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Related Concept Videos

Design Example: Joints in Concrete Pavements01:28

Design Example: Joints in Concrete Pavements

219
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...
219
Microcracking in Concrete01:20

Microcracking in Concrete

151
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...
151
Types of Non-structural Cracks in Concrete01:28

Types of Non-structural Cracks in Concrete

191
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.
191
Preplaced Aggregate Concrete01:29

Preplaced Aggregate Concrete

116
Preplaced aggregate concrete is ideal for construction environments that are not easily accessible. The process begins by properly wetting the gap-graded coarse aggregates to remove the dirt, then placing it in the form and compacting it. Voids are filled with a mortar mix pumped under pressure through slotted pipes. This mortar typically consists of Portland cement, pozzolan, fine aggregates, water, and a fluidizing aid. The pozzolan helps reduce bleeding and segregation while improving the...
116
Non-destructive Tests for Concrete Strength01:12

Non-destructive Tests for Concrete Strength

147
The rebound hammer test, also known as the Schmidt hammer test, is a non-destructive technique for evaluating the hardness of concrete and, indirectly, the strength of concrete. It operates on the principle that the rebound of a spring-driven mass from a concrete surface correlates to the surface's hardness. The device comprises a mass within a tubular housing, a spring mechanism, and a plunger that strikes the concrete. Upon release, the energy imparted to the mass by the spring causes it...
147
Masonry Paving01:21

Masonry Paving

273
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,...
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Related Experiment Video

Updated: Jul 23, 2025

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
00:05

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Pavement crack detection based on point cloud data and data fusion.

Qiao Dong1, Sike Wang1, Xueqin Chen2

  • 1Department of Roadway Engineering, School of Transportation, Southeast University, Nanjing 211189, People's Republic of China.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|July 16, 2023
PubMed
Summary
This summary is machine-generated.

Researchers developed two AI methods for detecting pavement cracks in 3D point cloud data. One uses an improved sliding window algorithm with RANSAC for extraction, while the other employs YOLOv5 for detection from transformed images.

Keywords:
Yolov5asphalt pavementcrack detectiondeep learningpoint cloud

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Area of Science:

  • Civil Engineering
  • Computer Vision
  • Artificial Intelligence

Background:

  • Pavement crack detection is crucial for infrastructure maintenance.
  • Accurate identification and characterization of cracks are key challenges.
  • 3D point cloud data offers rich information for pavement analysis.

Purpose of the Study:

  • To develop and evaluate novel methods for 3D pavement crack detection using point cloud data.
  • To extract crack information including location and size.
  • To advance artificial intelligence applications in transportation infrastructure analysis.

Main Methods:

  • Developed an improved sliding window algorithm combined with Random Sample Consensus (RANSAC) for direct crack extraction from point clouds.
  • Implemented a YOLOv5-based deep learning model for automatic pavement crack detection using 2D images transformed from point cloud data.
  • Investigated fusing point cloud images with greyscale images as input for YOLOv5.

Main Results:

  • The improved sliding window algorithm effectively extracts pavement cracks with reduced noise.
  • The YOLOv5-based method demonstrates good performance in automatic pavement crack detection.
  • Fusion of image types showed potential for enhanced detection accuracy.

Conclusions:

  • Both developed methods show promise for 3D pavement crack analysis.
  • AI-driven approaches offer efficient and accurate solutions for pavement health monitoring.
  • This research contributes to the field of artificial intelligence in transportation infrastructure failure analysis.