DOI QR코드

DOI QR Code

Rapid-to-deploy reconfigurable wireless structural monitoring systems using extended-range wireless sensors

  • Kim, Junhee (Department of Civil and Environmental Engineering, University of Michigan) ;
  • Swartz, R. Andrew (Department of Civil and Environmental Engineering, Michigan Technological University) ;
  • Lynch, Jerome P. (Department of Civil and Environmental Engineering, University of Michigan) ;
  • Lee, Jong-Jae (Department of Civil and Environmental Engineering, Sejong University) ;
  • Lee, Chang-Geun (Structural Research Team, Expressway and Transportation Research Institute, Korea Expressway Corporation)
  • Received : 2009.11.07
  • Accepted : 2010.02.08
  • Published : 2010.07.25

Abstract

Wireless structural monitoring systems consist of networks of wireless sensors installed to record the loading environment and corresponding response of large-scale civil structures. Wireless monitoring systems are desirable because they eliminate the need for costly and labor intensive installation of coaxial wiring in a structure. However, another advantageous characteristic of wireless sensors is their installation modularity. For example, wireless sensors can be easily and rapidly removed and reinstalled in new locations on a structure if the need arises. In this study, the reconfiguration of a rapid-to-deploy wireless structural monitoring system is proposed for monitoring short- and medium-span highway bridges. Narada wireless sensor nodes using power amplified radios are adopted to achieve long communication ranges. A network of twenty Narada wireless sensors is installed on the Yeondae Bridge (Korea) to measure the global response of the bridge to controlled truck loadings. To attain acceleration measurements in a large number of locations on the bridge, the wireless monitoring system is installed three times, with each installation concentrating sensors in one localized area of the bridge. Analysis of measurement data after installation of the three monitoring system configurations leads to reliable estimation of the bridge modal properties, including mode shapes.

Keywords

References

  1. Bensky, A. (2004), Short-range Wireless Communication, Elsevier, Oxford, UK.
  2. Brinker, R., Zhang, L. and Andersen, P. (2001), "Modal identification of output-only systems using frequency domain decomposition", Smart Mater. Struct., 10(3), 441-445. https://doi.org/10.1088/0964-1726/10/3/303
  3. Cantieni, R. (1983), Dynamic Load Tests on Highway Bridges in Switzerland – 60 years of Experience, Report 211, Federal Laboratory for Testing of Materials, Switzerland.
  4. Ginsberg, J.H. (2001), Mechanical and Structural Vibrations : Theory and Applications, Wiley, New York, NY.
  5. Grini, D. (2006), CC2420 with External PA, Application Note 37, Texas Instruments, Dallas, TX.
  6. IEEE (2006), Standard for Information Technology - Telecommunications and Information Exchange between Systems - Local and Metropolitan Area Networks - Specific Requirements Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low Rate Wireless Personal Area Networks (LRWPANs), Available at http://standards.ieee.org/getieee802/802.15.html.
  7. Jones, J.D. and Pei, J.S. (2009), "Embedded algorithms within an FPGA to classify nonlinear single-degree-offreedom systems", IEEE Sens. J., 9(11), 1486-93. https://doi.org/10.1109/JSEN.2009.2019322
  8. Kijewski-Correa, T. and Su, S. (2009), "BRAIN: a bivariate data-driven approach to damage detection in multiscale wireless sensor networks", Smart Struct. Syst., 5(4), 415-426. https://doi.org/10.12989/sss.2009.5.4.415
  9. Kim, J., Lynch, J.P., Zonta, D., Yun, C.B. and Lee, J.J. (2009), "Modal analysis of the Yeondae Bridge using a reconfigurable wireless monitoring system", Proceedings of the 10th International Conference on Structural Safety and Reliability (ICOSSAR'09), Osaka, Japan, September.
  10. Koo, K.Y., Hong, J.Y., Park, H.J. and Yun, C.B. (2008), "Remotely controllable structural health monitoring systems for bridges using 3.5 generation mobile telecommunication technology", Proceedings of IABMAS 2008: Bridge Maintenance, Safety, Management, Health Monitoring and Informatics, Seoul, Korea, July.
  11. Lee, C.G., Lee, W.T., Yun, C.B. and Choi, J.S. (2004), Development of Integrated System for Smart Evaluation of Load Carrying Capacity of Bridges, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  12. Lee, J.J., Fukuda, Y., Shinozuka, M., Cho, S. and Yun, C.B. (2007), "Development and application of a visionbased displacement measurement system for structural health monitoring of civil structures," Smart Struct. Syst., 3(3), 373-384. https://doi.org/10.12989/sss.2007.3.3.373
  13. Lei, Y., Kiremidjian, A.S., Nair, K.K., Lynch, J.P. and Law, K.H. (2005), "Algorithms for time synchronization of wireless structural monitoring sensors", Earthq. Eng. Struct. D., 34(6), 555-573. https://doi.org/10.1002/eqe.432
  14. Lian, F.L., Moyne, J.R. and Tilbury, D.M. (2005), Network Protocols for Networked Control Systems, Handbook of Networked and Embedded Control Systems (Ed. D. Hristu-Varsakelis and W.S. Levine), Boston, MA.
  15. Lu, K.C., Wang, Y., Lynch, J.P., Loh, C.H., Chen, Y.J., Lin, P.Y. and Lee, Z.K. (2006), "Ambient vibration study of the Gi-Lu cable-stay bridge: application of wireless sensing units", Proceedings of the SPIE - The International Society for Optical Engineering, San Diego, CA, March.
  16. Lynch, J.P., Law, K.H., Kiremidjian, A.S., Carryer, E., Farrar, C.R., Sohn, H., Allen, D.W., Nadler, B. and Wait, J.R. (2004a), "Design and performance validation of a wireless sensing unit for structural monitoring applications", Struct. Eng. Mech., 17(3-4), 393-408. https://doi.org/10.12989/sem.2004.17.3_4.393
  17. Lynch, J.P., Sundararajan, A., Law, K.H., Kiremidjian, A.S. and Carryer, E. (2004b), "Embedding damage detection algorithms in a wireless sensing unit for attainment of operational power efficiency", Smart Mater. Struct., 13(4), 800-810. https://doi.org/10.1088/0964-1726/13/4/018
  18. Lynch, J.P., Wang, Y., Loh, K., Yi, J.H. and Yun, C.B. (2006), "Performance monitoring of the Geumdang Bridge using a dense network of high-resolution wireless sensors", Smart Mater. Struct., 15(6), 1561-1575. https://doi.org/10.1088/0964-1726/15/6/008
  19. Lynch, J.P. and Loh, K.J. (2006), "A summary review of wireless sensors and sensor networks for structural health monitoring", Shock Vib. Digest, 38(2), 91-128. https://doi.org/10.1177/0583102406061499
  20. Nagayama, T. and Spencer, B. F. (2007), Structural Health Monitoring using Smart Sensors, NSEL Report Series 001, http://hdl.handle.net/2142/3521.
  21. Oppenhiem, A.V. and Schafer, R.W. (1999), Discrete-time Signal Processing, New Jersey: Prentice-Hall Inc.
  22. 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), 89-101. https://doi.org/10.1061/(ASCE)1076-0342(2008)14:1(89)
  23. Peeters, B. and Ventura, C.E. (2003), "Comparative study of modal analysis techniques for bridge dynamic characterizes", Mech. Syst. Signal Pr., 17(5), 965-988. https://doi.org/10.1006/mssp.2002.1568
  24. Raghavendra, C.S., Sivalingam, K.M. and Znati, T.F. (2004), Wireless sensor networks, Springer, New York, NY.
  25. Rice, J.A., Mechitov, K.A., Spencer, B.F. and Agha, G.A. (2008), "A service-oriented architecture for structural health monitoring using smart sensors", Proceedings of the 14th World Conference on Earthquake Engineering, Beijing, China.
  26. Salawu, O.S. and Williams, C. (1995), "Review of full-scale dynamic testing of bridge structures", Eng. Struct., 17(2), 113-121. https://doi.org/10.1016/0141-0296(95)92642-L
  27. Shih, C.Y., Tsuei, Y.G., Allemang, R.J. and Brown, D.L. (1988), "Complex mode indication function and its applications to spatial domain parameter estimation", Mech. Syst. Signal Pr., 2(4), 367-377. https://doi.org/10.1016/0888-3270(88)90060-X
  28. Silicon Designs (2009), Model 2012 Analog Accelerometer Module, Data Sheet, Silicon Designs Inc., Issaquah, WA.
  29. Spencer, B.F., Ruiz-Sandoval, M.E. and Kurata, N. (2004), "Smart sensing technology: opportunities and challenges", Struct. Control Health Monit., 11(4), 349-368. https://doi.org/10.1002/stc.48
  30. Straser, E. and Kiremidjian, A.S. (1998), A Modular, Wireless Damage Monitoring System for Structures, Blume Earthquake Engineering Center Report No. 128, Stanford, CA.
  31. Swartz, R.A., Jung, D., Lynch, J.P., Wang, Y., Shi, D. and Flynn, M.P. (2005), "Design of a wireless sensor for scalable distributed in-network computation in a structural health monitoring system", Proceedings of the 5th International Workshop on Structural Health Monitoring, Stanford, CA, June.
  32. Swartz, R.A. and Lynch, J.P. (2009), "Strategic network utilization in a wireless structural control system for seismically excited structures", J. Struct. Eng.-ASCE, 135(5), 597-608. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000002
  33. Swartz, R.A., Zimmerman, A.T., Lynch, J.P., Rosario, J., Brady, T., Salvino, L. and Law, K.H. (2009), "Hybrid wireless hull monitoring system for naval combat vessels," Struct. Infrastruct. E., under review.
  34. Texas Instruments (2003), ADS8341 16-Bit, 4-Channel Serial Output Sampling Analog-to-Digital Converter, http://focus.ti.com/lit/ds/symlink/ads8341.pdf.
  35. Texas Instruments (2008), CC2420 2.4 GHz IEEE 802.15.4 / ZigBee-ready RF Transceiver, http://focus.ti.com/lit/ ds/symlink/cc2420.pdf.
  36. Wang, Y, Lynch, J.P. and Law, K.H. (2007), "A wireless structural health monitoring system with multithreaded sensing de-vices: design and validation", Struct. Infrastruct. E., 3(2), 103-120. https://doi.org/10.1080/15732470600590820
  37. Whelan, M.J. and Janoyan, K.D. (2009), "Design of a robust, high-rate wireless sensor network for static and dynamic structural monitoring", J. Intel. Mat. Syst. Str., 20(7), 849-863. https://doi.org/10.1177/1045389X08098768
  38. Yan, G., Dyke, S.J. and Song, W. (2009), "Structural damage localization with tolerance to large time synchronization errors in WSNs", Proceedings of the 2009 American Control Conference, St. Louis, MO, May.
  39. Zimmerman, A.T., Shiraishi, M., Swartz, R.A., Lynch, J.P. (2008), "Automated modal parameter estimation by parallel processing within wireless monitoring systems," J Infrastruct. Syst., 14(1), 102-113. https://doi.org/10.1061/(ASCE)1076-0342(2008)14:1(102)

Cited by

  1. Dynamic Reconfigurable Hub as a Stationary Node in a Hybrid Sensor Network vol.9, pp.6, 2013, https://doi.org/10.1155/2013/484359
  2. Truck-based mobile wireless sensor networks for the experimental observation of vehicle–bridge interaction vol.20, pp.6, 2011, https://doi.org/10.1088/0964-1726/20/6/065009
  3. Effects of measurement noise on modal parameter identification vol.21, pp.6, 2012, https://doi.org/10.1088/0964-1726/21/6/065008
  4. Resource-efficient wireless sensor network architecture based on bio-mimicry of the mammalian auditory system vol.26, pp.1, 2015, https://doi.org/10.1177/1045389X14521877
  5. A migration-based approach towards resource-efficient wireless structural health monitoring vol.27, pp.4, 2013, https://doi.org/10.1016/j.aei.2013.08.003
  6. A Recent Research Summary on Smart Sensors for Structural Health Monitoring vol.19, pp.3, 2015, https://doi.org/10.11112/jksmi.2015.19.3.010
  7. Experimental analysis of vehicle–bridge interaction using a wireless monitoring system and a two-stage system identification technique vol.28, 2012, https://doi.org/10.1016/j.ymssp.2011.12.008
  8. A low-noise, real-time, wireless data acquisition system for structural monitoring applications vol.21, pp.7, 2014, https://doi.org/10.1002/stc.1636
  9. Long-term performance assessment of the Telegraph Road Bridge using a permanent wireless monitoring system and automated statistical process control analytics vol.13, pp.5, 2017, https://doi.org/10.1080/15732479.2016.1171883
  10. Factors affecting wireless network communication in monitoring systems for steel bridges vol.2, pp.2, 2012, https://doi.org/10.1007/s13349-012-0019-y
  11. Proof of concept of wireless TERS monitoring vol.24, pp.12, 2017, https://doi.org/10.1002/stc.2026
  12. In-Situ Validation of a Wireless Data Acquisition System by Monitoring a Pedestrian Bridge vol.18, pp.1, 2015, https://doi.org/10.1260/1369-4332.18.1.97
  13. Development and full-scale dynamic test of a combined system of heterogeneous laser sensors for structural displacement measurement vol.25, pp.6, 2016, https://doi.org/10.1088/0964-1726/25/6/065015
  14. Embedding human annoyance rate models in wireless smart sensors for assessing the influence of subway train-induced ambient vibration vol.25, pp.10, 2016, https://doi.org/10.1088/0964-1726/25/10/105023
  15. Internet-Enabled Wireless Structural Monitoring Systems: Development and Permanent Deployment at the New Carquinez Suspension Bridge vol.139, pp.10, 2013, https://doi.org/10.1061/(ASCE)ST.1943-541X.0000609
  16. An Iterative Modal Identification Algorithm for Structural Health Monitoring Using Wireless Sensor Networks vol.29, pp.2, 2013, https://doi.org/10.1193/1.4000133
  17. Event-driven strain cycle monitoring of railway bridges using a wireless sensor network with sentinel nodes vol.24, pp.7, 2017, https://doi.org/10.1002/stc.1934
  18. Wireless structural control using stochastic bandwidth allocation and dynamic state estimation with measurement fusion vol.25, pp.2, 2018, https://doi.org/10.1002/stc.2104
  19. Reliable multi-hop communication for structural health monitoring vol.6, pp.5, 2010, https://doi.org/10.12989/sss.2010.6.5_6.481
  20. In-construction vibration monitoring of a super-tall structure using a long-range wireless sensing system vol.7, pp.2, 2010, https://doi.org/10.12989/sss.2011.7.2.083
  21. Autonomous evaluation of ambient vibration of underground spaces induced by adjacent subway trains using high-sensitivity wireless smart sensors vol.19, pp.1, 2017, https://doi.org/10.12989/sss.2017.19.1.001
  22. Organolead halide perovskites beyond solar cells: self-powered devices and the associated progress and challenges vol.2, pp.16, 2010, https://doi.org/10.1039/d1ma00377a