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Localized identification of MDOF structures in the frequency domain
Author(s) -
Zhao Q.,
Sawada T.,
Hirao K.,
Nariyuki Y.
Publication year - 1995
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/eqe.4290240303
Subject(s) - identifiability , smoothing , identification (biology) , noise (video) , frequency domain , algorithm , convergence (economics) , computation , computer science , time domain , system identification , data mining , artificial intelligence , machine learning , botany , economics , image (mathematics) , computer vision , biology , measure (data warehouse) , economic growth
For the identification of multi‐degree‐of‐freedom structures, it is not practical to identify all of the parameters included in the structures because enormous computation time is required and because identifiability may not be possible. In this paper, a localized identification approach through substructuring is formulated in the frequency domain. A technique of spectral smoothing is incorporated in the approach to deal with noise‐corrupted data. The proposed approach can be used to identify the structural parameters in any part of interest in a structure. The numerical investigations for a lumped mass‐spring‐dashpot system indicate that faster convergence and higher accuracy are achieved and the noise influences on the identified results are reduced greatly by spectral smoothing. The approach also applies to whole‐structure identification if the required records available and the numerical example shows that higher accuracy results are obtained with less cpu time and more poorly guessed initial values as compared with the general complete‐structure identification.