腐蚀RC梁整体腐蚀程度的SMFL分级评价

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Hong Zhang, Xiaotao Ma, Hejing Jiang, Kai Tong, Yu Zheng, Jianting Zhou
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引用次数: 0

摘要

为了准确评价钢筋混凝土梁的整体腐蚀程度,基于SMFL技术,对6根钢筋混凝土梁进行了整体随机腐蚀检测试验。分析了磁感应强度与腐蚀程度的切向分量By与法向分量Bz之间的关系,建立了多缺陷磁偶极子模型。重点探讨了钢筋混凝土梁的平均腐蚀比C与磁特征指数KG之间的关系。结果表明,随着平均腐蚀比C的增大,磁性特征指数KG整体呈增大趋势。指数KG能减弱不同历史磁化强度的影响,但具有一定的色散性。根据相关性和朴素贝叶斯模型,将平均腐蚀比C划分为4个等级。利用KG磁特性指数可以定量评价C在不同取值范围内下降的概率。可靠性最高可达97.4%,最低可达56.8%,实现了钢筋混凝土梁锈蚀的定量分级评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Grading Evaluation of Overall Corrosion Degree of Corroded RC Beams via SMFL Technique

Grading Evaluation of Overall Corrosion Degree of Corroded RC Beams via SMFL Technique

To accurately evaluate the overall corrosion degree of reinforced concrete (RC) beams, on the basis of the SMFL technology, the overall random corrosion detection experiment of six RC beams was carried out. The relationship between the tangential component By and the normal component Bz of the magnetic induction intensity and corrosion degree was analyzed, and a multidefect magnetic dipole model was established. The correlation between the average corrosion ratio C of the RC beam and the magnetic characteristic index KG was emphatically explored. The results showed that, with the increase in the average corrosion ratio C, the magnetic characteristic index KG showed an increasing trend as a whole. The index KG could weaken the influence of different historical magnetizations, but it had a certain dispersion. On the basis of the correlation and the Naive Bayesian model, the average corrosion ratio C was divided into four grades. The probability of C falling in different value ranges can be quantitatively evaluated using the KG magnetic characteristic index. The reliability is as high as 97.4% and as low as 56.8% so as to realize the quantitative grading evaluation of the corrosion of the rebar in the RC beam.

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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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