Skip to main content
Log in

Estimation of modal parameters by using the ratios of imaginary to real parts of frequency response functions

  • Original
  • Published:
Archive of Applied Mechanics Aims and scope Submit manuscript

Abstract

Experimental modal analysis is one of the key technologies in structural dynamics analysis. However, in cases involving extremely high or low modal damping, it is difficult to accurately identify all the modal parameters. In particular, for systems with extremely low damping, there may not be sufficient data to allow curve fitting in the vicinity of the resonant peaks. To overcome this difficulty, we propose a linear fit method of modal parameters on a new mapping plane. This method uses a basic equation linearized from the nonlinear equation of the frequency response function (FRF) by erasing the residue, which is a modal parameter. Then, the basic equation becomes linear on a mapping plane related to the ratios of the real and imaginary parts of the FRF. The linearized basic equation can identify the modal parameters of a vibration system with extremely low damping. It was observed that the influence of the measurement noise degrades the identification accuracy of the linear fit method. Consequently, it was confirmed that the identification accuracy deteriorates when data with low coherence and far from the natural frequency are used. Thus, a weighted least squares method using the coherence and Gaussian kernel function was proposed for the linear fit method. Finally, the modal parameters obtained using the proposed method and the conventional least-squares complex frequency (LSCF) method, from the FRF including noise, were compared, which indicated that the proposed method can produce estimation results with an accuracy comparable to that pertaining to the LSCF method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability

The raw/processed data required to reproduce these findings cannot be shared at this time as the data are a part of an ongoing study as well.

References

  1. Ewins, D.J.: Modal Testing: Theory and Practice. Research Studies Press, LTD, Baldock (2001)

    MATH  Google Scholar 

  2. Iiyama, K., Kurita, S., Motosaka, M., Chiba, K., Hiramatsu, H., Mitsuji, K.: Model identification of a heavily damaged nine-story steel-reinforced concrete building by ambient vibration measurement. J. Jpn. Ass. Earthq. Eng. 15(3), 1884–6246 (2015). https://doi.org/10.5610/jaee.15.3_78

    Article  Google Scholar 

  3. Hsu, T.Y., Shih, Y.C., Pham, Q.V.: Damage detection of a thin plate using modal curvature via macrostrain measurement. Earthq. Eng. Eng. Vib. 18(2), 409–424 (2019). https://doi.org/10.1007/s11803-019-0512-y

    Article  Google Scholar 

  4. Magalhaes, F., Cunha, A., Caetano, E.: Vibration based structural health monitoring of an arch bridge: from automated OMA to damage detection. Mech. Syst. Signal Process. 28, 212–228 (2012). https://doi.org/10.1016/j.ymssp.2011.06.011

    Article  Google Scholar 

  5. Navabian, N., Bozorgnasab, M., Taghipour, R., et al.: Damage identification in plate-like structure using mode shape derivatives. Arch. Appl. Mech. 86, 819–830 (2016). https://doi.org/10.1007/s00419-015-1064-x

    Article  Google Scholar 

  6. Kompalka, A.S., Reese, S., Bruhns, O.T.: Experimental investigation of damage evolution by data-driven stochastic subspace identification and iterative finite element model updating. Arch. Appl. Mech. 77, 559–573 (2007). https://doi.org/10.1007/s00419-007-0114-4

    Article  Google Scholar 

  7. Mottershead, J.E., Link, M., Friswell, M.I.: The sensitivity method in finite element model updating: a tutorial. Mech. Syst. Signal Process. 25(5), 2275–2296 (2011). https://doi.org/10.1016/j.ymssp.2010.10.012

    Article  Google Scholar 

  8. Basaga, H.B., Turker, T., Bayraktar, A.: A model updating approach based on design points for unknown structural parameters. Appl. Math. Model. 35(12), 5872–5883 (2011)

    Article  MathSciNet  Google Scholar 

  9. Sehgal, S., Kumar, H.: Structural dynamic model updating techniques: a state of the art review. Arch. Comput. Methods Eng. 23(3), 515–533 (2016)

    Article  Google Scholar 

  10. Torres, W., Almazan, J.L., Sandoval, C., Boroschek, R.: Operational modal analysis and FE model updating of the Metropolitan Cathedral of Santiago, Chile. Eng. Struct. 143, 169–188 (2017). https://doi.org/10.1007/s11831-015-9150-3

    Article  Google Scholar 

  11. Sun, W., Liu, R., Fan, Y.: Analytical modeling and damping optimization for a thin plate partially covered with hard coating. Arch. Appl. Mech. 88, 897–912 (2018). https://doi.org/10.1007/s00419-018-1348-z

    Article  Google Scholar 

  12. Ibrahim, S.R., Mikulcik, E.C.: A method for the direct identification of vibration parameters from the free response. Shock Vib. Bull. 147, 183–198 (1977)

    Google Scholar 

  13. Malekjafarian A., Brincker R., Ashory M.R., Khatibi M.M.: Modified Ibrahim time domain method for identification of closely spaced modes: experimental results. In: Topics on the Dynamics of Civil Structures, vol. 1, pp. 443–449. Springer, New York. (2012). https://doi.org/10.1007/978-1-4614-2413-0_44

  14. Lin, C.S.: Parametric estimation of systems with modal interference. Arch. Appl. Mech. 87(11), 1845–1857 (2017). https://doi.org/10.1007/s00419-017-1292-3

    Article  Google Scholar 

  15. Bagheri, M., Jafari, A.: Analytical and experimental modal analysis of nonuniformly ring-stiffened cylindrical shells. Arch. Appl. Mech. 75, 177–191 (2006). https://doi.org/10.1007/s00419-005-0429-y

    Article  MATH  Google Scholar 

  16. Yang, Y., Zhao, G., Ma, D., Xu, X.: Mode calculation and testing of a car body in white. Shock Vib. 18(1–2), 289–298 (2011). https://doi.org/10.3233/SAV-2010-0604

    Article  Google Scholar 

  17. Yam, L.H., Guan, D.H., Zhang, A.Q.: Three-dimensional mode shapes of a tire using experimental modal analysis. Exp. Mech. 40(3), 369–375 (2000). https://doi.org/10.1007/BF02326482

    Article  Google Scholar 

  18. Palanivelu, S., Narasimha, R.K.V., Ramarathnam, K.K.: Determination of rolling tyre modal parameters using finite element techniques and operational modal analysis. Mech. Syst. Signal Process. 64–65, 385–402 (2015). https://doi.org/10.1016/j.ymssp.2015.04.006

    Article  Google Scholar 

  19. Saito, A., Suzuki, H., Kuroishi, M., Nakai, H.: Efficient forced vibration reanalysis method for rotating electric machines. J. Sound Vib. 334, 388–403 (2015). https://doi.org/10.1016/j.jsv.2014.09.004

    Article  Google Scholar 

  20. Behnam, M.R., Khatibi, M.M., Malekjafarian, A.: An accurate estimation of frequency response functions in output-only measurements. Arch. Appl. Mech. 88, 837–853 (2018). https://doi.org/10.1007/s00419-018-1345-2

    Article  Google Scholar 

  21. Matsubara, M., Kawamura, S.: Parameter identification of a three-dimensional flexible ring-based model of a tire using experimental modal analysis. Int. J. Automot. Eng. 10(2), 133–138 (2019). https://doi.org/10.20485/jsaeijae.10.2_133

    Article  Google Scholar 

  22. Dobson, B.J.: A straight-line technique for extracting modal properties from frequency response data. Mech. Syst. Signal Process. 1(1), 29–40 (1987). https://doi.org/10.1016/0888-3270(87)90081-1

    Article  Google Scholar 

  23. Phillips, A.W., Allemang, R.J., Fladung, W.A.: The Complex Mode Indicator Function (CMIF) as a parameter estimation method. Proc. SPIE Int. Soc. Opt. Eng. 3243, 705–710 (1998)

    Google Scholar 

  24. Lembregts, F.F., Leuridan, J., Zang, L., Kanda, H.: Multiple input modal analysis of frequency response functions based on direct parameter identification. Proc. Int. Modal Anal. Conf. IMAC 4, 589–598 (1986)

    Google Scholar 

  25. Yoshimura, T., Nagamatsu, A.: Research on modal analysis (7th report, estimation of variance of the frequency response function). Trans. Jpn. Soc. Mech. Eng. Ser. C 54, 2514–2521 (1988). (in Japanese)

    Article  Google Scholar 

  26. Yoshimura, T.: Research on modal analysis (9th report, proposition of multireference curve-fittingbased on the maxima likelihood method—part 1). Trans. Jpn. Soc. Mech. Eng. Ser. C 56(523), 527–536 (1990). (in Japanese)

    Article  Google Scholar 

  27. Guillaume, P., Verboven, P., Vanlanduit, S.: Frequency-domain maximum likelihood identification of modal parameters with confidence intervals. In: Proceedings of the International Seminar on Modal Analysis, vol. 1, pp. 359–366. Katholieke Universiteit Leuven (1998)

  28. Auweraer, H.V., Guillaume, P., Verboven, P., Vanlanduit, S.: Application of a fast-stabilizing frequency domain parameter estimation method. J. Dyn. Sys. Meas. Control 123(3), 651–658 (2001)

    Article  Google Scholar 

  29. Peeters, B., Auweraer, H.V., Guillaume, P., Leuridan, J.: The PolyMAX frequency-domain method: a new standard for modal parameter estimation? Shock Vib. 113(3, 4), 395–409 (2004)

    Article  Google Scholar 

  30. Peeters, B., Auweraer, H.V.: PloyMAX: a revolution in operational modal analysis. In: 1st International Operational Modal Analysis Conference, pp. 26–27 (2005)

  31. Guillaume, P., Verboven, P., Vanlanduit, S., Auweraer, H.V., Peeters, B.: A ploy-reference implementation of the least-squares complex frequency-domain estimator. Proc. IMAC 21, 395–409 (2003)

    Google Scholar 

  32. Sitarz, P., Powalka, B.: Modal parameters estimation using ant colony optimization algorithm. Mech. Syst. Signal Process. 76–77, 531–554 (2016)

    Article  Google Scholar 

  33. Sitarz, P., Powalka, B.: Dual ant colony operational modal analysis parameter estimation method. Mech. Syst. Signal Process. 98, 231–267 (2018)

    Article  Google Scholar 

  34. Kawamura, S., Kato, Y., Harada, M., Minamoto, H.: Estimation of dynamic properties of a lightly damped element. In: Proceedings of Dynamics and Design Conference, vol. 322 (2013) (in Japanese)

  35. Kitahara, A., Yoshimura, T.: Modal identification of cylindrical shell using circumference reduction method. Trans. JSME (2015). https://doi.org/10.1299/transjsme.14-00461. (in Japanese)

    Article  Google Scholar 

  36. Kawamura, S., Kita, M., Matsubara, M., Ise, T.: Study of the effect of specimen size and frequency on the structural damping property of beam. Mech. Eng. J. (2016). https://doi.org/10.1299/mej.16-00446

    Article  Google Scholar 

  37. Matsubara, M., Kawamura, S., Ise, T.: Application of modal properties identification to multi-degrees-of-freedom system using simultaneous of the real and imaginary parts of frequency response function. Trans. JSME (2018). https://doi.org/10.1299/transjsme.17-00540. (in Japanese)

    Article  Google Scholar 

  38. Matsubara, M., Tajiri, D., Takehara, S., Kawamura, S.: Linear fit method for modal parameter estimation using the real and imaginary parts of frequency response function (Identification accuracy improvement based on weighted least square method). Trans. JSME (2019). https://doi.org/10.1299/transjsme.18-00433. (in Japanese)

    Article  Google Scholar 

  39. Yin, H.P.: A new theoretical basis for the bandwidth method and optimal power ratios for the damping estimation. Mech. Syst. Signal Process. 22(6), 1869–1881 (2008). https://doi.org/10.1016/j.ymssp.2008.01.011

    Article  Google Scholar 

  40. Srikanth, N., Gupta, M.: Damping characterization of magnesium based composites using an innovative circle-fit approach. Compos. Sci. Technol. 63(4), 559–568 (2003). https://doi.org/10.1016/S0266-3538(02)00231-2

    Article  Google Scholar 

  41. Elsalama, A.A., Gohary, M.A., El-Gamal, H.A.: Modal analysis on tire with respect to different parameters. Alex. Eng. J. 56(3), 345–357 (2017). https://doi.org/10.1016/j.aej.2016.09.022

    Article  Google Scholar 

  42. Zhang, G., Zang, C., Friswell, M.I.: Identification of weak nonlinearities in MDOF systems based on reconstructed constant response tests. Arch. Appl. Mech. 89, 2053–2074 (2019). https://doi.org/10.1007/s00419-019-01559-4

    Article  Google Scholar 

  43. Wang, S., Sato, H., Ohori, M.: New approaches to the modal analysis for machine tool structure. J. Eng. Ind. 106(1), 40–47 (1984)

    Article  Google Scholar 

Download references

Funding

None.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masami Matsubara.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Matsubara, M., Saito, A. & Kawamura, S. Estimation of modal parameters by using the ratios of imaginary to real parts of frequency response functions. Arch Appl Mech 91, 1179–1191 (2021). https://doi.org/10.1007/s00419-020-01817-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00419-020-01817-w

Keywords

Navigation