Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Spatio-temporal protocol for power-efficient acquisition wireless sensors based SHM

  • Bogdanovic, Nikola (Department of Computer Engineering and Informatics, University of Patras & C.T.I RU-8) ;
  • Ampeliotis, Dimitris (Department of Computer Engineering and Informatics, University of Patras & C.T.I RU-8) ;
  • Berberidis, Kostas (Department of Computer Engineering and Informatics, University of Patras & C.T.I RU-8) ;
  • Casciat, Fabio (Department of Civil Engineering and Architecture, University of Pavia) ;
  • Plata-Chaves, Jorge (Department of Computer Engineering and Informatics, University of Patras & C.T.I RU-8)
  • Received : 2013.09.16
  • Accepted : 2014.06.30
  • Published : 2014.07.25
⟨ Previous Next ⟩

Abstract

In this work, we address the so-called sensor reachback problem for Wireless Sensor Networks, which consists in collecting the measurements acquired by a large number of sensor nodes into a sink node which has major computational and power capabilities. Focused on applications such as Structural Health Monitoring, we propose a cooperative communication protocol that exploits the spatio-temporal correlations of the sensor measurements in order to save energy when transmitting the information to the sink node in a non-stationary environment. In addition to cooperative communications, the protocol is based on two well-studied adaptive filtering techniques, Least Mean Squares and Recursive Least Squares, which trade off computational complexity and reduction in the number of transmissions to the sink node. Finally, experiments with real acceleration measurements, obtained from the Canton Tower in China, are included to show the effectiveness of the proposed method.

Keywords

References

  1. Ampeliotis, D., Bogdanovic, N., Berberidis, K., Casciati, F. and AlSaleh, R. (2012), "Power-efficient wireless sensor reachback for SHM", Proceedings of the 6th International Conference of Association for Bridge Maintenance and Safety (IABMAS 2012), Lake Como, Italy.
  2. Barros, J., Peraki, C. and Servetto, S. (2004). "Efficient network architectures for sensor reachback", Proceedings of the 13th International Zurich Seminar on Communications (IZS 2004), Zurich, Switzerland.
  3. Barros, J. and Servetto, S. (2006). "Network information flow with correlated sources", IEEE T. Inform. Theory, 52(1), 155 -170. https://doi.org/10.1109/TIT.2005.860435
  4. Casciati, F., Alsaleh, R. and Fuggini, C. (2009). "Gps-based shm of a tall building: torsional effects", Proceedings of the 7th International Workshop on Structural Health Monitoring (IWSHM 2009), Stanford, CA, USA.
  5. Cui, S., Goldsmith, R. and Bahai, A. (2004), "Energy efficiency of MIMO and cooperative MIMO techniques in sensor networks", IEEE J. Sel. Areas Comm., 22(6), 1089- 1098. https://doi.org/10.1109/JSAC.2004.830916
  6. Hong, Y.W., Huang, W.J., Chiu, F.H. and Kuo, C.C. (2007), Cooperative communications in resource-constrained wireless networks, IEEE Signal Processing Magazine, March.
  7. Lynch, J.P. (2006), "A summary review of wireless sensors and sensor networks for structural health monitoring", Shock Vib. Dig., 38(2), 91-128. https://doi.org/10.1177/0583102406061499
  8. Nagayama, T., Moinzadeh, P., Mechitov, K., Ushita, M., Makihata, N., Ieiri, M., Agha, G., Spencer, J.B.F., Fujino, Y. and Seo, J. (2010), "Reliable multi-hop communication for structural health monitoring", Smart Struct. Syst., 6(5), 481-503. https://doi.org/10.12989/sss.2010.6.5_6.481
  9. Ni, Y.Q. et al. (2008), A benchmark problem for the structural health monitoring of highrise slender structures, http://www.cse.polyu.edu.hk/benchmark/index.htm.
  10. Ni, Y.Q., Xia, Y., Liao, W.Y. and Ko, J.M. (2009), "Technology innovation in developing the structural health monitoring system for guangzhou new tv tower", Struct. Control Health Monit., 16(1), 73-98. https://doi.org/10.1002/stc.303
  11. Sayed, A.H. (2008), Adaptive filters, John Wiley & Sons, Hoboken, NJ, USA.
  12. Stankovic, V., Stankovic, L. and Cheng, S. (2010), "Distributed source coding: Theory and applications", Proceedings of the 18th European Signal Processing Conference, (EUSIPCO 2010), Aalborg, Denmark.

Cited by

  1. The state of the art in structural health monitoring of cable-stayed bridges vol.6, pp.1, 2016, https://doi.org/10.1007/s13349-015-0115-x
  2. Layout optimization of wireless sensor networks for structural health monitoring vol.14, pp.1, 2014, https://doi.org/10.12989/sss.2014.14.1.039
  3. Modeling and harnessing sparse and low-rank data structure: a new paradigm for structural dynamics, identification, damage detection, and health monitoring vol.24, pp.1, 2017, https://doi.org/10.1002/stc.1851
  4. Building structural health monitoring using dense and sparse topology wireless sensor network vol.16, pp.4, 2015, https://doi.org/10.12989/sss.2015.16.4.607
  5. Data to decisions: Real-time structural assessment from sparse measurements affected by uncertainty vol.182, 2017, https://doi.org/10.1016/j.compstruc.2016.12.007
  6. Damage localization and quantification in gusset plates: A battery-free sensing approach vol.25, pp.6, 2018, https://doi.org/10.1002/stc.2158