DOI QR코드

DOI QR Code

Issues in structural health monitoring employing smart sensors

Nagayama, T.;Sim, S.H.;Miyamori, Y.;Spencer, B.F. Jr.

  • 투고 : 2006.08.01
  • 심사 : 2006.10.20
  • 발행 : 2007.07.25

초록

Smart sensors densely distributed over structures can provide rich information for structural monitoring using their onboard wireless communication and computational capabilities. However, issues such as time synchronization error, data loss, and dealing with large amounts of harvested data have limited the implementation of full-fledged systems. Limited network resources (e.g. battery power, storage space, bandwidth, etc.) make these issues quite challenging. This paper first investigates the effects of time synchronization error and data loss, aiming to clarify requirements on synchronization accuracy and communication reliability in SHM applications. Coordinated computing is then examined as a way to manage large amounts of data.

키워드

coordinated computing;data compression;distributed computing strategy;smart sensors;time synchronization;data loss;data aggregation

참고문헌

  1. Nagayama, T., Abe, M., Fujino, Y. and Ikeda, K. (2005), "Structural identification of a nonproportionally damped system and its application to a full-scale suspension bridge", J. Struct. Eng., 131(10), 1536-1545. https://doi.org/10.1061/(ASCE)0733-9445(2005)131:10(1536)
  2. Nagayama, T., Spencer, Jr., B. F., Agha, G. A. and Mechitov, K. A. (2006), "Model-based data aggregation for structural monitoring employing smart sensors", Proceedings of the Third International Conference on Networked Sensing Systems (INSS 2006), May 31- Jun 2, pp. 203-210.
  3. Nitta, Y., Nagayama, T., Spencer Jr., B. F. and Nishitani, A. (2005), "Rapid damage assessment for the structures utilizing smart sensor MICA2 MOTE", Proceedings of 5th Int. Workshop on Structural Health Monitoring, Stanford, CA., 283-290.
  4. 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
  5. Sohn, H., Farrar, C. R., Hemez, F. M., Shunk, D. D., Stinemates, D. W. and Nadler, B. R. (2001), "A review of structural health monitoring literature: 1996-2001", Los Alamos National Laboratory Report, LA-13976-MS.
  6. Spencer Jr., B. F., Ruiz-Sandval, M. E. and Kurata, N. (2004), "Smart sensing technology: opportunities and challenges", Struct. Control Health Monit., 11, 349-368. https://doi.org/10.1002/stc.48
  7. Ruiz-Sandoval, M. (2004), "Smart sensors for civil infrastructure systems", Ph.D. Dissertation, University of Notre Dame, IN.
  8. Ruiz-Sandoval, M., Nagayama, T. and Spencer, B. F. (2006), "Sensor development using Berkeley Mote platform", J. Earthq. Eng., 10(2), 289-309.
  9. Wang, Y., Lynch, J. P. and Law, K. H. (2005), "Wireless structural sensors using reliable communication protocols for data acquisition and interrogation", Proceedings of the 23rd International Modal Analysis Conference (IMAC XXIII), Orlando, FL, January 31-February 3.
  10. Wong, K. Y. (2004), "Instrumentation and health monitoring of cable-supported bridges", Struct. Control Health Monit., 11(2), 91-124. https://doi.org/10.1002/stc.33
  11. Doebling, S. W. and Farrar, C. R. (1999), "The state of the art in structural identification of constructed facilities", A report by American Society of Civil Engineers Committee on Structural Identification of Constructed Facilities.
  12. Elson, J., Girod, L. and Estrin, D. (2002), "Fine-grained network time synchronization using reference broadcasts", Proc. of the Fifth Symposium on Operating Systems Design and Implementation (OSDI 2002).
  13. Farrar, C. R. (2001), "Historical overview of structural health monitoring", Lecture Notes on Structural Health Monitoring using Statistical Pattern Recognition, Los Alamos Dynamics, Los Alamos, NM.
  14. Gao., Y. (2005), "Structural health monitoring strategies for smart sensor networks", PhD Dissertation, University of Illinois at Urbana-Champaign.
  15. Gros, X. E. (1997), NDT data fusion, Arnold, London, UK.
  16. Hollar, S. (2000), COTS Dust., Master's Thesis, University of California, Berkeley, CA.
  17. James, G. H., Carne, T. G. and Lauffer, J. P. (1993), "The natural excitation technique for modal parameter extraction from operating wind turbine", Report No. SAND92-1666, UC-261, Sandia National Laboratories, Sandia, NM.
  18. James, G. H., Carne, T. G., Lauffer, J. P. and Nord, A. R. (1992), "Modal testing using natural excitation", Proceedings of 10th Int. Modal Analysis Conference, San Diego, CA.
  19. Kottapalli, V. A., Kiremidjian, A. S., Lynch, J. P., Carryer, E., Kenny, T. W., Law, K. H. and Lei, Y. (2003), "Twotiered wireless sensor network architecture for structural health monitoring", Smart Struct. Mater., San Diego, CA, March 3-6, Proceedings of the SPIE, 5057, 8-19.
  20. Kurata, N., Spencer, B. F. Jr. and Ruiz-Sandoval, M. (2004), "Building risk monitoring using wireless sensor network", Proceedings of the 13th World Conference on Earthquake Engineering, August 2-6, Vancouver, BC, Cananda.
  21. Lei, Y., Kiremidjian, S., Nair, K. K., Lynch, J. P. and Law, K. H. (2004), "Algorithms for time synchronization of wireless structural monitoring sensors", Earthq. Eng. Struct. Dyn., 34, 555-573.
  22. Lynch, J. P., Wang, Y., Law, K. H., Yi, J.-H., Lee, C. G. and Yun, C. B. (2005), "Validation of a large-scale wireless structural monitoring system on the Geumdang bridge", Proceedings of the Int. Conference on Safety and Structural Reliability, Rome, Italy.
  23. 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
  24. Mechitov, K., Kim, W., Agha, G., and Nagayama, T. (2004), "High-frequency distributed sensing for structure monitoring", Proceedings of 1st Int. Workshop on Networked Sensing Systems, 101-105
  25. Nagayama, T., Ruiz-Sandoval, M., Spencer Jr., B. F., Mechitov, K. A. and Agha, G. A. (2004), "Wireless strain sensor development for civil infrastructure", Proceedings of 1st Int. Workshop on Networked Sensing Systems, Tokyo, Japan, 97-100.
  26. Allemang, R. J. (2003), "The modal assurance criterion-twenty years of use and abuse", Sound Vib., 37(8), 14-23.
  27. Arici, Y. and Mosalam, K. M. (2003), "Modal analysis of a densely instrumented building using strong motion data", Proceedings of the International Conference on Applications of Statistics and Probability in Civil Engineering, San Francisco, CA, June 6-9, 419-426.
  28. Bendat, J. S. and Piersol, A. G. (2000), Random Data: Analysis and Measurement Procedures, John Wiley and Sons, Inc. New York, NY.
  29. Bernal, D. (2000), "Extracting flexibility matrices from state-space realization", COST F3 Conf., Madrid, Spain, 127-135.
  30. Bernal, D. (2002), "Load vectors for damage localization", J. Eng. Mech., 128(1), 7-14. https://doi.org/10.1061/(ASCE)0733-9399(2002)128:1(7)
  31. Casciati, F., Faraveli, L. and Borghetti, F. (2003), "Wireless links between sensor-device control stations in long span bridges", Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures, Proceedings of the SPIE, Vol. 5057, San Diego, CA, pp. 1-7
  32. Celebi, M. (2002), "Seismic instrumentation of buildings (with emphasis on federal buildings)", Special GSA/USGS Project, an administrative report, United States Geological Survey, Menlo Park, CA.
  33. Crossbow Technology, Inc. http://www.xbow.com.
  34. Doebling, S. W., Farrar, C. R., Prime, M. B. and Shevitz, D. W. (1996), "Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review", LA-13070-MS.
  35. Doebling, S. W., Farrar, C. R., and Prime, M. B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Digest, 30(2), 91-105. https://doi.org/10.1177/058310249803000201

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