DOI QR코드

DOI QR Code

Vibration-based structural health monitoring using large sensor networks

  • Deraemaeker, A. (ULB, Active Structures Laboratory) ;
  • Preumont, A. (ULB, Active Structures Laboratory) ;
  • Reynders, E. (KUL, Department of Civil Engineering) ;
  • De Roeck, G. (KUL, Department of Civil Engineering) ;
  • Kullaa, J. (Aalto University School of Science and Technology) ;
  • Lamsa, V. (Aalto University School of Science and Technology) ;
  • Worden, K. (Department of Mechanical Engineering, University of Sheffield) ;
  • Manson, G. (Department of Mechanical Engineering, University of Sheffield) ;
  • Barthorpe, R. (Department of Mechanical Engineering, University of Sheffield) ;
  • Papatheou, E. (Department of Mechanical Engineering, University of Sheffield) ;
  • Kudela, P. (IFFM, Polish Academy of Science) ;
  • Malinowski, P. (IFFM, Polish Academy of Science) ;
  • Ostachowicz, W. (IFFM, Polish Academy of Science) ;
  • Wandowski, T. (IFFM, Polish Academy of Science)
  • Received : 2008.09.26
  • Accepted : 2009.08.01
  • Published : 2010.04.25

Abstract

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

Keywords

References

  1. Agogino, A.M. and Tumer, I. (2006), Integrated systems health monitoring using smart dust mote sensor network, Final Report to NASA AMES.
  2. Alvandi, A. and Cremona, C. (2006), "Assessment of vibration-based damage identification techniques", J. Sound Vib., 292, 179-202. https://doi.org/10.1016/j.jsv.2005.07.036
  3. Barthorpe, R.J., Worden, K. and Manson. G. (2008), "An investigation into the necessary model fidelity for SHM feature selection", Proceedings of the 4th European Workshop on Structural Health Monitoring, Krakow, Poland.
  4. Basseville, M., Abdelghani, M. and Benveniste, A. (2000), "Subspace-based fault detection algorithms for vibration monitoring", Automatica, 36, 101-109. https://doi.org/10.1016/S0005-1098(99)00093-X
  5. Boukerche, A., Chatzigiannakis, I. and Nikoletseas, S. (2006), "A new energy efficient and fault-tolerant protocol for data propagation in smart dust networks using varying transmission range", Comput. Commun., 29, 477-489. https://doi.org/10.1016/j.comcom.2005.01.013
  6. Deraemaeker, A. and Preumont, A. (2006), "Vibration based damage detection using large array sensors and spatial filters", Mech. Syst. Signal Pr., 20, 1615-1630. https://doi.org/10.1016/j.ymssp.2005.02.010
  7. Deraemaeker, A., Reynders, E., De Roeck, G. and Kullaa, J. (2008), "Vibration-based structural health monitoring using output-only measurements under changing environment", Mech. Syst. Signal Pr., 22, 34-56. https://doi.org/10.1016/j.ymssp.2007.07.004
  8. Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Digest., 30, 91-105. https://doi.org/10.1177/058310249803000201
  9. Grandt, A.F. (2003), Fundamentals of Structural Integrity: Damage Tolerant Design and Nondestructive Evaluation, John Wiley and Sons.
  10. Kullaa, J. (2002), "Elimination of environmental influences from damage-sensitive features in a structural health monitoring system", Proceedings of the 1st European Workshop on Structural Health Monitoring, Paris, France.
  11. Kullaa, J. (2003), "Damage detection of the Z24 bridge using control charts", Mech. Syst. Signal Pr., 17, 163-170. https://doi.org/10.1006/mssp.2002.1555
  12. Kullaa, J. (2007), "Sensor fault identification and correction in vibration-based multichannel structural health monitoring", Proceedings of the 6th International Workshop on Structural Health Monitoring, Stanford, CA.
  13. Kullaa, J. and Heine, T. (2007), "Feature comparison in structural health monitoring of a vehicle crane", Proceedings of the International Conference on Engineering Dynamics (ICED 2007), Algarve, Portugal.
  14. Lamsa, V. and Kullaa, J. (2007), "Nonlinear factor analysis in structural health monitoring to remove environmental effects", Proceedings of the 6th International Workshop on Structural Health Monitoring, Stanford, CA.
  15. LeClerc, J.R., Worden, K., Staszewski, W.J. and Haywood, J. (2007), "Impact detection in an aircraft composite panel -a neural-network approach", J. Sound Vib., 299, 672-682. https://doi.org/10.1016/j.jsv.2006.07.019
  16. Malinowski, P., Wandowski, T., Trendalova, I. and Ostachowicz, W. (2007), "Multi-phased array for damage localisation", Key Eng. Mater., 347, 77-82. https://doi.org/10.4028/www.scientific.net/KEM.347.77
  17. Manson, G., Worden, K. and Allman, D.J. (2003), "Experimental validation of a structural health monitoring methodology; Part III, damage location on an aircraft wing", J. Sound Vib., 259(2), 365-385. https://doi.org/10.1006/jsvi.2002.5169
  18. Montalvao, D., Maia, N.M.M. and Ribeiro, A.M.R. (2006), "A review of vibration-based structural health monitoring with special emphasis on composite materials", Shock Vib. Digest., 38, 295-324. https://doi.org/10.1177/0583102406065898
  19. Paget, C.A., Atherton, K. and O'Brien, E. (2004), "Damage assessment in a full-scale aircraft wing by modified acoustic emission", Proceedings of the 2nd European Workshop on Structural Health Monitoring, Munich, Germany.
  20. Papatheou, E., Worden, K., Manson, G. and Barthorpe, R.J. (2008), "The use of pseudo-faults for SHM feature selection and pattern recognition", Proceedings of the 4th European Workshop on Structural Health Monitoring, Krakow, Poland.
  21. Papatheou, E., Manson, G., Barthorpe, R.J. and Worden, K. (2009), "The use of pseudo-faults for novelty detection in SHM", J. Sound Vib., 329(12), 2349-2366.
  22. Peeters, B. (2000), System identification and damage detection in civil engineering, PhD Thesis, KU Leuven, Belgium.
  23. Peeters, B. and De Roeck, G. (1999), "Reference-based stochastic subspace identification for output-only modal analysis", Mech. Syst. Signal pr., 13, 855-878. https://doi.org/10.1006/mssp.1999.1249
  24. Rippengill, S., Worden, K. Holford, K.M. and Pullin, R. (2003), "Automatic classification of acoustic emission patterns", Strain, 39, 31-41. https://doi.org/10.1046/j.1475-1305.2003.00041.x
  25. Salawu, O.S. (1997), "Detection of structural damage through changes in frequency: a review", Eng. Struct., 19, 718-723. https://doi.org/10.1016/S0141-0296(96)00149-6
  26. Scruby, C.B. and Wadley, H.N.G. (1983), "An assessment of acoustic emission for nuclear pressure vessel monitoring", Prog. Nucl. Energy, 11(3), 275-297. https://doi.org/10.1016/0149-1970(83)90014-8
  27. Sohn, H. (2007), "Effects of environmental and operational variability on structural health monitoring", Phil. Trans. R. Soc. A: Mathematical, Physical and Engineering Sciences, 365, 539-560. https://doi.org/10.1098/rsta.2006.1935
  28. Sorenson, H.W. (1980), Parameter estimation. Principles and problems, Marcel Dekker, New York.
  29. Wandowski, T., Malinowski, P., Kudela, P. and Ostachowicz, W. (2007), "Lamb wave-based discontinuity localization", Proceedings of the III ECCOMAS Thematic Conference on Smart Structures and Materials, Gdansk, Poland.
  30. Worden, K., Manson, G. and Fieller, N.R.J. (2000), "Damage detection using outlier analysis", J. Sound Vib., 229, 647-667. https://doi.org/10.1006/jsvi.1999.2514

Cited by

  1. Stochastic DLV method for steel truss structures: simulation and experiment vol.14, pp.2, 2014, https://doi.org/10.12989/sss.2014.14.2.105
  2. Hybrid two-step method of damage detection for plate-like structures vol.23, pp.2, 2016, https://doi.org/10.1002/stc.1769
  3. The hybrid multivariate analysis method for damage detection vol.23, pp.1, 2016, https://doi.org/10.1002/stc.1758
  4. Comparison between coupled local minimizers method and differential evolution algorithm in dynamic damage detection problems vol.65, 2013, https://doi.org/10.1016/j.advengsoft.2013.06.001
  5. Control-structure interaction in piezoelectric deformable mirrors for adaptive optics vol.21, pp.6, 2010, https://doi.org/10.12989/sss.2018.21.6.777
  6. A damage localization method based on the singular value decomposition (SVD) for plates vol.22, pp.5, 2018, https://doi.org/10.12989/sss.2018.22.5.621
  7. Damage detection in truss bridges using transmissibility and machine learning algorithm: Application to Nam O bridge vol.26, pp.1, 2010, https://doi.org/10.12989/sss.2020.26.1.035
  8. Prediction error of Johansen cointegration residuals for structural health monitoring vol.160, pp.None, 2010, https://doi.org/10.1016/j.ymssp.2021.107847