In this research, two radiofrequency identification (RFID) antenna sensor designs are tested for compressive strain measurement. The first design is a passive (battery-free) folded patch antenna sensor with a planar dimension of 61mm × 69mm. The second design is a slotted patch antenna sensor, whose dimension is reduced to 48mm × 44mm by introducing slots on antenna conducting layer to detour surface current path. A three-point bending setup is fabricated to apply compression on a tapered aluminum specimen mounted with an antenna sensor. Mechanics-electromagnetics coupled simulation shows that the antenna resonance frequency shifts when each antenna sensor is under compressive strain. Extensive compression tests are conducted to verify the strain sensing performance of the two sensors. Experimental results confirm that the resonance frequency of each antenna sensor increases in an approximately linear relationship with respect to compressive strain. The compressive strain sensing performance of the two RFID antenna sensors, including strain sensitivity and determination coefficient, is evaluated based on the experimental data.
In this work, a slotted patch antenna is employed as a wireless sensor for monitoring structural strain and fatigue crack. Using antenna miniaturization techniques to increase the current path length, the footprint of the slotted patch antenna can be reduced to one quarter of a previously presented folded patch antenna. Electromagnetic simulations show that the antenna resonance frequency varies when the antenna is under strain. The resonance frequency variation can be wirelessly interrogated and recorded by a radiofrequency identification (RFID) reader, and can be used to derive strain/deformation. The slotted patch antenna sensor is entirely passive (battery-free), by exploiting an inexpensive offthe- shelf RFID chip that receives power from the wireless interrogation by the reader.
For application in structural health monitoring, a folded patch antenna has been previously designed as a wireless sensor
that monitors strain and crack in metallic structures. Resonance frequency of the RFID patch antenna is closely related
with its dimension. To measure stress concentration in a base structure, the sensor is bonded to the structure like a
traditional strain gage. When the antenna sensor is under strain/deformation together with the base structure, the antenna
resonance frequency varies accordingly. The strain-related resonance frequency variation is wirelessly interrogated and
recorded by a reader, and can be used to derive strain/deformation. Material properties of the antenna components can
have significant effects on sensor performance. This paper investigates thermal effects through both numerical
simulation and temperature chamber testing. When temperature fluctuates, previous sensor design (with a glass
microfiber-reinforced PTFE substrate) shows relatively large variation in resonance frequency. To improve sensor
performance, a new ceramic-filled PTFE substrate material is chosen for re-designing the antenna sensor. Temperature
chamber experiments are also conducted to the sensor with new substrate material, and compared with previous design.
In order to assess structural safety conditions, many vibration-based damage detection methods have been developed in
recent years. Among these methods, transmissibility function analysis can utilize output data only, and proves to be
effective in damage detection. However, previous research mostly focused on experimental validation of using
transmissibility function for damage detection. Very few studies are devoted to analytically investigating its performance
for damage detection. In this paper, a spring-mass-damper model with multiple degrees-of-freedom is formulated for
further analytical studies on the damage sensitivity of transmissibility functions. The sensitivity of transmissibility
function against structural mass and stiffness change is analytically derived and validated by numerical examples.
This paper explores folded patch antennas for the development of low-cost and wireless smart-skin sensors that monitor
the strain in metallic structures. When the patch antenna is under strain/deformation, its resonance frequency varies
accordingly. The variation can be easily interrogated and recorded by a wireless reader that also provides power for the
antenna operation. The patch antenna adopts a specially selected substrate material with low dielectric constant, as well
as an inexpensive off-the-shelf radiofrequency identification (RFID) chip for signal modulation. A thicker substrate
increases RFID signal-to-noise ratio, but reduces the strain transfer efficiency. To experimentally study the effect of
substrate thickness, two prototype folded patch antennas with different substrate thicknesses have been designed and
manufactured. For both prototypes, tensile testing results show strong linearity between the interrogated resonance
frequency and the strain experienced by the antenna. Longer interrogation range is achieved with the larger substrate
thickness.
Structural health monitoring (SHM) and damage detection have attracted great interest in recent decades, in meeting the
challenges of assessing the safety condition of large-scale civil structures. By wiring remote sensors directly to a
centralized data acquisition system, traditional structural health monitoring systems are usually costly and the installation
is time-consuming. Recent advances in wireless sensing technology have made it feasible for structural health
monitoring; furthermore, the computational core in a wireless sensing unit offers onboard data interrogation. In addition
to wireless sensing, the authors have recently developed a mobile sensing system for providing high spatial resolution
and flexible sensor deployment in structural health monitoring. In this study, transmissibility function analysis is
embedded in the mobile sensing node to perform onboard and in-network structural damage detection. The system
implementation is validated using a laboratory 2D steel portal frame. Simulated damage is applied to the frame
structure, and the damage is successfully identified by two mobile sensing nodes that autonomously navigate through the
structure.
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