DOI QR코드

DOI QR Code

Clump interpolation error for the identification of damage using decentralized sensor networks

  • Received : 2020.06.06
  • Accepted : 2020.10.02
  • Published : 2021.02.25

Abstract

Recent developments in the field of smart sensing systems enable performing simple onboard operations which are increasingly used for the decentralization of complex procedures in the context of vibration-based structural health monitoring (SHM). Vibration data collected by multiple sensors are traditionally used to identify damage-sensitive features (DSFs) in a centralized topology. However, dealing with large infrastructures and wireless systems may be challenging due to their limited transmission range and to the energy consumption that increases with the complexity of the sensing network. Local DSFs based on data collected in the vicinity of inspection locations are the key to overcome geometric limits and easily design scalable wireless sensing systems. Furthermore, the onboard pre-processing of the raw data is necessary to reduce the transmission rate and improve the overall efficiency of the network. In this study, an effective method for real-time modal identification is used together with a local approximation of a damage feature, the interpolation error, to detect and localize damage due to a loss of stiffness. The DSF is evaluated using the responses recorded at small groups of sensors organized in a decentralized topology. This enables the onboard damage identification in real time thereby reducing computational effort and memory allocation requirements. Experimental tests conducted using real data confirm the robustness of the proposed method and the potential of its implementation onboard decentralized sensor networks.

Keywords

Acknowledgement

The authors would like to thank the Vienna Consulting Engineers (VCE) company for providing the data recorded during the experimental campaign carried out on the S101 Bridge.

References

  1. Avci, O., Abdeljaber, O., Kiranyaz, S., Hussein, M. and Inman, D.J. (2018), "Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks", J. Sound Vib., 424, 158-172. https://doi.org/10.1016/j.jsv.2018.03.008
  2. Brincker, R. and Ventura, C.E. (2015), Introduction to Operational Modal Analysis, John Wiley & Sons, Ltd.
  3. Daubechies, I. (1992), Ten Lectures on Wavelets.
  4. Dohler, M., Hille, F., Mevel, L. and Rucker, W. (2014), "Structural health monitoring with statistical methods during progressive damage test of S101 Bridge", Eng. Struct., 69, 183-193. https://doi.org/10.1016/j.engstruct.2014.03.010
  5. Domaneschi, M., Limongelli, M.P. and Martinelli, L. (2013a), "Multi-site damage localization in a suspension bridge via aftershock monitoring", Int. J. Earthq. Eng., 30(3), 56-72.
  6. Domaneschi, M., Limongelli, M.P. and Martinelli, L. (2013b), "Vibration based damage localization using MEMS on a suspension bridge model", Smart Struct. Syst., Int. J., 12(6), 679-694. http://dx.doi.org/10.12989/sss.2013.12.6.679
  7. Gabor, D. (1946), "Theory of communication. Part 1: The analysis of information", J. Inst. Elect. Engr. - Part III: Radio and Commu. Eng., 93(26), 429-441. https://doi.org/10.1049/ji-3-2.1946.0074
  8. Gao, Y., Spencer, B.F. and Ruiz-Sandoval, M. (2006), "Distributed computing strategy for structural health monitoring", Struct. Control Health Monitor., 13(1), 488-507. https://doi.org/10.1002/stc.117
  9. Giordano, P.F. and Limongelli, M.P. (2020), "Response-based time-invariant methods for damage localization on a concrete bridge", Struct. Concrete, 21(4), 1254-1271. https://doi.org/10.1002/suco.202000013
  10. Iacovino, C., Ditommaso, R., Ponzo, F.C. and Limongelli, M.P. (2018), "The Interpolation Evolution Method for damage localization in structures under seismic excitation", Earthq. Eng. Struct. Dyn., 47(10), 2117-2136. https://doi.org/10.1002/eqe.3062
  11. Jang, S., Jo, H., Cho, S., Mechitov, K., Rice, J.A., Sim, S.H., Jung, H.J., Yun, C.B., Spencer, B.F. and Agha, G. (2010), "Structural health monitoring of a cable-stayed bridge using smart sensor technology: Deployment and evaluation", Smart Struct. Syst., Int. J., 6(5-6), 439-459. https://doi.org/10.12989/sss.2010.6.5_6.439
  12. Kaya, Y. and Safak, E. (2015), "Real-time analysis and interpretation of continuous data from structural health monitoring (SHM) systems", Bull. Earthq. Eng., 13(3), 917-934. https://doi.org/10.1007/s10518-014-9642-9
  13. Kijewski, T. and Kareem, A. (2003), "Wavelet transforms for system identification in civil engineering", Comput.-Aided Civil Infrastruct. Eng., 18(5), 339-355. https://doi.org/10.1111/1467-8667.t01-1-00312
  14. Klepka, A. and Uhl, T. (2014), "Identification of modal parameters of non-stationary systems with the use of wavelet based adaptive filtering", Mech. Syst. Signal Process., 47(1-2), 21-34. https://doi.org/10.1016/j.ymssp.2013.09.001
  15. Li, J., Su, M. and Fan, L. (2003), "Natural frequency of railway girder bridges under vehicle loads", J. Bridge Eng., 8(4), 199-203. https://doi.org/10.1061/(ASCE)1084-0702(2003)8:4(199)
  16. Limongelli, M.P. (2010), "Frequency response function interpolation for damage detection under changing environment", Mech. Syst. Signal Process., 24(8), 2898-2913. https://doi.org/10.1016/j.ymssp.2010.03.004
  17. Limongelli, M.P. (2014), "Seismic health monitoring of an instrumented multistory building using the interpolation method", Earthq. Eng. Struct. Dyn., 43(11), 1581-1602. https://doi.org/10.1002/eqe.2411
  18. Long, J. and Buyukozturk, O. (2017), "Decentralised one-class kernel classification-based damage detection and localisation", Struct. Control Health Monitor., 24(6), 1-22. https://doi.org/10.1002/stc.1930
  19. Nagarajaiah, S. and Basu, B. (2009), "Output only modal identification and structural damage detection using time frequency & wavelet techniques", Earthq. Eng. Eng. Vib., 8(4), 583-605. https://doi.org/10.1007/s11803-009-9120-6
  20. Nagayama, T., Spencer, B.F. and Rice, J.A. (2009), "Autonomous decentralized structural health monitoring using smart sensors", Struct. Control Health Monitor., 16(7-8), 842-859. https://doi.org/10.1002/stc.352
  21. Nguyen, K.V. (2013), "Comparison studies of open and breathing crack detections of a beam-like bridge subjected to a moving vehicle", Eng. Struct., 51, 306-314. https://doi.org/10.1016/j.engstruct.2013.01.018
  22. Pakrashi, V., O'Connor, A. and Basu, B. (2010), "Effect of tuned mass damper on the interaction of a quarter car model with a damaged bridge", Struct. Infrastruct. Eng., 6(4), 409-421. https://doi.org/10.1080/15732470701816850
  23. Quqa, S., Landi, L. and Diotallevi, P.P. (2020), "Instantaneous modal identification under varying structural characteristics: A decentralized algorithm", Mech. Syst. Signal Process., 142, 106750. https://doi.org/10.1016/j.ymssp.2020.106750
  24. Quqa, S., Landi, L. and Diotallevi, P.P. (2021), "Modal assurance distribution of multivariate signals for modal identification of time-varying dynamic systems", Mech. Syst. Signal Process., 148, 107136. https://doi.org/10.1016/j.ymssp.2020.107136
  25. Rice, J.A., Mechitov, K., Sim, S.H., Nagayama, T., Jang, S., Kim, R., Spencer, B.F., Agha, G. and Fujino, Y. (2010), "Flexible smart sensor framework for autonomous structural health monitoring", Smart Struct. Syst., Int. J., 6(5-6), 423-438. https://doi.org/10.12989/sss.2010.6.5_6.423
  26. Siringoringo, D.M., Fujino, Y. and Nagayama, T. (2013), "Dynamic characteristics of an overpass bridge in a full-scale destructive test", J. Eng. Mech., 139(6), 691-701. https://doi.org/10.1061/%28ASCE%29EM.1943-7889.0000280
  27. Spiridonakos, M.D. and Fassois, S.D. (2009), "Parametric identification of a time-varying structure based on vector vibration response measurements", Mech. Syst. Signal Process., 23(6), 2029-2048. https://doi.org/10.1016/j.ymssp.2008.11.004
  28. Stockwell, R.G. (1996), "Localization of the complex spectrum: the s transform", IEEE Transact. Signal Process., 44(4), 993. https://doi.org/10.1109/78.492555
  29. VCE, Vienna Consulting Engineers (2009), Progressive damage test S101 - Flyover reibersdorf, Report nr. 08/2308.
  30. Vetterli, M. and Kovacevic, J. (1995), Wavelets and Subband Coding, Prentice Hall Ptr, Englewood Cliffs, NJ, USA.
  31. Wenzel, H. and Pichler, D. (2005), Ambient Vibration Monitoring, John Wiley and Sons Ltd.

Cited by

  1. Statistical Approach for Vibration-Based Damage Localization in Civil Infrastructures Using Smart Sensor Networks vol.6, pp.2, 2021, https://doi.org/10.3390/infrastructures6020022
  2. On the Effectiveness of Vibration-Based Monitoring for Integrity Management of Prestressed Structures vol.6, pp.12, 2021, https://doi.org/10.3390/infrastructures6120171