Review of bridge crack detection based on digital image technology

被引：0
作者：
Yang G.-J. [1 ,2 ]
Qi Y.-H. [1 ]
Shi X.-M. [1 ]
机构：
[1] School of Civil Engineering, Lanzhou University of Technology, Lanzhou
[2] State Key Laboratory of Bridge Engineering Structural Dynamic, China Merchants Chongqing Communications Technology Research and Design Institute Co., Ltd., Chongqing
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2024年 / 54卷 / 02期
关键词：
bridge engineering; convolutional neural network; crack identification; deep learning; image processing; intelligent detection;
D O I：
10.13229/j.cnki.jdxbgxb.20221475
中图分类号：
学科分类号：
摘要：
As one of the important contents of bridge health detection, crack detection reflects the stress and damage state of bridge structure. The traditional bridge crack detection is mainly based on human eye recognition, of which efficiency and accuracy are both low. Moreover, the human eye recognition has the following problems such as effected greatly by illumination, incapability to detect in some high-altitude positions like bridge towers and high piers and strong subjectivity. In recent years, many scholars at home and abroad have developed many bridges crack detection equipment based on digital image technology to solve the above problems, such as bridge detection vehicles equipped with high-definition cameras, drones, and climbing robots. Meanwhile, the efficient and high-precision crack detection algorithm is the basis of crack detection. How to balance the detection speed and accuracy has always been one of the hot issues studied by many scholars. In this paper, the bridge crack detection equipment based on digital image technology, the platform and calibration method of camera, preprocessing algorithm, traditional detection algorithm, deep learning algorithm, crack feature calculation, image stitching algorithm and three-dimensional output and monitoring of cracks are reviewed. In addition, summaries to deficiencies in the study and prospects the bridge crack detection method, crack three-dimensional expression, crack monitoring and management, bridge stiffness loss evaluation and early warning for the future development trend. © 2024 Editorial Board of Jilin University. All rights reserved.
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页码：313 / 332
页数：19
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