Abstract
In this paper, the recently-developed MLMM method (Maximum Likelihood estimation of a Modal Model) will be introduced and applied to challenging industrial cases. Specific about the method is that the well-established statistical concept of maximum likelihood estimation is applied to estimate directly a modal model based on measured Frequency Response Functions (FRFs). Due to the nature of this model, the optimal modal parameters are estimated using an iterative Gauss-Newton minimization scheme. The method is able to tackle some of the remaining challenges in modal analysis. For instance, in highly-damped cases (e.g. acoustic cavity modal analysis, trimmed body modal analysis) where it is needed to use a large amount of excitation locations to sufficiently excite the modes and to obtain a reliable modal model, the more classical modal parameter estimation methods sometimes fail to achieve a high-quality curve-fit of the measured FRF data. Due to the iterative minimization of the cost function, MLMM is able to estimate a model that very closely represents the measurements. Another benefit of the method is that additional constraints can be imposed to the model. For instance, it is possible to impose that real modes and participation factors are estimated and/or to impose that the estimated modal model is reciprocal (as prescribed by the modal theory). More classical modal parameter estimation methods have rarely the possibly to fully integrate these constraints and the obtained modal parameters are typically altered in a subsequent step to satisfy the desired realness and reciprocity constraints. It is obvious that this may lead to sub-optimal results, as for instance evidenced by a degradation of the quality of the fit between the identified modal model and the measurements. The applicability of MLMM to estimate a constrained modal model will be demonstrated using challenging industrial applications.
Keywords
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Pintelon, R., Schoukens, J.: System Identification: A Frequency Domain Approach. Wiley IEEE Press (2012)
Balmes, E.: Frequency domain identification of structural dynamics using the pole/residue parametrization. In: Proceedings of the 14th International Modal Analysis Conference, Dearborn, MI, USA, 1996
Heylen, W., Lammens, S., Sas, P.: Modal Analysis Theory and Testing. Katholieke Universiteit Leuven, Department Werktuigkunde, Heverlee (2016)
Snoeys, R., Sas, P., Heylen, W., Van der Auweraer, H.: Trends in experimental modal analysis. Mech. Syst. Signal Process. 1(1), 5–27 (1987)
Van der Auweraer, H.: Structural dynamics modeling using modal analysis: applications, trends and challenges. In: Proceedings of IEEE Instrumentation and Measurement Technology Conference, Budapest, Hungary, 2001
Tsuji, H., Maruyama, S., Yoshimura, T., Takahashi, E.: Experimental method extracting dominant acoustic mode shapes for automotive interior acoustic field coupled with the body structure. SAE Int. J. Passenger Cars Mech. Syst. 6(2), 1139–1146 (2013)
El-Kafafy, M., Peeters, B., Guillaume, P., De Troyer, T.: Constrained maximum likelihood modal parameter identification applied to structural dynamics. Mech. Syst. Signal Process. 72–73, 567–589 (2016)
Accardo, G., El-kafafy, M., Peeters, B., Bianciardi, F., Brandolisio, D., Janssens, K., Martarelli, M.: Experimental acoustic modal analysis of an automotive cabin. In: De Clerck, J. (ed.) Experimental Techniques, Rotating Machinery, and Acoustics, vol. 8, pp. 33–58. Springer International Publishing (2015)
Peeters, B., El-Kafafy, M., Accardo, G., Knechten, T., Janssens, K., Lau, J., Gielen, L.: Automotive cabin characterization by acoustic modal analysis. In: Proceedings of the JSAE Annual Congress, Japan, 2014
Yoshimura, T., Saito, M., Maruyama, S., Iba, S.: Modal analysis of automotive cabin by multiple acoustic excitation. In: Proceedings of ISMA2012-USD2012, Leuven, Belgium, 2012
El-Kafafy, M., De Troyer, T., Peeters, B., Guillaume, P.: Fast maximum-likelihood identification of modal parameters with uncertainty intervals: a modal model-based formulation. Mech. Syst. Signal Process. 37, 422–439 (2013)
El-kafafy, M., Accardo, G., Peeters, B., Janssens, K., De Troyer, T., Guillaume, P.: A fast maximum likelihood-based estimation of a modal model. In: Mains, M. (ed.) Topics in Modal Analysis, vol. 10, pp. 133–156. Springer International Publishing (2015)
Guillaume, P., Verboven, P., Vanlanduit, S.: Frequency-domain maximum likelihood identification of modal parameters with confidence intervals. In: Proceedings of the 23rd International Seminar on Modal Analysis, Leuven, Belgium, 1998
Hermans, L., Van der Auweraer, H., Guillaume, P.: A frequency-domain maximum likelihood approach for the extraction of modal parameters from output-only data. In: Proceedings of ISMA23, the International Conference on Noise and Vibration Engineering, Leuven, Belgium, 1998
Guillaume, P., Verboven, P., Vanlanduit, S., Van der Auweraer, H., Peeters, B.: A poly-reference implementation of the least-squares complex frequency domain-estimator. In: Proceedings of the 21st International Modal Analysis Conference (IMAC), Kissimmee (Florida), 2003
Peeters, B., Van der Auweraer, H., Guillaume, P., Leuridan, J.: The PolyMAX frequency-domain method: a new standard for modal parameter estimation? Shock Vib. 11(3–4), 395–409 (2004)
Van der Auweraer, H., Liefooghe, C., Wyckaert, K., Debille, J.: Comparative study of excitation and parameter estimation techniques on a fully equipped car. In: Proceedings of the International Modal Analysis Conference (IMAC), Kissimmee, FL, USA, 1993
El-kafafy, M., Guillaume, P., Peeters, B.: Modal parameter estimation by combining stochastic and deterministic frequency-domain approaches. Mech. Syst. Signal Process. 35(1–2), 52–68 (2013)
Peeters, B., El-Kafafy, M., Guillaume, P.: The new PolyMAX Plus method: confident modal parameter estimation even in very noisy cases. In: Proceedings of the International Conference on Noise and Vibration Engineering (ISMA), Leuven, Belgium, 2012
Tsuji, H., Maruyama, S., Yoshimura, T., Takahashi, E.: Experimental method extracting dominant acoustic mode shapes for automotive interior acoustic field coupled with the body structure. J. Passenger Cars Mech. Syst. 6(2), 1139–1146 (2013)
Accardo, G., El-kafafy, M., Peeters, B., Bianciardi, F., Brandolisio, D., Janssens, K., Martarelli, M.: Experimental acoustic modal analysis of an automotive cabin. In: Proceedings of International Modal Analysis Conference (IMAC XXXIII), Springer, Orlando, FL, 2015
Siemens Industry Software: LMS Test.Lab Modal Analysis 16A - User Manual. Leuven, Belgium (2016)
Hwang, K.H., Choi, S.C., Van Genechten, B., Jeon, J.H., Brechlin, E.: Acoustic finite element model validation of vehicle interior cabin from acoustic mode and transfer function. In: Proceedings of NAFEMS World Congress, San Diego, CA, USA, 2015
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El-Kafafy, M., Peeters, B., Guillaume, P. (2017). Optimal Modal Parameter Estimation for Highly Challenging Industrial Cases. In: Mains, M., Blough, J. (eds) Topics in Modal Analysis & Testing, Volume 10. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-54810-4_19
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DOI: https://doi.org/10.1007/978-3-319-54810-4_19
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