Smart Structures and Systems

  • 제22권6호
  • /
  • Pages.711-725
  • /
  • 2018
  • /
  • 1738-1584(pISSN)
  • /
  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Detection of nonlinear structural behavior using time-frequency and multivariate analysis

  • Prawin, J. (Academy of Scientific and Innovative Research, CSIR-Structural Engineering Research Centre, CSIR Campus) ;
  • Rao, A. Rama Mohan (Academy of Scientific and Innovative Research, CSIR-Structural Engineering Research Centre, CSIR Campus)
  • 투고 : 2018.03.22
  • 심사 : 2018.09.29
  • 발행 : 2018.12.25
⟨ 이전 논문 다음 논문 ⟩

초록

Most of the practical engineering structures exhibit nonlinearity due to nonlinear dynamic characteristics of structural joints, nonlinear boundary conditions and nonlinear material properties. Hence, it is highly desirable to detect and characterize the nonlinearity present in the system in order to assess the true behaviour of the structural system. Further, these identified nonlinear features can be effectively used for damage diagnosis during structural health monitoring. In this paper, we focus on the detection of the nonlinearity present in the system by confining our discussion to only a few selective time-frequency analysis and multivariate analysis based techniques. Both damage induced nonlinearity and inherent structural nonlinearity in healthy systems are considered. The strengths and weakness of various techniques for nonlinear detection are investigated through numerically simulated two different classes of nonlinear problems. These numerical results are complemented with the experimental data to demonstrate its suitability to the practical problems.

키워드

참고문헌

  1. Bae, S.H., Jeong, W.B., Cho, J.R. and Lee, S.H. (2017), "Transient response of vibration systems with viscous-hysteretic mixed damping using Hilbert transform and effective eigenvalues", Smart Struct. Syst., 20(3), 263-272. https://doi.org/10.12989/SSS.2017.20.3.263
  2. Cammarata, M., Rizzo, P., Dutta, D. and Sohn, H. (2010), "Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides", Smart Struct. Syst., 6(4), 349-362. https://doi.org/10.12989/sss.2010.6.4.349
  3. Casciati, F. and Faravelli, L. (2016), "Dynamic transient analysis of systems with material nonlinearity: a model order reduction approach", Smart Struct. Syst., 18(1), 1-16. https://doi.org/10.12989/sss.2016.18.1.001
  4. Feldman, M. (2011), "Hilbert Transform Applications in Mechanical Vibration", Wiley-Interscience, New York, March.
  5. Giannini, O., Casini, P. and Vestroni, F. (2013), "Nonlinear harmonic identification of breathing cracks in beams", Comput. Struct., 129, 166-177. https://doi.org/10.1016/j.compstruc.2013.05.002
  6. Goggins, J., Broderick, B.M., Basu, B. and Elghazouli, A.Y. (2007), "Investigation of the seismic response of braced frames using wavelet analysis", Struct. Control Health Monit., 14, 627-648. https://doi.org/10.1002/stc.180
  7. Gokhale, M.Y. and Khanduja, D.K. (2010), "Time domain signal analysis using wavelet packet decomposition approach", Int. J. Commun. Network Syst. Sci., 3, 321.
  8. Golub, G.H. and Loan, C.F.V. (2012), "Matrix computations", 3, (JHU Press).
  9. Hasselman, T.K., Anderson, M.C. and Gan, W.E.N.S.H.U.I. (1998), "Principal components analysis for nonlinear model correlation, updating and uncertainty evaluation", Proceedings of the 16th international modal analysis conference , 3243, 644.
  10. Hickey, D., Worden, K., Platten, M.F., Wright, J.R. and Cooper, J. E. (2009), "Higher-order spectra for identification of nonlinear modal coupling", Mech. Syst. Signal Pr., 23, 1037-1061. https://doi.org/10.1016/j.ymssp.2008.10.008
  11. Hot, A., Kerschen, G., Foltete, E. and Cogan, S. (2012), "Detection and quantification of non-linear structural behaviour using principal component analysis", Mech. Syst. Signal Pr., 26, 104-116. https://doi.org/10.1016/j.ymssp.2011.06.006
  12. http://institute.lanl.gov/ei/software-and-data/data
  13. Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C. and Liu, H.H. (1998), "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Proceedings of the Royal Society of London A: mathematical, physical and engineering sciences, 454, 903-995. https://doi.org/10.1098/rspa.1998.0193
  14. Lim, H.J., Kim, Y., Sohn, H., Jeon, I. and PLiu, P. (2017), "Reliability improvement of nonlinear ultrasonic modulation based fatigue crack detection using feature-level data fusion", Smart Struct. Syst., 20(6), 683-696 https://doi.org/10.12989/SSS.2017.20.6.683
  15. Kerschen, G., Boe, P.D., Golinval, J.C. and Worden, K. (2004), "Sensor validation using principal component analysis", Smart Mater. Struct., 14, 36-42.
  16. Kerschen, G., Worden, K., Vakakis, A.F. and Golinval, J.C. (2006), "Past, present and future of nonlinear system identification in structural dynamics", Mech. Syst. Signal Pr., 20, 505-592. https://doi.org/10.1016/j.ymssp.2005.04.008
  17. Khoshnoudian, F. and Talaei, S. (2017), "A new damage index using FRF data, 2D-PCA method and pattern recognition techniques", Int. J. Struct. Stab. Dynam., 17(8), 1750090. https://doi.org/10.1142/S0219455417500900
  18. Khoshnoudian, F. and Bokaeian, V. (2017), "Damage detection in plate structures using frequency response function and 2DPCA", Smart Struct. Syst., 20(4), 427-440. https://doi.org/10.12989/sss.2017.20.4.427
  19. Li, L., Qin, H. and Niu, Y. (2017), "Wavelet-based system identification for a nonlinear experimental model", Smart Struct. Syst., 20(4), 415-426. https://doi.org/10.12989/sss.2017.20.4.415
  20. Nagarajaiah, S. and Yang, Y. (2015), "Blind modal identification of output-only non-proportionally-damped structures by time-frequency complex independent component analysis", Smart Struct. Syst., 15(1), 81-97. https://doi.org/10.12989/sss.2015.15.1.081
  21. Pai, P.F., Nguyen, B.A. and Sundaresan, M.J. (2013), "Nonlinearity identification by time-domain-only signal processing", Int. J. Nonlinear Mech., 54, 85-98. https://doi.org/10.1016/j.ijnonlinmec.2013.04.002
  22. Prawin, J. and Rao, A.R.M. (2017), "Nonlinear identification of MDOF systems using Volterra series approximation", Mech. Syst. Signal Pr., 84, 58-77. https://doi.org/10.1016/j.ymssp.2016.06.040
  23. Prawin, J. and Rao, A.R.M. (2018a), "Nonlinear structural damage detection based on adaptive volterra filter model", Int. J. Struct. Stab. Dynam., 18(2), 1871003. https://doi.org/10.1142/S0219455418710037
  24. Prawin, J. and Rao, A.R.M. (2018b), "A method for detecting damage-induced nonlinearity in structures using weighting function augmented curvature approach", Struct. Health Monit., 147592171878 8801. https://doi.org/10.1177/1475921718788801
  25. Prawin, J., Rao, A.R.M. and Lakshmi, K. (2015), "Nonlinear identification of structures using ambient vibration data", Comput. Struct., 154, 116-134. https://doi.org/10.1016/j.compstruc.2015.03.013
  26. Prawin, J., Rao, A.R.M. and Lakshmi, K. (2016), "Nonlinear parametric identification strategy combining reverse path and hybrid dynamic quantum particle swarm optimization", Nonlinear Dynam., 84(2), 797-781 https://doi.org/10.1007/s11071-015-2528-9
  27. Rao, A.R.M., Kasireddy, V., Gopalakrishnan, N. and Lakshmi, K. (2015), "Sensor fault detection in structural health monitoring using null subspace-based approach", J. Intel. Mat. Syst. Str., 26(2), 172-185. https://doi.org/10.1177/1045389X14522534
  28. Robertson, A.N., Farrar. C.R. and Sohn, H. (2013), "An improved statistical classifier for identifying signal discontinuities using holder exponents", Proceedings of the 4th International Workshop on Structural Health Monitoring, (Stanford, CA) 13-17.
  29. Robertson, A., Farrar, C. and Sohn, H. (2003), "Singularity detection for structural health monitoring using holder exponents", Mech. Syst. Signal Pr., 17, 1163-1184. https://doi.org/10.1006/mssp.2002.1569
  30. Salehi, H., Burgueno, R., Das, S., Biswas, S. and Chakrabartty, S. (2016), "Structural health monitoring from discrete binary data through pattern recognition. Insights and Innovations in structural engineering", Mech. Comput., 1840-1845.
  31. Sapsis T.P., Quinn, D.D., Vakakis, A.F. and Bergman, L.A. (2012), "Effective stiffening and damping enhancement of structures with strongly nonlinear local attachments", J. Vib. Acoust., 134, 011016. https://doi.org/10.1115/1.4005005
  32. Shahverdi, S., Lotfollahi-Yaghin, M.A. and Asgarian, B. (2013), "Reduced wavelet component energy-based approach for damage detection of jacket type offshore platform", Smart Struct. Syst., 11(6), 589-604. https://doi.org/10.12989/sss.2013.11.6.589
  33. Sohn, H., Farrar, C.R., Hemez, F.M. and Czarnecki, J.J. (2002), "A review of structural health review of structural health monitoring literature", Proceedings of 3rd World Conference on Structural Control, Como, Italy, January.
  34. Wang, Z.C., Geng, D., Ren, W.X., Chen, G.D. and Zhang, G.F. (2015), "Damage detection of nonlinear structures with analytical mode decomposition and Hilbert transform", Smart Struct. Syst., 15(1), 1-13. https://doi.org/10.12989/sss.2015.15.1.001
  35. Worden, K. and Tomlinson, G.R. (2000), Nonlinearity in structural dynamics: detection, identification and modeling, (CRC Press).
  36. Worden, K., Farrar, C.R., Haywood, J. and Todd, M. (2008), "A review of nonlinear dynamics applications to structural health monitoring", Struct. Control Health Monit., 15, 540-567. https://doi.org/10.1002/stc.215
  37. Yan, A.M. and Golinval, J.C. (2006), "Null subspace-based damage detection of structures using vibration measurements", Mech. Syst. Signal Pr., 20, 611-626. https://doi.org/10.1016/j.ymssp.2005.04.010
  38. Zang, C. and Imregun, M. (2001), "Combined neural network and reduced FRF techniques for slight damage detection using measured response data", Arch. Appl. Mech., 71(8), 525-536. https://doi.org/10.1007/s004190100154

피인용 문헌

  1. Structural damage diagnosis under varying environmental conditions with very limited measurements vol.31, pp.5, 2020, https://doi.org/10.1177/1045389x19898268
  2. Investigation on modulation of multi-frequency ultrasonic waves in structures with quadratic nonlinearity vol.28, pp.1, 2021, https://doi.org/10.12989/sss.2021.28.1.043