Modeling and Signal Processing of Bulk Acoustic Wave Passive Wireless Strain Sensors

Untethered, battery-less, and chip-less passive wireless strain sensors have been widely investigated to overcome the drawbacks of conventional sensors for structure health monitoring of large civil structures. Although the-state-of-the-art passive wireless sensors enable long-range, high-resolution...

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Vydáno v:IEEE transactions on instrumentation and measurement Ročník 73; s. 1 - 9
Hlavní autoři: Zou, Xiyue, Li, Wen, Zhang, Yan, Hu, Bin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Acoustic waves
Algorithms
Bulk acoustic wave (BAW) device
Cantilever beams
Capacitive sensors
Frequency measurement
frequency-domain signal
Functions (mathematics)
Mathematical analysis
Mathematical models
passive wireless sensor
Peak frequency
Polynomials
Receivers
Resonant frequencies
Resonant frequency
Sensors
Signal processing
smoothing algorithms
Structural health monitoring
Transmitters
Vibration measurement
Waveforms
Wireless communication
Wireless sensor networks
ISSN:0018-9456, 1557-9662
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Popis
Shrnutí:Untethered, battery-less, and chip-less passive wireless strain sensors have been widely investigated to overcome the drawbacks of conventional sensors for structure health monitoring of large civil structures. Although the-state-of-the-art passive wireless sensors enable long-range, high-resolution measurements, the signal processing of these sensors is still a challenging task. Passive wireless sensors require an algorithm to capture their resonant frequencies from noisy signals. In this article, we propose an algorithm based on rational polynomial functions to fit the full waveform of bulk acoustic wave (BAW)-based passive wireless strain sensors. We establish an analytical expression for the signal and simplify it based on multiple constrains. Numerical simulations show that the simplified fitting functions can accurately extract the peak frequency of the resonant signal when these constraints are satisfied. The experimental demonstrations confirm that passive wireless sensors utilizing this algorithm achieve a resolution of <inline-formula> <tex-math notation="LaTeX">4 \mu \varepsilon </tex-math></inline-formula> and a refresh rate of 7.5 Hz. In addition, we used the proposed algorithm to realize the vibration frequency measurement of a cantilever beam with a first mode around 4 Hz. The proposed method has high accuracy and moderate speed in extracting the resonance frequency of passive wireless sensors, thus making it possible to realize noncontact measurements of strain changes or vibrations in large civil structures.
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ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2024.3366286