Smart Structures and Systems

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Layout optimization of wireless sensor networks for structural health monitoring

  • Jalsan, Khash-Erdene (Structural Engineering Research Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology) ;
  • Soman, Rohan N. (Department of Civil Engineering and Geomatics, Cyprus University of Technology) ;
  • Flouri, Kallirroi (Structural Engineering Research Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology) ;
  • Kyriakides, Marios A. (Department of Civil Engineering and Geomatics, Cyprus University of Technology) ;
  • Feltrin, Glauco (Structural Engineering Research Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology) ;
  • Onoufriou, Toula (Department of Civil Engineering and Geomatics, Cyprus University of Technology)
  • Received : 2014.03.10
  • Accepted : 2014.06.30
  • Published : 2014.07.25
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Abstract

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

Keywords

References

  1. Custodio, A.L., Emmerich, M. and Madeira, J. (2012), "Recent developments in derivative-free multiobjective optimization", Comput. Technol. Rev., 5(1), 1-30. https://doi.org/10.4203/ctr.5.1
  2. Deb, K., Pratap, A., Agarwal, S. and Meyarivan, T. (2002), "A fast and elitist multiobjective genetic algorithm: Nsga-ii", IEEE T. Evolut. Comput., 6(2), 182-197. https://doi.org/10.1109/4235.996017
  3. Egea-Lopez, E., Vales-Alonso, J., Martinez-Sala, A., Pavon-Mario, P. and Garcia-Haro, J. (2006), "Simulation scalability issues in wireless sensor networks", IEEE Commun.Mag., 44(7), 64-73.
  4. Feltrin, G., Meyer, J., Bischoff, R. and Motavalli, M. (2010), "Long-term monitoring of cable stays with a wireless sensor network", Struct. Infrastruct. E., 6(5), 535-548. https://doi.org/10.1080/15732470903068573
  5. Fu, T.S., Ghosh, A., Johnson, E.A. and Krishnamachari, B. (2012), "Energy-efficient deployment strategies in structural health monitoring using wireless sensor networks", Struct. Control Health Monit., 20(6), 971-986.
  6. Guo, H.Y., Zhang, L., Zhang, L.L. and Zhou, J.X. (2004), "Optimal placement of sensors for structural health monitoring using improved genetic algorithms", Smart Mater. Struct., 13(3), 528-534. https://doi.org/10.1088/0964-1726/13/3/011
  7. Huang, J., Liu, S., Xing, G., Zhang, H., Wang, J. and Huang, L. (2011), "Accuracy-aware interference modeling and measurement in wireless sensor networks", Proceedings of the 31st International Conference on Distributed Computing Systems (ICDCS).
  8. Iyer, A., Rosenberg, C. and Karnik, A. (2009), "What is the right model for wireless channel interference?", IEEE T. Wirel. Commun., 8(5), 2662-2671. https://doi.org/10.1109/TWC.2009.080720
  9. Jalsan, K.E., Flouri, K. and Feltrin, G. (2012), "Bi-objective layout optimization of a wireless sensor network for footbridge monitoring", Proceedings of the 6th International Conference on Bridge Maintenance, Safety and Management, Stresa, Italy, July.
  10. Jourdan, D.B. and de Weck, O.L. (2004), "Layout optimization for a wireless sensor network using a multi-objective genetic algorithm", Proceedings of the IEEE 59th Vehicular Technology Conference, Milan, Italy, May.
  11. Kammer, D.C. (1990), "Sensor placement for on-orbit modal identification and correlation of large space structures", Proceedings of the American Control Conference, San Diego, USA, May.
  12. Konak, A., Coit, D.W. and Smith, A.E. (2006), "Multi-objective optimization using genetic algorithms: a tutorial", Reliab. Eng. Syst. Safe., 91(9), 992-1007. https://doi.org/10.1016/j.ress.2005.11.018
  13. Krause, A., Guestrin, C., Gupta, A. and Kleinberg, J.M. (2006), "Near-optimal sensor placements: Maximizing information while minimizing communication cost", Proceedings of the 5th International Conference on Information Processing in Sensor Networks, Nashville, USA, May.
  14. Levine-West, M., Milman, M. and Kissil, A. (1996), "Mode shape expansion techniques for prediction - experimental evaluation", AIAA J., 34(4), 821-829. https://doi.org/10.2514/3.13145
  15. Levis, P., Lee, N., Welsh, M. and Culler, D.E. (2003), "Tossim: Accurate and scalable simulation of entire tinyos applications", Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, Los Angeles, USA, November.
  16. Li, B., Wang, D., Wang, F. and Ni, Y.Q. (2010), "High quality sensor placement for shm systems: Refocusing on application demands", Proceedings of the 29th Conference on Information Communications, San Diego, USA, March.
  17. Meo, M. and Zumpano, G. (2005), "On the optimal sensor placement techniques for a bridge structure", Eng. Struct., 27(10), 1488-1497. https://doi.org/10.1016/j.engstruct.2005.03.015
  18. Natarajan, S., Howells, H., Deka, D. and Walters, D. (2006), "Optimization of sensor placement to capture riser viv response", Proceedings of the 25th International Conference on Offshore Mechanics and Arctic Engineering, Hamburg, Germany, June.
  19. Pakzad, S.N., Fenves, G.L., Kim, S. and Culler, D.E. (2008), "Design and implementation of scalable wireless sensor network for structural monitoring", J. Infrastruct. Syst., 14(1), 89. https://doi.org/10.1061/(ASCE)1076-0342(2008)14:1(89)
  20. Rappaport, T.S. and Sandhu, S. (1994), "Radio-wave propagation for emerging wireless personal-communication systems", IEEE T. Anten. Propag., 36(5), 14-24.
  21. Rice, J.A., Mechitov, K.A., Sim, S.H., Spencer, B.F. and Agha, G.A. (2011), "Enabling framework for structural health monitoring using smart sensors", Struct. Control Health Monit., 18(5), 574-587. https://doi.org/10.1002/stc.386
  22. Shnayder, V., Hempstead, M., Chen, B., Allen, G.W. and Welsh, M. (2004), "Simulating the power consumption of large-scale sensor network applications", Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, Baltimore, USA, November.
  23. Sohrabi, K., Manriquez, B. and Pottie, G.J. (1999), "Near ground wideband channel measurement in 800-1000 mhz", Proceedings of the IEEE 49th Vehicular Technology Conference, Houston, USA, July.
  24. Soman, R.N., Onoufriou, T.O., Votsis, R., Chrysostomou, C.Z. and Kyriakides, M.A. (2014), "Multi-type, multi-sensor placement optimization for structural health monitoring of long span bridges", Smart Struct. Syst., 14(1), 1-9. https://doi.org/10.12989/sss.2014.14.1.001
  25. Younis, M. and Akkaya, K. (2008), "Strategies and techniques for node placement in wireless sensor networks: a survey", Ad Hoc Networks, 6(4), 621-625. https://doi.org/10.1016/j.adhoc.2007.05.003
  26. Zhang, Y., Antonsson, E.K. and Martinoli, A. (2008), "Evolutionary engineering design synthesis of on-board traffic monitoring sensors", Res. Eng. Des., 19(2-3), 113-125. https://doi.org/10.1007/s00163-008-0047-0

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