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Application of SVD in optimization of structural modal test

โœ Scribed by K. Liu

Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
691 KB
Volume
63
Category
Article
ISSN
0045-7949

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โœฆ Synopsis

AMract4onventional time-domain methods for structural modal identification using free msponau are based on polynomial realization scheme. However, these methods are limited in terms of robustness to noise disturbance. Razenlly the model-based eigendecomposition methods have receival cons&rable attention. A critical step in these methods utilizes the singular value decomposition (SVD) of the data matrix. The SVD ruuks in a low rank approximate matrix in which the noise effect is greatly reduced. In addition, the SVD of the data matrix provides significant information about the modal contents of the responses. The paper focuses on the application of this feature in structural modal tat planning. An analytical derivation is presented to show the SVD low rank approximation and singlular value structure. A concept of identifiability is introduced. A measure of the identifiability is proposed by exploring the singular values and such measure is employed to design optimal impact testing. A simply-supported beam is used as an example to illustrate the proposed testing optimization. 0 I997 Elsevier science Ltd. All rights reserved 1. INTRODUCI'lON

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