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Microcracking in Concrete

Microcracking in Concrete

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...

Types of Non-structural Cracks in Concrete

Types of Non-structural Cracks in Concrete

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.

Structural Classification of Joints

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
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Design Example: Joints in Concrete Pavements

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Related Experiment Video

Updated: Sep 13, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Lightweight Dual-Attention Network for Concrete Crack Segmentation.

Min Feng^1,2, Juncai Xu^1,3

¹Anhui Provincial International Joint Research Center of Data Diagnosis and Smart Maintenance on Bridge Structures, Chuzhou 239099, China.

Sensors (Basel, Switzerland)

|July 30, 2025

Summary

This study introduces a lightweight dual-attention network for accurate crack segmentation on edge devices. The model achieves high performance with minimal computational cost, enabling real-time civil infrastructure inspection.

Keywords:

crack segmentation dual-attention network edge computing real-time inference structural health monitoring

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Area of Science:

Computer Vision
Artificial Intelligence
Civil Engineering

Background:

Structural health monitoring requires accurate crack segmentation on resource-constrained edge devices.
Existing models often exceed power, memory, and latency limits of these devices.

Purpose of the Study:

To develop a lightweight crack segmentation network for edge devices.
To achieve high accuracy comparable to heavyweight models within strict resource constraints.

Main Methods:

A compressed U-Net architecture (lightweight dual-attention network) was developed.
A compact dual-attention block combining channel and spatial self-attention was integrated.
The network was optimized for low power consumption and INT8 quantization.

Main Results:

The network achieved an Intersection over Union (IoU) of 0.827 and an F1 score of 0.905 on a concrete crack benchmark.
It outperformed existing lightweight models like MobileNetV3 and ESPNetv2.
Real-time performance was validated at 110 FPS on a Jetson Nano and 220 FPS on a Coral TPU.

Conclusions:

The lightweight dual-attention network provides cutting-edge crack segmentation for on-device civil infrastructure inspection.
The dual-attention module is key to the model's accuracy and efficiency.
The model meets the demands of real-time monitoring in resource-constrained environments.