Identification of physically realistic state-space models for accurate component synthesis
Mechanical Systems and Signal Processing, ISSN: 0888-3270, Vol: 145, Page: 106906
2020
- 7Citations
- 6Captures
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Article Description
For components that are difficult to model with conventional analytical or numerical tools, experimentally derived state-space models can instead be used in system synthesis. For successful state-space synthesis, a physically realistic model must be identified. For this purpose, a hybrid first- and second-order system description is used here as the basis for identification. In the identification procedure, a physically motivated rigid body rank constraint is imposed together with a reciprocity constraint. The two constraints are enforced during a re-estimation phase of the state-space matrices following after a traditional state-space subspace identification phase. In this paper, two complex and modally dense industrial components are combined into a dynamical system. An experimental model of a car body-in-white structure is identified. The identified subsystem model is coupled with a finite element model of a rear subframe in a system synthesis. The two subsystems are attached through four rubber bushings modelled by finite element procedures. It is shown that the experimental-analytical assembly successfully predicts the reference measured system, with higher accuracy than what could be achieved with a model based solely on finite elements. It is also shown that synthesis with individually calibrated rear subframe models can capture the variability in the coupled system.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0888327020302922; http://dx.doi.org/10.1016/j.ymssp.2020.106906; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85084557131&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0888327020302922; https://dx.doi.org/10.1016/j.ymssp.2020.106906
Elsevier BV
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