APSIPA Transactions on Signal and Information Processing > Vol 13 > Issue 4

Contactless Micron-Level Vibration Measurement with Millimeter Wave Radar

Renjie Wen, University of Science and Technology of China, China, Dongheng Zhang, University of Science and Technology of China, China, dongheng@ustc.edu.cn , Jinbo Chen, University of Science and Technology of China, China, Qibin Sun, University of Science and Technology of China, China
 
Suggested Citation
Renjie Wen, Dongheng Zhang, Jinbo Chen and Qibin Sun (2024), "Contactless Micron-Level Vibration Measurement with Millimeter Wave Radar", APSIPA Transactions on Signal and Information Processing: Vol. 13: No. 4, e302. http://dx.doi.org/10.1561/116.00000073

Publication Date: 16 May 2024
© 2024 R. Wen, D. Zhang, J. Chen and Q. Sun
 
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Keywords
Wireless sensingvibration measurementdeep neural network
 

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In this article:
Introduction 
Related Work 
Theory and Estimation Challenges 
Proposed Method 
Experimental Results 
Conclusion 
References 

Abstract

Vibration measurements play a critical role in troubleshooting mechanical equipment and assessing the structural integrity of buildings. However, conventional vibration measurement methods rely on contact-based approaches, such as the attachment of accelerometers to the target object, leading to complex equipment deployment. Therefore, non-contact vibration measurement has attracted great attention but has yet to be fully addressed. In this paper, we propose DeepVib, a non-contact vibration measurement system that enables accurate micron-level vibration monitoring. First, we introduce a series of signal processing algorithms to extract the vibration object motion from mmWave reflection signals. Then, we design a deep neural network to effectively suppress noise interference and achieve outputting higher signal-to-noise ratio data. Finally, we eliminate static reflections with geometric-based method to recover the vibrations of the target. The experimental results show that our non-contact measurement method can accurately measure the vibration at the micron level with the average error of vibration frequency less than 0.1%. For the amplitude below 100μm, the median error of estimation is 7.23%. In addition, DeepVib reduces the estimation error of 80th-percentile amplitude by 56.60% compared with the conventional method.

DOI:10.1561/116.00000073

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APSIPA Transactions on Signal and Information Processing Special Issue - Emerging Wireless Sensing Technologies for Smart Environments
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