Research on the Corrosion Detection of Rebar in Reinforced Concrete Based on SMFL Technology

被引:0
|
作者
Tian, Hongsong [1 ]
Kong, Yujiang [1 ]
Liu, Bin [1 ]
Ouyang, Bin [1 ]
He, Zhenfeng [2 ,3 ]
Liao, Leng [2 ,3 ]
机构
[1] Guizhou Bridge Construction Grp Co Ltd, Guiyang 550001, Peoples R China
[2] Chongqing Jiaotong Univ, State Key Lab Mt Bridge & Tunnel Engn, Chongqing 400074, Peoples R China
[3] Chongqing Jiaotong Univ, Sch Civil Engn, Chongqing 400074, Peoples R China
基金
中国国家自然科学基金;
关键词
rebar corrosion; reinforced concrete; SMFL technology; influence factors; prediction model; XGBoost; STRENGTH; XGBOOST; MODEL;
D O I
10.3390/ma17143421
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The corrosion damage of rebars is a leading cause of structural failure in reinforced concrete structures. Timely detection and evaluation of corrosion damage are crucial for ensuring structural safety. The self-magnetic flux leakage (SMFL) technology is often used due to its unique advantages in detecting corrosion damage of rebars. However, challenges persist in theoretically characterizing corrosion damage and exploring influencing factors. Therefore, the magnetic dipole theory model coupled with multiple-shaped defects is proposed and the influence of corrosion expansion force on the detection of corrosion damage is analyzed. The results show that the standard deviation of the magnetic field intensity induced by corrosion varied by up to 833%, while that induced by corrosion expansion force did not exceed 10%. So the changes in the SMFL field induced by corrosion damage play the dominant role and the influence of corrosion expansion force can be ignored. In addition, corrosion damage experiments on reinforced concrete based on the SMFL technology were conducted. The results indicate that the SFML curves of rebars change monotonically with the increasing corrosion degree. Significant variations in the curves correspond well with the locations of severe corrosion on the rebars. There is a positive relationship between the proposed magnetic parameters and the corrosion degree of the rebars. Furthermore, a corrosion damage evaluation model considering multiple parameters is developed to predict the corrosion degree of rebars. The prediction results demonstrate high accuracy, with an average absolute error of only 8.33%, which is within 10%.
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页数:22
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