Related Concept Videos
01:20Microcracking in Concrete
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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...
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01:28Types of Non-structural Cracks in Concrete
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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.
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.
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01:22Creep in Concrete
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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...
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01:29Preplaced Aggregate Concrete
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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...
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01:12Bonding and Strength of Aggregate
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The bond between aggregate particles and the cement matrix is significantly influenced by the shape and surface texture of the aggregates. High-strength concretes benefit from a rougher texture, which leads to stronger bonding due to greater adhesion. Angular aggregates with larger surface areas also enhance this bond. The bonding quality, however, is complex to assess as no universally accepted test exists. Good bonding is indicated when a crushed concrete specimen shows some aggregate...
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01:25Effects of Creep
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Creep in concrete, the gradual deformation under prolonged stress, significantly impacts the integrity of structures. For reinforced concrete beams, it can be a vital design consideration, as it increases deflection, sometimes necessitating additional design measures. In columns, especially slender ones under eccentric loads, creep can cause buckling, compromising their stability. However, creep can be beneficial in indeterminate structures by mitigating stresses that arise from shrinkage,...
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A Multi-Stage Feature Aggregation and Structure Awareness Network for Concrete Bridge Crack Detection.
Erhu Zhang1, Tao Jiang1, Jinghong Duan2
1Department of Information Science, Xi'an University of Technology, Xi'an 710048, China.
Sensors (Basel, Switzerland)
|March 13, 2024
Summary
A new network, MFSA-Net, effectively detects concrete bridge cracks by combining square and strip convolutions to capture linear structures and long-range dependencies. This method improves precision and recall for critical infrastructure safety.
Area of Science:
- Civil Engineering
- Computer Vision
- Artificial Intelligence
Background:
- Concrete bridge cracks pose significant safety risks.
- Existing detection methods struggle with crack characteristics like slenderness, low contrast, and background noise.
- Conventional convolutional methods lack the ability to capture long-range dependencies and effectively suppress background interference.
Purpose of the Study:
- To propose a novel network, MFSA-Net, for accurate pixel-level concrete bridge crack detection.
- To enhance the perception of linear crack structures and long-range dependencies.
- To improve the precision and robustness of crack detection systems.
Main Methods:
- Developed a multi-stage feature aggregation and structure awareness network (MFSA-Net).
- Introduced a structure-aware convolution block combining square and strip convolutions.
- Implemented a feature attention fusion block for edge sharpening and feature fusion.
- Aggregated features from different stages for fine-grained segmentation.
Main Results:
- MFSA-Net achieved average precision of 73.74%, recall of 77.04%, F1 score of 75.30%, and IoU of 60.48% on a concrete bridge crack dataset.
- Demonstrated superior performance compared to existing methods.
- Showcased adaptability and optimal performance on concrete pavement crack datasets.
Conclusions:
- MFSA-Net effectively addresses the challenges in concrete bridge crack detection.
- The proposed network architecture enhances the ability to perceive linear structures and long-range dependencies.
- MFSA-Net demonstrates significant potential for crack detection in diverse infrastructure scenarios.