| 1. |
|
|
| 2. |
- Johansson, Anders, 1982, et al.
(author)
-
Comparison of Several Error Metrics for FE Model Updating
- 2007
-
In: Proceedings of the 25th International Modal Analysis Conference (IMAC-XXV), February 19-22, Orlando, Florida, USA. - 0912053968
-
Conference paper (other academic/artistic)abstract
- The choice of error metric is one of the most crucial choices of model updating. Many articles have been published advocating the use of certain such metrics, as have comparative studies of various methods based on different error metrics. This article describes the differences between a number of error metrics and their corresponding objective functions using many different evaluation methods, such as plots of objective functions, Cramer-Rao lower bounds and condition numbers of the Hessian. This approach has the advantage that it gives the user a way of assessing error metrics in terms of solvability of the optimization problem and identifiability of parameters of the model updating problem.
|
|
| 3. |
- Sjövall, Per, 1977, et al.
(author)
-
State-space model identification for component synthesis
- 2007
-
In: Proceedings of the 25th International Modal Analysis Conference (IMAC-XXV), February 19-22, Orlando, Florida, USA. - 0912053968
-
Conference paper (other academic/artistic)abstract
- A scheme for synthesis of subsystem state-space models to be used for analysis of dynamic behavior of built-up linear structures is presented. Using measurements on each component, subsystem models are identified adopting contemporary system identification methods. The subsystem state-space models are transformed into a coupling form, at which kinematic constraints and equilibrium conditions for the interfaces are introduced. The procedure is applied to a plane frame structure, which is built up of two components. It is found that the non-trivial model order determination constitutes a crucial step in the system identification process. If the model order is incorrect at subsystem level, the synthesized model may radically fail to describe the properties of the built-up structure. Furthermore, we use subsystem models that satisfy certain physically motivated constraints, e.g. reciprocity and passivity. Different approaches and methods to aid the model order determination and the estimation of physically consistent state-space models at subsystem level are discussed.
|
|
