Substructure decoupling techniques allow identifying the dynamic behavior of a substructure starting from the dynamic behavior or the assembled system and a residual subsystem. Standard approaches rely on the knowledge of all FRFs at the interface DOFs between the two substructures. However, as these typically include also rotational DOFs which are extremely difficult and most of the time impossible to measure, several techniques have been investigated to overcome these limitations. A very attractive solution consists in defining mixed or pseudo interfaces, that allow to substitute unmeasurable coupling DOFs with internal DOFs on the residual substructure. Additionally, smoothing/denoising techniques have been proposed to reduce the detrimental effect of FRF noise and inconsistencies on the decoupling results. Starting from these results, some recent analysis on the possibility of combining coupling and decoupling FBS to validate the results and compensate for inconsistencies will be presented in this paper. The proposed method relies on errors introduced in the substructuring process when assuming that the interface behaves rigidly, while it is generally known that this assumption is seldom verified. Consequently, a recursive coupling-decoupling approach will be used to improve the estimation of the dynamic response of either the residual structure (for decoupling) or the assembly (for coupling). The method, validated on analytical data, will be here analyzed on a numerical example inspired by an experimental campaign used to validate the finite element models and on which standard substructuring techniques showed some limitations. The results discussed in this paper will be then used as guidelines to apply the proposed methodologies on experimental data in the future.
A recursive coupling-decoupling approach to improve experimental frequency based substructuring results / Cumbo, R.; Manzato, S.; Coppotelli, G.; Fregolent, A.; D’Ambrogio, W.. - STAMPA. - 4:(2017), pp. 239-253. (Intervento presentato al convegno 35th IMAC Conference and Exposition on Structural Dynamics tenutosi a Garden Grove, CA, United States nel JAN 30-FEB 02, 2017) [10.1007/978-3-319-54930-9_21].
A recursive coupling-decoupling approach to improve experimental frequency based substructuring results
Cumbo, R.;Coppotelli, G.;Fregolent, A.;
2017
Abstract
Substructure decoupling techniques allow identifying the dynamic behavior of a substructure starting from the dynamic behavior or the assembled system and a residual subsystem. Standard approaches rely on the knowledge of all FRFs at the interface DOFs between the two substructures. However, as these typically include also rotational DOFs which are extremely difficult and most of the time impossible to measure, several techniques have been investigated to overcome these limitations. A very attractive solution consists in defining mixed or pseudo interfaces, that allow to substitute unmeasurable coupling DOFs with internal DOFs on the residual substructure. Additionally, smoothing/denoising techniques have been proposed to reduce the detrimental effect of FRF noise and inconsistencies on the decoupling results. Starting from these results, some recent analysis on the possibility of combining coupling and decoupling FBS to validate the results and compensate for inconsistencies will be presented in this paper. The proposed method relies on errors introduced in the substructuring process when assuming that the interface behaves rigidly, while it is generally known that this assumption is seldom verified. Consequently, a recursive coupling-decoupling approach will be used to improve the estimation of the dynamic response of either the residual structure (for decoupling) or the assembly (for coupling). The method, validated on analytical data, will be here analyzed on a numerical example inspired by an experimental campaign used to validate the finite element models and on which standard substructuring techniques showed some limitations. The results discussed in this paper will be then used as guidelines to apply the proposed methodologies on experimental data in the future.File | Dimensione | Formato | |
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