Review on Damage Identification and Health Monitoring of Steel Structures Based on Computer Vision

LU Peng; ZHAO Tiansong; WANG Jian; ZHAO Lei; CHANG Haosong; ZHENG Yun

doi:10.13204/j.gyjzG22071401

Volume 52 Issue 10

Oct. 2022

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CHEN Tao, JIN Chenhua, ZHANG Ke, DIAO Zhiwei, WU Chang, MENG Shaoping. Calculation of Effective Axial Stiffness of Cracked Reinforced Concrete Tension-Flexure Members Under Temperature Reduction[J]. INDUSTRIAL CONSTRUCTION, 2023, 53(6): 100-104,74. doi: 10.13204/j.gyjzG21120701

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LU Peng, ZHAO Tiansong, WANG Jian, ZHAO Lei, CHANG Haosong, ZHENG Yun. Review on Damage Identification and Health Monitoring of Steel Structures Based on Computer Vision[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(10): 22-27. doi: 10.13204/j.gyjzG22071401

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Review on Damage Identification and Health Monitoring of Steel Structures Based on Computer Vision

doi: 10.13204/j.gyjzG22071401

1. Inspection and Certification Co., Ltd., MCC, Beijing 100088, China;
2. Tianjin Chengjian University, Tianjin 300384, China;
3. 96854 Troops of PLA, Shenyang 110033, China;
4. Central Research Institute of Building and Construction Co., Ltd., MCC Group, Beijing 100088, China

Received Date: 2022-07-14
Available Online: 2023-03-22

Abstract

Abstract

Steel structures suffer from surface damage all the time due to their material properties and insufficient daily management. With the development of digital information technology, computer vision techniques have become key means in damage identification and health monitoring of steel structures. This paper presented the advances of computer vision techniques in damage and health monitoring of steel structures and discussed the identification techniques for surface corrosion damage, weld joint damage, and bolt connection damage of steel structures and their health monitoring. Moreover, it also predicted the development trends of damage identification and health monitoring techniques based on computer vision for steel structures.
- steel structure damage,
- damage identification,
- computer vision,
- health monitoring,
- carrying platform

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References(36)

References

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