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振动导致钢绞线腐蚀的漏磁检测实验分析

Experimental Analysis of the Magnetic Leakage Detection of a Corroded Steel Strand Due to Vibration.

作者信息

Zhang Hong, Ding Yaxi, Yuan Ye, Xia Runchuan, Zhou Jianting

机构信息

State Key Laboratory of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing 400074, China.

School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China.

出版信息

Sensors (Basel). 2023 Aug 11;23(16):7130. doi: 10.3390/s23167130.

DOI:10.3390/s23167130
PMID:37631669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10459005/
Abstract

The self-magnetic flux leakage (SMFL) detection technique has great potential in the corrosion detection of bridge stay cables due to its advantages of small testing equipment, high accuracy, and fast testing rate. However, the vibration effect in the cable's SMFL detection is unclear. To address this, the influence of vibration on the magnetic field distribution of cable structure is analyzed theoretically. According to the theoretical model, the effect of vibration on SMFL detection primarily manifests as displacement changes (displacement-added magnetic field) and defect shape changes (deformation-added magnetic field). SMFL detection experiments are conducted on steel strands. The results demonstrate that the displacement-added magnetic field exhibits statistical characteristics in the form of a normal distribution, fluctuating around the zero value. The impact of the deformation-added magnetic field on SMFL is linearly correlated with the corrosion ratio Moreover, a corrosion characterization index was proposed and has an excellent linear fit with the corrosion ratio . The index effectively improves the accuracy of corrosion detection and provides early warning for the maintenance of cable structures.

摘要

自漏磁检测技术因其检测设备体积小、精度高、检测速度快等优点，在桥梁拉索腐蚀检测中具有很大潜力。然而，电缆自漏磁检测中的振动影响尚不清楚。为解决这一问题，从理论上分析了振动对电缆结构磁场分布的影响。根据理论模型，振动对自漏磁检测的影响主要表现为位移变化（附加位移磁场）和缺陷形状变化（附加变形磁场）。对钢绞线进行了自漏磁检测实验。结果表明，附加位移磁场呈正态分布形式的统计特征，围绕零值波动。附加变形磁场对自漏磁的影响与腐蚀率呈线性相关。此外，提出了一种腐蚀表征指标，与腐蚀率具有良好的线性拟合。该指标有效提高了腐蚀检测的准确性，为电缆结构维护提供了预警。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/848b/10459005/f3f2c8e88552/sensors-23-07130-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/848b/10459005/a1228fb10e5f/sensors-23-07130-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/848b/10459005/6bcb5a8bc346/sensors-23-07130-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/848b/10459005/23dcce7c464b/sensors-23-07130-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/848b/10459005/8a0880f345f1/sensors-23-07130-g014.jpg
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本文引用的文献

1
Research on the Method of Predicting Corrosion width of Cables Based on the Spontaneous Magnetic Flux Leakage.基于自发漏磁场的电缆腐蚀宽度预测方法研究
Materials (Basel). 2019 Jul 4;12(13):2154. doi: 10.3390/ma12132154.
2
Experimental Study on Residual Bending Strength of Corroded Reinforced Concrete Beam Based on Micromagnetic Sensor.基于微磁传感器的锈蚀钢筋混凝土梁残余抗弯强度的试验研究。
Sensors (Basel). 2018 Aug 11;18(8):2635. doi: 10.3390/s18082635.
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Quantitative Study on Corrosion of Steel Strands Based on Self-Magnetic Flux Leakage.
基于自磁漏的钢绞线腐蚀定量研究。
Sensors (Basel). 2018 May 2;18(5):1396. doi: 10.3390/s18051396.
4
The Non-Destructive Test of Steel Corrosion in Reinforced Concrete Bridges Using a Micro-Magnetic Sensor.基于微磁传感器的钢筋混凝土桥梁中钢材腐蚀的无损检测
Sensors (Basel). 2016 Sep 6;16(9):1439. doi: 10.3390/s16091439.
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Defect profile estimation from magnetic flux leakage signal via efficient managing particle swarm optimization.基于高效管理粒子群优化算法的漏磁信号缺陷轮廓估计
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