Dispersed passive RF-sensing for 3D structural health monitoring

Abeer Ahmad, Xiao Sha, Akshay Athalye, Samir R. Das, Kelly Caylor, Branko Glisic, Milutin Stanacevic, Petar M. Djuric
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Abstract

We propose a sensing system comprising a large network of tiny, battery-less, Radio Frequency (RF)-powered sensors that use backscatter communication. The sensors use an entirely passive technique to 'sense' the parameters of the wireless channel between themselves. Since the material properties influence RF channels, this fine-grain sensing can uncover multiple material properties both at a large scale and fine spatial resolution. In this paper, we study the feasibility of the proposed passive technique for monitoring parameters of material in which the sensors are embedded. We performed a set of experiments where the sensor-to-sensor wireless channel parameters are well-defined using physics-based modeling, and we compared the theoretical and experimentally obtained values. For some material parameters of interest, like humidity or strain, the relationship with the observed wireless channel parameters have to be modeled relying on data-driven approaches. The initial experiments show an observable difference in the sensor-to-sensor channel phase with variation in the applied weights.
用于三维结构健康监测的分散被动射频传感
我们提出了一个传感系统,包括一个大型网络的微型,无电池,射频(RF)供电的传感器,使用反向散射通信。传感器使用完全被动的技术来“感知”它们之间无线信道的参数。由于材料特性影响射频通道,这种细粒度传感可以在大尺度和精细空间分辨率下揭示多种材料特性。在本文中,我们研究了所提出的无源技术用于监测嵌入传感器的材料参数的可行性。我们进行了一组实验,其中传感器到传感器的无线信道参数使用基于物理的建模来定义,我们比较了理论和实验得到的值。对于一些感兴趣的材料参数,如湿度或应变,与观测到的无线信道参数的关系必须依靠数据驱动的方法来建模。初始实验表明,随着所施加权重的变化,传感器到传感器信道相位存在可观察到的差异。
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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