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A SAW wireless sensor network platform for industrial predictive maintenance

  • Bérenger Ossété Gombé
  • Gwenhael Goavec Mérou
  • Karla Breschi
  • Hervé Guyennet
  • Jean-Michel Friedt
  • Violeta Felea
  • Kamal Medjaher
Article

Abstract

Predictive maintenance predicts the system health, based on the current condition, and defines the needed maintenance activities accordingly. This way, the system is only taken out of service if direct evidence exists that deterioration has actually taken place. This increases maintenance efficiency and productivity on one hand, and decreases maintenance support costs and logistics footprints on the other. We propose a system based on wireless sensor network to monitor industrial systems in order to prevent faults and damages. The sensors use the surface acoustic wave technology with an architecture composed of an electronic interrogation device and a passive sensor (without energy at the transducer) which is powered by the radio frequency transmitted by the interrogation unit. The radio frequency link transfers energy to the sensor to perform its measurement and to transmit the result to the interrogation unit—or in a description closer to the implemented, characterize the cooperative target cross section characteristics to recover the physical quantity defining the transducer material properties. We use this sensing architecture to measure the temperature of industrial machine components and we evaluate the robustness of the method. This technology can be applied to other physical parameters to be monitored. Captured information is transmitted to the base station through multi-hop communications. We also treat interferences involved in both interrogator to interrogator and sensor to interrogator communications.

Keywords

Predictive maintenance Surface acoustic wave Wireless sensor network 

Notes

Acknowledgements

This work is supported by the Franco-Swiss INTERREG IV program, in the context of the MainPreSI project.

References

  1. Beckley, J., Kalinin, V., Lee, M., & Voliansky, K. (2002). Non-contact torque sensors based on SAW resonators. In IEEE international frequency control symposium and PDA exhibition (pp. 202–213).Google Scholar
  2. Beriain, A., Berenguer, R., Jimenez-Irastorza, A., Farsens, S. L., Montiel-Nelson, J. A., Sosa, J., & Pulido, R. (2014). Full passive RFID pressure sensor with a low power and low voltage time to digital interface. In Conference on design of circuits and integrated circuits (DCIS) (pp. 1–6). IEEE.Google Scholar
  3. Buff, W., Plath, F., Schmeckebier, O., Rusko, M., Vandahl, T., Luck, H., et al. (1994). Remote sensor system using passive SAW sensors. Proceedings of IEEE Ultrasonics Symposium, 1, 585–588.Google Scholar
  4. Bulst, W.-E., Fischerauer, G., & Reindl, L. (2001). State of the art in wireless sensing with surface acoustic waves. IEEE Transactions on Industrial Electronics, 48(2), 265–271.CrossRefGoogle Scholar
  5. Droit, C., Friedt, J.-M., Goavec-Merou, G., Martin, G., Ballandras, S., Breschi, K., Bernard, J., & Guyennet, H. (2012). Radiofrequency transceiver for probing SAW sensors and communicating through a wireless sensor network. In SENSORCOMM 2012, the sixth international conference on sensor technologies and applications (pp. 48–52).Google Scholar
  6. Fonseca, R., Gnawali, O., Jamieson, K., Kim, S., Levis, P., & Woo, A. (2006a). The collection tree protocol (CTP). TinyOS TEP, 123, 2.Google Scholar
  7. Fonseca, R., Gnawali, O., Jamieson, K., & Levis, P. (2006b). TEP 119: Collection. http://tinyos.net/tinyos-2.x/doc/html/tep119.html.
  8. Gnawali, O. (2006). TEP 124: The link estimation exchange protocol (LEEP). http://tinyos.net/tinyos-2.x/doc/html/tep124.html.
  9. Goavec-Merou, G., Breshi, K., Martin, G., Ballandras, S., Bernard, J., Droit, C., & Friedt, J.-M. ( 2012). Multipurpose use of radiofrequency sources for probing passive wireless sensors and routing digital messages in a wireless sensor network. In eWise workshop, at IEEE iThings conference.Google Scholar
  10. Hartmann, P. R. (2009). A passive SAW based RFID system for use on ordnance. In IEEE international conference on RFID (pp. 291–297).Google Scholar
  11. Hartmann, C. S., & Claiborne, L. T. (2007). Fundamental limitations on reading range of passive IC-based RFID and SAW-based RFID. In IEEE international conference on RFID (pp. 41–48).Google Scholar
  12. Hashimoto, K.-Y. (2009). RF Bulk Acoustic Wave Filters for Communications. Artech House Microwave Library .Google Scholar
  13. Heng, A., Zhang, S., Tan, A. C. C., & Mathew, J. (2009). Rotating machinery prognostics: State of the art, challenges and opportunities. Mechanical Systems and Signal Processing, 23(3), 724–739.CrossRefGoogle Scholar
  14. Hu, C., Youn, B. D., Wang, P., & Yoon, J. T. (2012). Ensemble of data-driven prognostic algorithms for robust prediction of remaining useful life. Reliability Engineering and System Safety, 103, 120–135.CrossRefGoogle Scholar
  15. Kuypers, J. H., Tanaka, S., Esashi, M., Eisele, D. A., & Reindl, D. A. (2006). 2.45 GHz passive wireless temperature monitoring system featuring parallel sensor interrogation and resolution evaluation. In 5th IEEE conference on sensors (pp. 773–776).Google Scholar
  16. Levis, P., Madden, S., Polastre, J., Szewczyk, R., Whitehouse, K., Woo, A., Gay, D., Hill, J., Welsh, M., & Brewer, E.(2005). TinyOS: An operating system for sensor networks. In W. Weber, J. M. Rabaey, & E. Aarts (Eds.) Ambient intelligence (pp. 115–148). Berlin, Heidelberg: Springer.Google Scholar
  17. Levis, P., Patel, N., Culler, D., & Shenker, S. (2004). Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks. In Proceedings of the 1st conference on symposium on networked systems design and implementation.Google Scholar
  18. Medjaher, K., Tobon-Mejia, D., & Zerhouni, N. (2012). Remaining useful life estimation of critical components with application to bearings. IEEE Transactions on Reliability, 61(2), 292–302.CrossRefGoogle Scholar
  19. Morgan, D. (2007). Surface acoustic wave filters with applications to electronic communications and signal processing. Amsterdam, Boston: Academic Press.Google Scholar
  20. Plessky, V. P., & Reindl, L. M. (2010). Review on SAW RFID tags. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 57(3), 654–668.CrossRefGoogle Scholar
  21. Pohl, A., Seifert, F., Reindl, L., Scholl, G., Ostertag, T., & Pietsch, W. (1994). Radio signals for SAW ID tags and sensors in strong electromagnetic interference. Proceedings of IEEE Ultrasonics Symposium, 1, 195–198.Google Scholar
  22. Pohl, A., Steindl, R., & Reindl, L. (1999). The ’intelligent tire’ utilizing passive SAW sensors measurement of tire friction. IEEE Transactions on Instrumentation and Measurement, 48(6), 1041–1046.CrossRefGoogle Scholar
  23. Preradovic, S., & Karmakar, N. C. (2012). Multiresonator-based chipless RFID. Barcode of the future. New York: Springer.CrossRefGoogle Scholar
  24. Reindl, L., Scholl, G., Ostertag, T., Ruppel, C. C. W., Bulst, W. E., & Seifert, F. (1996). SAW devices as wireless passive sensors. Proceedings of IEEE Ultrasonics Symposium, 1, 363–367.Google Scholar
  25. Scherr, H., Scholl, G., Seifert, F., & Weigel, R. (1996). Quartz pressure sensor based on SAW reflective delay line. Proceedings of IEEE Ultrasonics Symposium, 1, 347–350.Google Scholar
  26. Skolnik, M. (1990). Radar handbook (2nd ed.). New York: McGraw-Hill.Google Scholar
  27. Soualhi, A., Medjaher, K., & Zerhouni, N. (2015). Bearing health monitoring based on Hilbert–Huang transform, support vector machine, and regression. IEEE Transactions on Instrumentation and Measurement, 64(1), 52–62.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Bérenger Ossété Gombé
    • 1
    • 2
  • Gwenhael Goavec Mérou
    • 2
  • Karla Breschi
    • 3
  • Hervé Guyennet
    • 3
  • Jean-Michel Friedt
    • 1
    • 2
  • Violeta Felea
    • 3
  • Kamal Medjaher
    • 4
  1. 1.SENSeOR SAS, BesançonBesançonFrance
  2. 2.FEMTO-ST/Time and FrequencyBesançonFrance
  3. 3.FEMTO-ST/DISCBesançonFrance
  4. 4.Laboratoire Génie de Production/INP-ENITTarbesFrance

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