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ON THE USE OF CONSISTENT AND SIGNIFICANT INFORMATION TO REDUCE ILL-CONDITIONING IN DYNAMIC MODEL UPDATING

✍ Scribed by W. D'Ambrogio; A. Fregolent


Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
297 KB
Volume
12
Category
Article
ISSN
0888-3270

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✦ Synopsis


A dynamic model updating technique, force residual updating-interactive technique (FRU-IT), is described. The technique is based on minimisation of the force (input) residual. Like most parametric identification problems, dynamic model updating is affected strongly by measurement errors due to the ill-conditioning of the problem. The proposed method is used to define and solve the set of updating equations in order to minimise the influence of measurement errors. This includes the selection of experimental degrees of freedom to ensure data consistency, the choice of the working frequencies to pursue data significance, and the use of regularisation techniques; specifically, an interactive use is made of the truncated singular value decomposition. The performance of the method is demonstrated by test cases.