research-article

Exploring commodity RFID for contactless sub-millimeter vibration sensing

Authors:

Xiaojiang Chen,

Dingyi FangAuthors Info & Claims

SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems

Pages 15 - 27

https://doi.org/10.1145/3384419.3430771

Published: 16 November 2020 Publication History

Abstract

Monitoring the vibration characteristics of a machine or structure provides valuable information of its health condition and this information can be used to detect problems in their incipient stage. Recently, researchers employ RFID signals for vibration sensing. However, they mainly focus on vibration frequency estimation and still face difficulties in accurately sensing the other important characteristic of vibration which is vibration amplitude in the scale of sub-millimeter. In this paper, we introduce TagSMM, a contactless RFID-based vibration sensing system which can measure vibration amplitude in sub-millimeter resolution. TagSMM employs the signal propagation theory to deeply understand how the signal phase varies with vibration and proposes a coupling-based method to amplify the vibration-induced phase change to achieve sub-millimeter level amplitude sensing for the first time. We design and implement TagSMM with commodity RFID hardware. Our experiments show that TagSMM can detect a 0.5 mm vibration, 10 times better than the state-of-the-arts. Our field studies show TagSMM can sense a drone's abnormal vibration and can also effectively detect a small 0.2 cm screw loose in a motor at a 100% accuracy.

References

[1]

Bass: the physical sensation of sound. https://www.audioholics.com/room-acoustics/bass-the-physical-sensation-of-sound.

[2]

Displacement sensors. https://www.pruftechnik.com/products/condition-monitoring-systems/sensors-and-accessories-for-condition-monitoring/displacement-sensors.html.

[3]

Eliminating vibration for drone. http://www.thedronesmag.com/eliminating-vibration/.

[4]

Epc gen2 tag filtering. https://support.impinj.com/hc/en-us/articles/202756568-epc-gen2-tag-filtering.

[5]

Industrial vibration experiments. https://www.twi-global.com/technical-knowledge/published-papers/an-experiment-to-show-the-feasibility-of-condition-monitoring-above-ground-storage-tank-walls-by-modal-testing-with-piezoelectri.

[6]

Llrp tookit. https://sourceforge.net/p/llrp-toolkit/mailman/message/28740553/.

[7]

Machinery vibration. https://www.machinerylubrication.com/read/25974/signs-tips-machinery-vibration.

[8]

Multi-level machine vibration tester marker pen. https://patents.google.com/patent/us20030056593.

[9]

Petrol electricity generator. https://www.alamy.com/stock-photo-small-emergency-backup-petrol-electricity-generator-in-heavy-winter-54889007.html.

[10]

Portable gm63a digital lcd vibration sensor meter tester. https://www.ebay.com/i/183096688809?chn=ps.

[11]

Rfid mapper. https://www.rfidjournal.com/store/powermapper.

[12]

Vibration amplitude vs. frequency. https://www.skf.com/group/services/services-and-solutions/introduction-to-condition-monitoring/vibration.html.

[13]

S. E. Asl, M. T. Ghasr, M. Zawodniok, and K. E. Robinson. Preliminary study of mutual coupling effect on a passive rfid antenna array. In IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pages 138--141. IEEE, 2013.

[14]

W. Chen, M. Guan, Y. Huang, L. Wang, R. Ruby, W. Hu, and K. Wu. Vitype: A cost efficient on-body typing system through vibration. In Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pages 1--9. IEEE, 2018.

[15]

A. Davis, M. Rubinstein, N. Wadhwa, G. J. Mysore, F. Durand, and W. T. Freeman. The visual microphone: Passive recovery of sound from video. 33(4):1--10, 2014.

[16]

D. Ding, W. Liu, S. Gupta, G. Lombaert, and G. Degrande. Prediction of vibrations from underground trains on beijing metro line 15. Journal of Central South University of Technology, 17(5):1109--1118, 2010.

[17]

L. Ding, M. Ali, S. Patole, and A. Dabak. Vibration parameter estimation using fmcw radar. In Annual IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 2224--2228. IEEE, 2016.

Digital Library

[18]

D. M. Dobkin. The RF in RFID: passive UHF RFID in practice. Newnes, 2012.

[19]

C. Duan, L. Yang, Q. Lin, Y. Liu, and L. Xie. Robust spinning sensing with dual-rfid-tags in noisy settings. In IEEE International Conference on Computer Communications (INFOCOM), pages 855--863. IEEE, 2018.

[20]

A. R. Hassan and K. M. Ali. Dignosis of pulley-belt system faults using vibration analysis technique. Journal of University of Babylon, 26(2):167--180, 2018.

[21]

H. T. Hui, M. E. Bialkowski, and H. S. Lui. Mutual coupling in antenna arrays. International Journal of Antennas and Propagation, 27(6):1039--1055, 2010.

[22]

K. Krajnak, D. A. Riley, J. Wu, T. Mcdowell, D. E. Welcome, X. S. Xu, and R. G. Dong. Frequency-dependent effects of vibration on physiological systems: Experiments with animals and other human surrogates. Industrial health, 50(5):343--353, 2012.

[23]

P. Li, Z. An, L. Yang, and P. Yang. Towards physical-layer vibration sensing with rfids. In International Conference on Computer Communications (INFOCOM), pages 892--900. IEEE, 2019.

[24]

J. Liu, Y. Chen, M. Gruteser, and Y. Wang. Vibsense: Sensing touches on ubiquitous surfaces through vibration. In Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pages 1--9. IEEE, 2017.

[25]

F. Lu, X. S. Chen, and T. T. Ye. Performance analysis of stacked rfid tags. In IEEE International Conference on Rfid, pages 330--337. IEEE, 2009.

[26]

Y.-P. Luh and Y.-C. Liu. Reading rate improvement for uhf rfid systems with massive tags by the q parameter. Wireless Personal Communications, 59(1):147--157, 2011.

Digital Library

[27]

Y. Ma, N. Selby, and F. Adib. Minding the billions: Ultra-wideband localization for deployed rfid tags. In Annual International Conference on Mobile Computing and Networking (Mobicom), pages 248--260. ACM, 2017.

Digital Library

[28]

K. Niu, F. Zhang, J. Xiong, X. Li, E. Yi, and D. Zhang. Boosting fine-grained activity sensing by embracing wireless multipath effects. In International Conference on emerging Networking Experiments and Technologies (CoNEXT), pages 1--14. ACM, 2018.

Digital Library

[29]

K. Otsuka, K. Abe, J.-Y. Ko, and T.-S. Lim. Real-time nanometer-vibration measurement with a self-mixing microchip solid-state laser. Optics letters, 27(15):1339--1341, 2002.

[30]

S. Pan, T. Yu, M. Mirshekari, J. Fagert, A. Bonde, O. J. Mengshoel, H. Y. Noh, and P. Zhang. Footprintid: Indoor pedestrian identification through ambient structural vibration sensing. ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3):89, 2017.

[31]

S. Pradhan, E. Chai, K. Sundaresan, L. Qiu, M. A. Khojastepour, and S. Rangarajan. Rio: A pervasive rfid-based touch gesture interface. In Annual International Conference on Mobile Computing and Networking (MobiCom), pages 261--274. ACM, 2017.

Digital Library

[32]

N. Roy and R. R. Choudhury. Ripple ii: Faster communication through physical vibration. In SENIX Symposium on Networked Systems Design and Implementation (USENIX NSDI), pages 671--684, 2016.

[33]

N. Roy, M. Gowda, and R. R. Choudhury. Ripple: Communicating through physical vibration. In SENIX Symposium on Networked Systems Design and Implementation (USENIX NSDI), pages 265--278, 2015.

[34]

N. Roy and R. Roy Choudhury. Listening through a vibration motor. In 14th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys), pages 57--69. ACM, 2016.

Digital Library

[35]

M. Safizadeh and S. Latifi. Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell. Information Fusion, 18(6):1--8, 2014.

Digital Library

[36]

L. Shangguan, Z. Zhou, and K. Jamieson. Enabling gesture-based interactions with objects. In Annual International Conference on Mobile Systems, Applications, and Services (MobiSys), pages 239--251. ACM, 2017.

Digital Library

[37]

F. Tonolini and F. Adib. Networking across boundaries: enabling wireless communication through the water-air interface. In 2018 Conference of the ACM Special Interest Group on Data Communication, pages 117--131. ACM, 2018.

Digital Library

[38]

A. Veeraraghavan, D. Reddy, and R. Raskar. Coded strobing photography: Compressive sensing of high speed periodic videos. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(4):671--686, 2010.

Digital Library

[39]

H. Wang, D. Zhang, J. Ma, Y. Wang, Y. Wang, D. Wu, T. Gu, and B. Xie. Human respiration detection with commodity wifi devices: do user location and body orientation matter? In ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp), pages 25--36. ACM, 2016.

Digital Library

[40]

J. Wang, J. Xiong, X. Chen, H. Jiang, R. K. Balan, and D. Fang. Tagscan: Simultaneous target imaging and material identification with commodity rfid devices. In 23rd Annual International Conference on Mobile Computing and Networking (MobiCom), pages 288--300. ACM, 2017.

Digital Library

[41]

J. Wang, J. Xiong, H. Jiang, X. Chen, and D. Fang. D-watch: embracing "bad" multipaths for device-free localization with cots rfid devices. IEEE/ACM Transactions on Networking (TON), 25(6):3559--3572, 2017.

[42]

Z. Wang, J. Soltis, and W. Miller. Improved approach to interpolation using the fft. Electronics Letters, 28(25):2320--2322, 1992.

[43]

T. Wei and X. Zhang. Gyro in the air: tracking 3d orientation of batteryless internet-of-things. In 22st Annual International Conference on Mobile Computing and Networking (MobiCom), pages 55--68. ACM, 2016.

Digital Library

[44]

Y. Xie, J. Xiong, M. Li, and K. Jamieson. md-track: Leveraging multi-dimensionality in passive indoor wi-fi tracking. In 25st Annual International Conference on Mobile Computing and Networking (Mobicom), pages 487--499. ACM, 2019.

Digital Library

[45]

C. Xu, Z. Li, H. Zhang, A. S. Rathore, H. Li, C. Song, K. Wang, and W. Xu. Waveear: Exploring a mmwave-based noise-resistant speech sensing for voice-user interface. In Annual International Conference on Mobile Systems, Applications, and Services (MobiSys), pages 14--26. ACM, 2019.

Digital Library

[46]

L. Yang, Y. Chen, X.-Y. Li, C. Xiao, M. Li, and Y. Liu. Tagoram: Real-time tracking of mobile rfid tags to high precision using cots devices. In Annual International Conference on Mobile Computing and Networking (MobiCom), pages 237--248. ACM, 2014.

Digital Library

[47]

L. Yang, Y. Li, Q. Lin, H. Jia, X.-Y. Li, and Y. Liu. Tagbeat: Sensing mechanical vibration period with cots rfid systems. IEEE/ACM transactions on networking, 25(6):3823--3835, 2017.

[48]

L. Yang, Y. Li, Q. Lin, X.-Y. Li, and Y. Liu. Making sense of mechanical vibration period with sub-millisecond accuracy using backscatter signals. In Annual ACM International Conference on Mobile Computing and Networking (MobiCom), pages 16--28. ACM, 2016.

Digital Library

[49]

P. Yang, Y. Feng, J. Xiong, Z. Chen, and X. Li. Rf-ear: Contactless multi-device vibration sensing and identification using cots rfid. In International Conference on Computer Communications (INFOCOM), pages 1--10. IEEE, 2020.

Digital Library

[50]

Y. Zhang, G. Laput, and C. Harrison. Vibrosight: Long-range vibrometry for smart environment sensing. In Annual ACM Symposium on User Interface Software and Technology, pages 225--236. ACM, 2018.

Digital Library

[51]

Y. Zheng, Y. He, M. Jin, X. Zheng, and Y. Liu. Red: Rfid-based eccentricity detection for high-speed rotating machinery. In IEEE International Conference on Computer Communications (INFOCOM), pages 1565--1573. IEEE, 2018.

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Index Terms

Exploring commodity RFID for contactless sub-millimeter vibration sensing
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Sensors and actuators

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cover image ACM Conferences

SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems

November 2020

852 pages

ISBN:9781450375900

DOI:10.1145/3384419

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 16 November 2020

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ShaanXi Science and Technology Innovation Team Support Project
National Natural Science Foundation of China (NSFC)
UMass Amherst Institute For Applied Life Sciences Equipment Fund
International Science and Technology Cooperation Project

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SenSys '20

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SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems

November 16 - 19, 2020

Virtual Event, Japan

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Overall Acceptance Rate 174 of 867 submissions, 20%

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Cited By

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Nie MZou LCui HZhou XWan Y(2024)Enhancing Human Activity Recognition with LoRa Wireless RF Signal Preprocessing and Deep LearningElectronics10.3390/electronics1302026413:2(264)Online publication date: 6-Jan-2024
https://doi.org/10.3390/electronics13020264
Chang ZZhang FMa XWang PChen WZhang DJouaber BZhang D(2024)MmECare: Enabling Fine-grained Vital Sign Monitoring for Emergency Care with Handheld MmWave RadarsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997668:4(1-24)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699766
Chen YYu JChen YKong LZhu YChen YOkoshi TKo JLiKamWa R(2024)RFSpy: Eavesdropping on Online Conversations with Out-of-Vocabulary Words by Sensing Metal Coil Vibration of Headsets Leveraging RFIDProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661887(169-182)Online publication date: 3-Jun-2024
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Ning JYan ZWu ZXie LWang CChen YYe BLu SGanesan DLane NShi W(2024)MoiréVib: Micron-level Vibration Detection based on Moiré PatternProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3690700(1393-1407)Online publication date: 4-Dec-2024
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