Residual States for Modal Models Identified from Accelerance Data

Gibanica, Mladen; Abrahamsson, Thomas; Allemang, Randall J.

doi:10.1007/978-3-319-74700-2_20

Cited by 1 publication

(2 citation statements)

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“…An identified system is necessary for the calibration procedure. A recently proposed state-space system identification method using residual states is used for this purpose [18,20]. For single-input multi-output systems, as considered here, only one re-estimation of the system input and output matrices is necessary, according to [24].…”

Section: Rear Subframementioning

confidence: 99%

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Model Updating of Multiple Nominally Identical Car Components

2020

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A method for estimation of rubber bushing stiffness parameters is presented. Four individual rubber bushings, mounted in a car rear subframe are considered. A traditional model of the bushing elements using a generalised spring model, known as a CBUSH element in Nastran, is compared to a geometrically more realistic approach where the bushing is modelled with solid elements and a linear elastic material model. Each bushing is mass loaded to better reveal the bushing's dynamic behaviour in a lower frequency range of interest. In an initial step, the overall subframe model is updated towards test data. In a second step, the bushing parameters are updated. Three nominally identical components are used to investigate the spread between the identified parameters. The model updating procedure is based on frequency responses and equalised damping. The undamped behaviour at frequencies below 300 Hz are considered. To quantify the parameter uncertainty, with respect to measurement noise for each individual, an uncertainty quantification procedure is proposed, using a linear-in-parameters surrogate model with bootstrapping.Experimental Techniques (2020) 44:391-407Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Section: Rear Subframementioning

confidence: 99%

“…The same system identification procedure was used here as for the rear subframe [18,20]. The data is multi-input multi-output and therefore a few (typically four) iterations of the system input and output matrices were necessary to reach convergence of the least squares loss function.…”

Section: Mass Loaded Bushingsmentioning

confidence: 99%