-plastic concrete cannot withstand, leading to diagonal or randomly patterned cracks on the concrete surface.
154
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

49
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
49
Creep in Concrete01:22

Creep in Concrete

230
Creep refers to the time-dependent increase in strain under a sustained load, excluding other time-dependent deformations associated with shrinkage, swelling, and thermal expansion in concrete. The primary mechanism behind creep involves the loss of physically adsorbed water from the calcium silicate hydrate within the hydrated cement paste. This process is further exacerbated by concrete's non-linear stress-strain relationship, microcrack development in the interfacial transition zone, and...
230
Masonry Paving01:21

Masonry Paving

256
The construction of masonry paving involves using materials such as bricks, stones, and concrete masonry units. These materials are chosen for their shape, color, strength, and resistance to abrasion and weathering. Masonry units can be installed dry on a thin layer of sand and a gravel base, or they can be embedded in mortar or asphalt on a concrete slab. For areas subjected to heavy vehicular loads, a rigid base layer of reinforced or unreinforced concrete is recommended. In contrast,...
256

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在复杂的环境下自动识别高速公路路面上的裂.

Zhihua Zhang1,2,3, Kun Yan1,2,3, Xinxiu Zhang1,2,3,4

  • 1Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, China.

Heliyon
|February 29, 2024
PubMed
概括

这项研究引入了ResNet34模型,配有卷积块注意模块 (CBAM),用于增强高速公路路面裂识别,提高各种裂类型的检测精度和回忆.

关键词:
卷积式的注意力模块注意力模块.高速公路路面上的裂是路面上的裂.认可 承认 认可剩余网络的残余网络

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科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 土木工程 土木工程是指土木工程.

背景情况:

  • 由各种因素造成的路面损坏需要有效的监测,以便及时修复.
  • 在复杂的环境中识别高速公路裂是由于干扰而具有挑战性的.
  • 计算机视觉为路面裂检测提供了有前途的解决方案.

研究的目的:

  • 开发和评估一种新的计算机视觉方法,用于高速公路路面上的裂识别.
  • 通过使用深度学习来提高路面裂检测的准确性和效率.
  • 评估与卷积块注意模块 (CBAM) 集成的ResNet34模型的性能.

主要方法:

  • 使用转移学习训练ResNet18,ResNet34和ResNet50模型.
  • 选择ResNet34作为基础模型,并集成了CBAM模块.
  • 进行了进一步的培训,并使用精度,平均回忆和类特定回忆来评估模型性能.

主要成果:

  • 带有CBAM集成的ResNet34模型显示了测试准确度和平均回忆率的提高.
  • 拟议的模型在性能指标方面表现优于其他评估的模型.
  • 在横向 (88.8%),纵向 (86.8%),地图裂 (88.5%),修复 (98.3%) 和路面标记 (99.9%) 方面实现了高回调率.
  • 达到最高精度92.9%和平均回忆率92.5%的最高精度.

结论:

  • 将CBAM集成到ResNet34中显著提高了路面裂识别能力.
  • 拟议的模型显示出高速公路维护应用的巨大潜力.
  • 需要进一步的研究,以解决检测网状裂纹的局限性.