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基于智能表皮的钢筋混凝土结构裂缝检测

Crack Detection of Reinforced Concrete Structure Using Smart Skin.

作者信息

Jung Yu-Jin, Jang Sung-Hwan

机构信息

Department of Smart City Engineering, Hanyang University ERICA, Ansan 15588, Republic of Korea.

Department of Civil and Environmental Engineering, Hanyang University ERICA, Ansan 15588, Republic of Korea.

出版信息

Nanomaterials (Basel). 2024 Apr 5;14(7):632. doi: 10.3390/nano14070632.

Abstract

The availability of carbon nanotube (CNT)-based polymer composites allows the development of surface-attached self-sensing crack sensors for the structural health monitoring of reinforced concrete (RC) structures. These sensors are fabricated by integrating CNTs as conductive fillers into polymer matrices such as polyurethane (PU) and can be applied by coating on RC structures before the composite hardens. The principle of crack detection is based on the electrical change characteristics of the CNT-based polymer composites when subjected to a tensile load. In this study, the electrical conductivity and electro-mechanical/environmental characterization of smart skin fabricated with various CNT concentrations were investigated. This was performed to derive the tensile strain sensitivity of the smart skin according to different CNT contents and to verify their environmental impact. The optimal CNT concentration for the crack detection sensor was determined to be 5 wt% CNT. The smart skin was applied to an RC structure to validate its effectiveness as a crack detection sensor. It successfully detected and monitored crack formation and growth in the structure. During repeated cycles of crack width variations, the smart skin also demonstrated excellent reproducibility and electrical stability in response to the progressive occurrence of cracks, thereby reinforcing the reliability of the crack detection sensor. Overall, the presented results describe the crack detection characteristics of smart skin and demonstrate its potential as a structural health monitoring (SHM) sensor.

摘要

基于碳纳米管(CNT)的聚合物复合材料的可用性使得能够开发用于钢筋混凝土(RC)结构健康监测的表面附着自传感裂纹传感器。这些传感器是通过将碳纳米管作为导电填料集成到聚氨酯(PU)等聚合物基体中制成的,并且可以在复合材料硬化之前通过涂覆在RC结构上进行应用。裂纹检测原理基于基于碳纳米管的聚合物复合材料在承受拉伸载荷时的电学变化特性。在本研究中,研究了用不同碳纳米管浓度制备的智能表皮的电导率以及机电/环境特性。这样做是为了根据不同的碳纳米管含量得出智能表皮的拉伸应变灵敏度,并验证其对环境的影响。确定用于裂纹检测传感器的最佳碳纳米管浓度为5 wt%碳纳米管。将智能表皮应用于RC结构以验证其作为裂纹检测传感器的有效性。它成功地检测和监测了结构中裂纹的形成和扩展。在裂纹宽度变化的重复循环过程中,智能表皮在响应裂纹的逐渐出现时还表现出出色的可重复性和电稳定性,从而增强了裂纹检测传感器的可靠性。总体而言,所呈现的结果描述了智能表皮的裂纹检测特性,并证明了其作为结构健康监测(SHM)传感器的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7dc9/11013725/7196f40335fb/nanomaterials-14-00632-g001.jpg

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