4.7 Article

Nondestructive Phase Variation-Based Chipless Sensing Methodology for Metal Crack Monitoring

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2021.3065432

关键词

Chipless; comb sensing (CS) structure; crack; metal; nondestructive testing (NDT); passive; phase; sensor; spiral sensing (SS) structure; structural health monitoring (SHM)

向作者/读者索取更多资源

This article introduces a new methodology for structural health monitoring using a passive microwave sensor, demonstrating the detection of cracks on metallic structures. By comparing the phase parameter of signals reflected from damaged and undamaged metals, the method offers a potentially submillimeter-width crack detection through smart structures. The vision is to provide a chipless, low-cost sensor with increased detection reliability and durability in harsh environments.
This article presents a new methodology for structural health monitoring (SHM) applications using a passive microwave sensor. This sensor provides sensitivities on metallic structures for nondestructive testing (NDT) and detecting fatigue cracks or damages. In this method, two different microstrip-based designs are mounted on metal, spiral, and comb sensing structures. Both sensing structures are interrogated by a 2.45 GHz signal in CST Microwave Studio, and their sensitivities for crack detection are compared through the S-11 scattering parameter. We demonstrate that measuring the reflected signal's phase parameter from a sensor on a damaged metal provides information from the surface crack by comparing it to the same metal without any crack. The vision is to provide a new chipless, low-cost sensor with increased detection reliability and durability in harsh environments. Simulation results of the comb sensing (CS) structure show that the signal phase shift caused by a crack envisions the possibility of submillimeter-width crack detection through smart structures.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据