Spatially resolved capacitance-based stress self-sensing in concrete

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2024-07-07 DOI:10.1016/j.isatra.2024.06.034
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Abstract

Spatially resolved capacitance-based stress self-sensing in unmodified concrete has been demonstrated. The spatial resolution is 45 mm in one dimension, which is in the direction of the capacitance measurement. Parallel coplanar component electrodes (aluminum, 5-mm wide), attached to the concrete using double-sided adhesive tape) separated by 45 mm are used to measure the in-plane capacitance in the direction perpendicular to the length of the electrodes. Combinations of component electrodes are electrically connected to form an electrode. The capacitance ranges from ∼200 pF to ∼750 pF. The greater is the number of component electrodes in an electrode, the higher is the capacitance. The compressive loading is applied at selected areas located between adjacent component electrodes. The stress (defined as load divided by the 300 ×300-mm2 concrete area) is up to 3000 Pa. The load decreases the capacitance monotonically and reversibly. The fractional decrease in capacitance ranges from ∼0.1 % to ∼0.5 %. More spatially concentrated loading, as for loading near the edges of the specimen, gives greater fractional decrease in capacitance. The capacitance decreases with increasing inter-electrode distance. Embedded steel rebars with a 20.0-mm concrete cover do not affect the capacitance or capacitance-based sensing.

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基于空间分辨电容的混凝土应力自感。
在未改性混凝土中演示了基于电容的空间分辨应力自感应。空间分辨率在电容测量方向的一个维度上为 45 毫米。使用双面胶带将平行共面元件电极(铝,5 毫米宽)粘贴到混凝土上,间隔 45 毫米,用于测量垂直于电极长度方向的面内电容。各组电极通过电连接形成一个电极。电容范围从 ∼200 pF 到 ∼750 pF。电极中的元件电极数量越多,电容越大。压缩负载施加在相邻元件电极之间的选定区域。应力(定义为荷载除以 300 ×300 平方毫米的混凝土面积)最大为 3000 Pa。荷载单调且可逆地降低电容。电容下降的比例从 0.1 % 到 0.5 % 不等。加载的空间越集中,如在试样边缘附近加载,电容下降的分数越大。电容随电极间距的增加而减小。带有 20.0 毫米混凝土覆盖层的嵌入式钢筋不会影响电容或基于电容的传感。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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