| Autor: |
Frank Naets, S. Donders, Jan Croes, Steven Gillijns, Herman Van der Auweraer, Wim Desmet |
| Rok vydání: |
2016 |
| Předmět: |
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| Zdroj: |
Special Topics in Structural Dynamics, Volume 6 ISBN: 9783319299099 |
| DOI: |
10.1007/978-3-319-29910-5_12 |
| Popis: |
Design models can drastically improve the applicability of testing and allow measuring previously unmeasurable quantities and designing reduced test configurations. A common workflow is followed: a multiphysics system model provides a prediction of the system states which is corrected by the estimation algorithms using the measurement data. The model can then generate data of the non-measurable quantities (e.g. virtual sensors). A wide range of models can be used, including analytical, 1D lumped parameter and 3D distributed parameter models. Key is that they are easy to evaluate and have a small number of states, while capturing the dominant physics. Novel model order reduction techniques enable the use of more complex models. A wide range of state estimation approaches has been developed such as the (linear, extended, unscented, …) Kalman Filter and the Moving Horizon Estimator. All approaches require a trade-off between accuracy and computational load so that conventional estimators must be tailored to deal with high-fidelity nonlinear models of industrial complexity. The approach is illustrated with two cases: the estimation of hard-to-measure vehicle body forces using the extended Kalman filter and the application to an electro-mechanical drivetrain subject to unknown input forces. Methodological aspects are evaluated and different estimators are compared. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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