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The measurement errors of modal data are simulated by superimposing random noise with appropriate magnitudes.
As reference data for updating, both cases of using frequency as well as modal data are discussed.
Adequate objective functions relying on the discrepancy between the experimental and numerical modal data are developed for the parameter estimation.
The updating algorithm is based on the sensitivity approach in which the discrepancies between the analytical and experimental modal data are minimized in an iterative manner.
All of the obtained results demonstrate that the proposed method precisely identifies damages by using only the first several modes' data, even when incomplete noisy modal data are considered as input data.
The present technique is referred to as the inverse substructuring model updating method as the measured global modal data are disassembled into the substructure level and then the updating is conducted on the substructures only.
Similar(46)
The simulated reduced modal data is expanded using the eigenvector projection method.
An approach on determining the equivalent elastic modulus of honeycomb core using experimental modal data is proposed in this paper.
Model validation based on experimental modal data is often not possible due to the high modal density that aircraft fuselage structures exhibit in this frequency range.
The error in the modal data is simulated by an additive noise that follows the normal distribution.
The results of the technique presented in this paper versus those obtained by a technique based on modal data is also discussed.
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