Structural Engineering and Mechanics

  • 제59권1호
  • /
  • Pages.187-207
  • /
  • 2016
  • /
  • 1225-4568(pISSN)
  • /
  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Operational modal analysis of structures by stochastic subspace identification with a delay index

  • Li, Dan (School of Civil Engineering, Hefei University of Technology) ;
  • Ren, Wei-Xin (School of Civil Engineering, Hefei University of Technology) ;
  • Hu, Yi-Ding (School of Information Engineering, Wuyi University) ;
  • Yang, Dong (School of Civil Engineering, Hefei University of Technology)
  • 투고 : 2015.05.03
  • 심사 : 2016.04.29
  • 발행 : 2016.07.10
⟨ 이전 논문 다음 논문 ⟩

초록

Practical ambient excitations of engineering structures usually do not comply with the stationary-white-noise assumption in traditional operational modal analysis methods due to heavy traffic, wind guests, and other disturbances. In order to eliminate spurious modes induced by non-white noise inputs, the improved stochastic subspace identification based on a delay index is proposed in this paper for a representative kind of stationary non-white noise ambient excitations, which have nonzero autocorrelation values near the vertical axis. It relaxes the stationary-white-noise assumption of inputs by avoiding corresponding unqualified elements in the Hankel matrix. Details of the improved stochastic subspace identification algorithms and determination of the delay index are discussed. Numerical simulations on a four-story frame and laboratory vibration experiments on a simply supported beam have demonstrated the accuracy and reliability of the proposed method in eliminating spurious modes under non-white noise ambient excitations.

키워드

과제정보

연구 과제 주관 기관 : Natural Science Foundation of China

참고문헌

  1. Araujo, I.G. and Laier, J.E. (2014), "Operational modal analysis using SVD of power spectral density transmissibility matrices", Mech. Syst. Signal Pr., 46(1), 129-145. https://doi.org/10.1016/j.ymssp.2014.01.001
  2. Brincker, R., Zhang, L.M. 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. Cooper, J.E., Desforges, M.J. and Wright, J.R. (1995), "Model parameter identification using an unknown coloured random input", Mech. Syst. Signal Pr., 9(6), 685-695. https://doi.org/10.1006/mssp.1995.0051
  4. De Roeck, G., Peeters, B. and Ren, W.X. (2000), "Benchmark study on system identification through ambient vibration measurements", Proceedings of the 18th International Modal Analysis Conference (IMAC XVIII), San Antonio, TX, USA.
  5. Devriendt, C., De Sitter, G., Vanlanduit, S. and Guillaume, P. (2009), "Operational modal analysis in the presence of harmonic excitations by the use of transmissibility measurements", Mech. Syst. Signal Pr., 23(3), 621-635. https://doi.org/10.1016/j.ymssp.2008.07.009
  6. Devriendt, C. and Guillaume, P. (2007), "The use of transmissibility measurements in output-only modal analysis", Mech. Syst. Signal Pr., 21(7), 2689-2696. https://doi.org/10.1016/j.ymssp.2007.02.008
  7. Dorvash, S. and Pakzad, S.N. (2012), "Effects of measurement noise on modal parameter identification", Smart Mater. Struct., 21(6), 065008. https://doi.org/10.1088/0964-1726/21/6/065008
  8. Goethals, I., Vanluyten, B. and De Moor, B. (2004), "Reliable spurious mode rejection using self learning algorithms", Proceedings of the International Conference on Noise and Vibration Engineering (ISMA 2004), Leuven, Belgium.
  9. Goursat, M. and Mevel, L. (2008), "Covariance subspace identification: numerical analysis of spurious mode stability", Proceedings of the 26th International Modal Analysis Conference (IMAC-XXVI), Orlando, US.
  10. Hassiotis, S. (1999), "Identification of damage using natural frequencies and system moments", Struct. Eng. Mech., 8(3), 285-297. https://doi.org/10.12989/sem.1999.8.3.285
  11. Jacobsen, N.J. (2005), "Identifying harmonic components in operational modal analysis", Proceedings of the 12th International Congress on Sound and Vibration (ICSV 12), Lisbon, Portugal.
  12. Li, D., Ren, W.X. and Hu, Y.D. (2011), "Output-only modal parameter identification based on augmented state space models", Proceedings of the 4th International Symposium on Innovation & Sustainability of Structures in Civil Engineering (ISISS 2011), Xiamen, China.
  13. Lisowski, W. (2001), "Classification of vibration modes in operational modal analysis", Proceedings of the International Conference on Structural System Identification, Kassel, Germany.
  14. Mevel, L., Benveniste, A., Basseville, M. and Goursat, M. (2002), "Blind subspace-based eigenstructure identification under nonstationary excitation using moving sensors", IEEE T. Signal Pr., 50(1), 41-48. https://doi.org/10.1109/78.972480
  15. Mohanty, P. and Rixen, D.J. (2004a), "A modified Ibrahim time domain algorithm for operational modal analysis including harmonic excitation", J. Sound Vib., 275(1), 375-390. https://doi.org/10.1016/j.jsv.2003.06.030
  16. Mohanty, P. and Rixen, D.J. (2004b), "Operational modal analysis in the presence of harmonic excitation", J. Sound Vib., 270(1-2), 93-109. https://doi.org/10.1016/S0022-460X(03)00485-1
  17. Mohanty, P. and Rixen, D.J. (2006), "Modified ERA method for operational modal analysis in the presence of harmonic excitations", Mech. Syst. Signal Pr., 20(1), 114-130. https://doi.org/10.1016/j.ymssp.2004.06.010
  18. Peeters, B. (2000), "System identification and damage detection in civil engineering", Ph.D. Dissertation, Katholieke Universiteit Leuven, Belgium.
  19. Peeters, B. and De Roeck, G. (2001), "Stochastic system identification for operational modal analysis: a review", J. Dyn. Syst., Meas., Control, ASME, 123(4), 659-667. https://doi.org/10.1115/1.1410370
  20. Ren, W.X., Zhao, T. and Harik, I.E. (2004), "Experimental and analytical modal analysis of steel arch bridge", J. Struct. Eng., ASCE, 130(7), 1022-1031. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:7(1022)
  21. Ren, W.X. and Zong, Z.H. (2004), "Output-only modal parameter identification of civil engineering structures", Struct. Eng. Mech., 17, 429-444. https://doi.org/10.12989/sem.2004.17.3_4.429
  22. Reynders, E. (2012), "System identification methods for (operational) modal analysis: review and comparison", Arch. Comput. Meth. E., 19(1), 51-124. https://doi.org/10.1007/s11831-012-9069-x
  23. Reynders, E., Pintelon, R. and De Roeck, G. (2008), "Uncertainty bounds on modal parameters obtained from stochastic subspace identification", Mech. Syst. Signal Pr., 22(4), 948-969. https://doi.org/10.1016/j.ymssp.2007.10.009
  24. Saeed, K., Mechbal, N., Coffignal, G. and Verge, M. (2008), "Recursive modal parameter estimation using output-only subspace identification for structural health monitoring", Proceedings of the 16th Mediterranean Conference on Control and Automation, IEEE, Ajaccio Corsica, France.
  25. Van der Auweraer, H. and Hermans, L. (1999), "Structural model identification from real operating conditions", J. Sound Vib., 33(1), 34-41.
  26. Van Overschee, P. and De Moor, B. (1996), Subspace Identification for Linear Systems: Theory, Implementation, Applications, Kluwer Academic Publishers, Netherlands.
  27. Yan, W.J. and Ren, W.X. (2013), "Use of continuous-wavelet transmissibility for structural operational modal analysis", J. Struct. Eng., ASCE, 139(9), 1444-1456. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000711
  28. Yi, J.H. and Yun, C.B. (2004), "Comparative study on modal identification methods using output-only information", Struct. Eng. Mech., 17(3), 445-466. https://doi.org/10.12989/sem.2004.17.3_4.445
  29. Yu, D.J. and Ren, W.X. (2005), "EMD-based stochastic subspace identification of structures from operational vibration measurements", Eng. Struct., 27(12), 1741-1751. https://doi.org/10.1016/j.engstruct.2005.04.016

피인용 문헌

  1. The harmonic probing method for output-only nonlinear mechanical systems vol.39, pp.9, 2017, https://doi.org/10.1007/s40430-017-0723-y
  2. Comparative analysis of different weight matrices in subspace system identification for structural health monitoring vol.271, 2017, https://doi.org/10.1088/1757-899X/271/1/012092
  3. Health Monitoring of Civil Infrastructures by Subspace System Identification Method: An Overview vol.10, pp.8, 2016, https://doi.org/10.3390/app10082786
  4. Application of the Subspace-Based Methods in Health Monitoring of Civil Structures: A Systematic Review and Meta-Analysis vol.10, pp.10, 2016, https://doi.org/10.3390/app10103607
  5. Experimental investigations on the cross-correlation function amplitude vector of the dynamic strain under varying environmental temperature for structural damage detection vol.39, pp.3, 2016, https://doi.org/10.1177/1461348418820237
  6. Two-Step Finite Element Model Tuning Strategy of a Bridge Subjected to Mining-Triggered Tremors of Various Intensities Based on Experimental Modal Identification vol.14, pp.8, 2021, https://doi.org/10.3390/en14082062
  7. A new SVD-based filtering technique for operational modal analysis in the presence of harmonic excitation and noise vol.510, pp.None, 2021, https://doi.org/10.1016/j.jsv.2021.116252