Optimized Design of a Multiaxis Vibration Sensor With Flexible Hinge Using PESA-II

A unique multiaxis vibration sensor system based on a flexible fiber Bragg grating (FBG) hinge is presented in this article. Derivation of sensitivity formulae for longitudinal and transverse vibration offers insight into the sensor’s behavior in response to stimuli that are directed in multiple directions. The sensor design is improved via a multiobjective optimization technique, which minimizes interference and increases sensitivity. By tackling crosstalk and interference, a random forest (RF)-based recognition model substantially increases the accuracy of vibration signal identification. High sensitivities are seen in the 100–1000 Hz frequency range: 8.847, 11.71, and 7.687 pm/g. Impressive lateral anti-interference identification rates of 99.58% and 98.75% are attained by our RF model, proving its resilience in a variety of monitoring circumstances. These results highlight the improved dependability and performance of FBG hinge-type accelerometers.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-11-27
DOI
https://doi.org/10.1109/jsen.2024.3503611
Citations
2
Primary Topic
Sensor Technology and Measurement Systems
Type
article
Field-Weighted Citation Impact
0.70
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article

Optimized Design of a Multiaxis Vibration Sensor With Flexible Hinge Using PESA-II

Xiaoling Tong, Yuxing Duan, Hui Wang, Lei Liang et al.
2 citations
IEEE Sensors Journal
Sensor Technology and Measurement Systems
0.70
article

Optimized Design of a Multiaxis Vibration Sensor With Flexible Hinge Using PESA-II

Xiaoling Tong, Yuxing Duan, Hui Wang, Lei Liang, Ke Jiang, Shu Dai
article en
2 citations

Abstract

A unique multiaxis vibration sensor system based on a flexible fiber Bragg grating (FBG) hinge is presented in this article. Derivation of sensitivity formulae for longitudinal and transverse vibration offers insight into the sensor’s behavior in response to stimuli that are directed in multiple directions. The sensor design is improved via a multiobjective optimization technique, which minimizes interference and increases sensitivity. By tackling crosstalk and interference, a random forest (RF)-based recognition model substantially increases the accuracy of vibration signal identification. High sensitivities are seen in the 100–1000 Hz frequency range: 8.847, 11.71, and 7.687 pm/g. Impressive lateral anti-interference identification rates of 99.58% and 98.75% are attained by our RF model, proving its resilience in a variety of monitoring circumstances. These results highlight the improved dependability and performance of FBG hinge-type accelerometers.

IEEE Sensors JournalVol. 25(2)
Wuhan University of Technology (CN), Sanya University (CN)
Affordable and clean energy
Openalex Percentile: Top 26%
Sensor Technology and Measurement Systems
0.70
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Optimized Design of a Multiaxis Vibration Sensor With Flexible Hinge Using PESA-II — Xiaoling Tong, Yuxing Duan, et al. · IEEE Sensors Journal (2024) | TGRS Research Map | TGRS