基于TDR的智能自感碳基TRC损伤区检测

Mahdi Gaben, Y. Goldfeld
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引用次数: 0

摘要

本研究旨在探讨智能自感知碳粗纱机检测TRC结构损伤区域的能力。目前最先进的监测程序是基于综合测量,因此仅限于检测损伤的发生。本研究针对这一限制,提出采用时域反射计(TDR)技术。TDR概念广泛应用于卡口螺母连接(BNC)电缆中,用于识别沿电缆的缺陷(开路、短路等)。本研究将其原理应用于碳粗纱。为了模拟BNC电缆配置,本研究提出将两个平行的碳粗纱连接到TDR数据采集(DAQ)系统。通过对两根纤维增强MPC梁进行单轴拉伸加载,对所提出的监测技术进行了研究。结果表明了该方法在TRC结构损伤区域定位中的潜力,并突出了其局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DETECTING DAMAGED ZONES ALONG SMART SELFSENSORY CARBON BASED TRC BY TDR
The study aims to investigate the ability of smart self-sensory carbon roving to detect damaged zones in TRC structures. State of the art monitoring procedures are based on integrative measurements and accordingly are limited in detecting only the occurrence of damage. This study aims to handle this limitation and offers to adopt the Time Domain Reflectometer (TDR) technique. The TDR concept is widely used in Bayonet Nut Coupling (BNC) cables to identify defects along the cable (opens, shorts, etc.). The current study adopts its principle to carbon rovings. To simulate the BNC cable configuration, the study offers to connect two parallel carbon rovings to the TDR Data Acquisition (DAQ) system. The proposed monitoring technique is investigated by loading two textile reinforced MPC beams under uniaxial tensile loading. Results show the potential of the suggested technique to locate damage zones in TRC structures and highlights its limitation.
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