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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。

Experimental Study on Residual Bending Strength of Corroded Reinforced Concrete Beam Based on Micromagnetic Sensor.

机构信息

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

Yunnan Wuyi Expressway Construction Command, Kunming 650000, China.

出版信息

Sensors (Basel). 2018 Aug 11;18(8):2635. doi: 10.3390/s18082635.

DOI:10.3390/s18082635
PMID:30103500
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6111848/
Abstract

This paper presents a nondestructive test method to evaluate the residual bending strength of corroded reinforced concrete beam by analyzing the self-magnetic flux leakage (SMFL) signals. The automatic scanning device was equipped with a micromagnetic sensor and sensor-based experimental details were introduced. Next, the theoretical formula of the normal component () of the SMFL signal that originated from the corroded region was derived based on the magnetic dipole model and the experimental results were discussed. The results indicate that the experimental data of () are consistent with the theoretical calculations, both location and extent of the steel bars corrosion can be qualitatively determined by using (). The gradient of () is approximately linearly related to the loss rate, , of the bending strength, which can be used to evaluate the residual bending strength of the corroded reinforced concrete beam. This work lays the foundation for evaluating the residual bending strength of corroded reinforced concrete beams using the SMFL signal; the micromagnetic sensor is further applied to the civil engineering.

摘要

本文提出了一种通过分析自磁场漏磁(SMFL)信号来评估腐蚀钢筋混凝土梁残余弯曲强度的无损检测方法。该自动扫描装置配备了微磁传感器,并介绍了基于传感器的实验细节。接下来,基于磁偶极子模型推导出了源于腐蚀区域的 SMFL 信号的法向分量()的理论公式,并讨论了实验结果。结果表明,()的实验数据与理论计算相符,可通过()定性确定钢筋的位置和腐蚀程度。()的梯度与弯曲强度的损失率 大致呈线性关系,可用于评估腐蚀钢筋混凝土梁的残余弯曲强度。这项工作为利用 SMFL 信号评估腐蚀钢筋混凝土梁的残余弯曲强度奠定了基础;微磁传感器进一步应用于土木工程领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/7942b81a89da/sensors-18-02635-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/1a6fcfe23ace/sensors-18-02635-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/58282a742a6b/sensors-18-02635-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/60ee1ff95274/sensors-18-02635-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/c3511970d03c/sensors-18-02635-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/19f9e6c8e31c/sensors-18-02635-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/771e290b8ad0/sensors-18-02635-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/d466aefe33d7/sensors-18-02635-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/3846acd6b518/sensors-18-02635-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/7942b81a89da/sensors-18-02635-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/1a6fcfe23ace/sensors-18-02635-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/3db7c862a9d1/sensors-18-02635-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/9b2e5df48148/sensors-18-02635-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/442435187aa2/sensors-18-02635-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/58282a742a6b/sensors-18-02635-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/60ee1ff95274/sensors-18-02635-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/c3511970d03c/sensors-18-02635-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/19f9e6c8e31c/sensors-18-02635-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/771e290b8ad0/sensors-18-02635-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/d466aefe33d7/sensors-18-02635-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/3846acd6b518/sensors-18-02635-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2194/6111848/7942b81a89da/sensors-18-02635-g012.jpg

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