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Experimental Research on MFL Detection Technology for Corrosion Damage of Prestressing Tendons in Bridges National Key Laboratory for Bridge Engineering Safety and Re

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Wang, Peng, author.
Contributor:
Dong, Lei
Gao, Min
Zhu, Junliang
Conference Name:
2025 8th International Conference on Traffic Transportation and Civil Architecture (ICTTCA 2025) (2025-04-18 : Tianjin, China)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2025
Summary:
Corrosion of prestressed tendons endangers the safety of bridges, but until now, there has been no effective method to solve the problem of detecting corrosion damage in prestressed tendons of concrete beams. To address this, a magnetic flux leakage detection experimental apparatus for corrosion damage in prestressed tendons based on the principle of magnetic flux leakage inspection has been developed. Using this apparatus, magnetic flux leakage tests were conducted on prestressed tendons after electrochemical corrosion, and the results were compared with simulation analysis to conduct a comparative study. In the experiments, the influence of corrosion severity, corrosion width, and the effect of stirrups on the characteristics of the magnetic flux leakage signals were studied. Magnetic signal feature values were extracted, and a quantification neural network model for corrosion damage was established, which is used to quantify the degree of corrosion damage in prestressed tendons. The research results show that the model can predict corrosion rates with an accuracy of 93.58% and predict corrosion widths with an accuracy of 90.30%. This method effectively reduces the influence of external factors on the determination of corrosion rates and widths in prestressed tendons during experimental analysis, thereby improving the precision of quantifying corrosion damage identification in prestressed tendons
Notes:
Vendor supplied data
Publisher Number:
2025-99-0203
Access Restriction:
Restricted for use by site license

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