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2012 | OriginalPaper | Buchkapitel

17. Advanced Frequency-Domain Modal Analysis for Dealing with Measurement Noise and Parameter Uncertainty

verfasst von : Mahmoud El-Kafafy, P. Guillaume, B. Peeters, F. Marra, G. Coppotelli

Erschienen in: Topics in Modal Analysis I, Volume 5

Verlag: Springer New York

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Abstract

The poly-reference Least Squares Complex Frequency-domain (pLSCF) estimator –commercially known as the LMS PolyMAX method- has introduced an improvement in the field of modal analysis. The main advantages are its computational speed and the very clear stabilization diagrams it yields even in the case of highly damped systems and noisy FRF measurements. Moreover, the numerical stability of the algorithm allows for a large-bandwidth and high-model order analysis and makes it suitable both for lowly- and highly-damped structures.

Regardless of the very clear stabilization diagrams, it has been observed that the damping estimates are not always reliable for highly damped modes when the FRFs are very noisy. In this paper, a two-step procedure is introduced to improve the damping estimates while maintaining the very clear stabilization diagrams. In the first step, a kind of smoothing is used to remove the noise from the data and in the second step; the pLSCF estimator is applied to the smoothed data resulting in improved (damping) estimates. In addition, the proposed procedure properly deals with uncertainty: the data variance due to measurement noise is taken into account to compute confidence bounds on the modal parameter estimates. The procedure is validated by means of simulated as well as experimental data. The presented procedure to process highly damped noisy vibration data leads to very accurate estimates in comparison to the traditional pLSCF approach.

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Bishop R, Gladwell G (1963) An investigation into the theory of resonance testing. Philos Trans R Soc Lond 255(A-1055):241–280MATH

Pendered J (1965) Theoretical investigation into the effects of close natural frequencies in resonance testing. J Mech Eng Sci 7(4):372–379CrossRef

Kennedy CC, Pancu CDP (1947) Use of vectors in vibration measurement and analysis. J Aeronaut Sci 14(11):603–625

Ibrahim S, Mikulcik E (1977) A method from the direct identification of vibration parameters from the free response. Shock Vib Bull 47(4):183–198

Juang JJ (1994) Applied system identification. Prentice-Hall, New JerseyMATH

Juang J-N, Pappa RS (1985) An eigensystem realization algorithm for modal parameter identification and model reduction. Guid Contr Dynam 8(5):620–627MATHCrossRef

Larimore WE (1994) The optimality of canonical variate identification by example. In: Proceedings of the SYSID’94, vol 2. Copenhagen, pp 151–156, 4–6 July 1994

Van Overschee P, De Moor B (1994) N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems. Automatica 30(1):75–93MathSciNetMATHCrossRef

Verhaegen M (1994) Identification of the deterministic part of MIMO state space models given in innovations from input–output data. Automatica 30(1):61–74MathSciNetMATHCrossRef

10.

Van Overschee P, De Moor B (1996) Subspace identification for linear systems: theory-implementation-application. Kluwer, DordrechtCrossRef

11.

LMS International (2005) The LMS theory and background book – analysis and design. Manual of Test. Lab Revision 5. LMS International, Leuven

12.

Brown DL, Allemang RJ, Zimmermann R, Mergeay R (1979) Parameter estimation techniques for modal analysis. SAE Technical Paper Series, No. 790221

13.

Vold H, Kundrat L, Rocklin GT, Russel R (1982) A multi-input modal estimation algorithm for mini computers. SAE Technical Paper series, No. 820194

14.

Hermans L, Van der Auweraer H (1999) Modal testing and analysis of structures under operational conditions: industrial applications. Mech Syst Signal Process 13(2):193–216CrossRef

15.

Leuridan J (1984) Some direct parameter model identification methods applicable for multiple input modal analysis. Ph.D. Thesis, Department of Mechanical and Industrial Engineering, University of Cincinnati, Ohio

16.

LMS International (1997) LMS CADA-X fourier monitor manual, Orlando

17.

Juang J-N, Pappa RS (1988) An eigensystem realization algorithm in the frequency domain for modal analysis. ASME Trans Vib Acoust Stress 110(24):24–29CrossRef

18.

Lembregts F (1988) Frequency domain identification for experimental multiple inputs modal analysis. Ph.D. Thesis, Department PMA, K.U. Leuven, Belgium

19.

Böswald M, Göge D, Füllekrug U, Govers Y (2006) A review of experimental modal analysis methods with respect to their applicability to test data of large aircraft. In: Proceedings of the international conference on noise and vibration engineering, Leuven, pp 2461–2481

20.

Levi EC (1959) Complex curve fitting. IEEE Trans Automat Contr 4(1):37–44

21.

Richardson MH, Formenti DL (1982) Parameter estimation from frequency response measurements using rational fraction polynomials. In: Proceedings of the 1st international modal analysis conference, Orlando, pp 167–181

22.

Richardson MH, Formenti DL (1985) Global curve fitting of frequency response measurements using the rational fraction polynomial method. In: Proceedings of the 3rd international modal analysis conference, Orlando, pp 390–397

23.

Van der Auweraer H, Leuridan J (1987) Multiple input orthogonal polynomial parameter estimation. Mech Syst Signal Process 1(3):259–272CrossRef

24.

Van der Auweraer H, Guillaume P, Verboven P, Vanlanduit S (2001) Application of a fast-stabilizing frequency domain parameter estimation method. ASME J Dynam Syst Meas Contr 123(4):651–658CrossRef

25.

Guillaume P, Verboven P, Vanlanduit PH, Van der Auweraer, Peeters B (2003) A poly-reference implementation of the least-squares complex frequency domain-estimator. In: Proceedings of the 21th international modal analysis conference, Kissimmee

26.

Pintelon R, Guillaume P, Schoukens J (1996) Measurement of noise (cross-) power spectra for frequency-domain system identification purposes: large-sample results. IEEE Trans Instrum Meas 45(1):12–20CrossRef

27.

Schoukens J, Pintelon R (1991) Identification of linear systems: a practical guide to accurate modeling. Pergamon Press, London

28.

Guillaume P (1992) Identification of multi-input multi-output systems using frequency-domain models. Ph.D. Thesis, Department ELEC, VUB, Brussels

29.

Van Hamme H, Pintelon R (1992) Application of the bootstrapped total least squares (BTLS) estimator in linear system identification, Signal processing VI: theories and applications, pp 731–734

30.

Guillaume P, Pintelon R, Schoukens J (1998) A weighted total least squares estimator for multivariable systems with nearly maximum likelihood properties. IEEE Trans Instrum Meas 47(4):818–822CrossRef

31.

Guillaume P, Verboven P, Vanlanduit S (1998) Frequency-domain maximum likelihood identification of modal parameters with confidence intervals. In: Proceedings of the 23rd international seminar on modal analysis, Leuven, pp 359–366

32.

Guillaume P (1996) Parametric identification of multivariable systems in the frequency-domain – a survey. In: Proceedings of the international conference on noise and vibration engineering (ISMA-21), vol 2. Leuven, pp 1069–1082

33.

Pintelon R, Schoukens J (2001) System identification: a frequency domain approach. IEEE Press, New JerseyCrossRef

34.

Guillaume P, Schoukens J, Pintelon R (1989) Sensitivity of roots to errors in the coefficient of polynomials obtained by frequency-domain estimation method. IEEE Trans Instrum Meas 38(6):1050–1056CrossRef

35.

Guillaume P, Pintelon R, Schoukens J (1995) Robust parametric transfer function estimation using complex logarithmic frequency response data. IEEE Trans Automat Contr 40(7):1180–1190MathSciNetMATHCrossRef

Titel: Advanced Frequency-Domain Modal Analysis for Dealing with Measurement Noise and Parameter Uncertainty
verfasst von: Mahmoud El-Kafafy
P. Guillaume
B. Peeters
F. Marra
G. Coppotelli
Verlag: Springer New York
Buch: Topics in Modal Analysis I, Volume 5
Print ISBN: 978-1-4614-2424-6

Electronic ISBN: 978-1-4614-2425-3

Copyright-Jahr: 2012
DOI: https://doi.org/10.1007/978-1-4614-2425-3_17

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