A Comparison of Finite Element Model Error Localization Methods

The aim of this study is to compare a new and some existing finite element model error localization methods. The methods are applied to two problems. First, fundamental properties of the error localization methods are studied on a simple sprung mass system. In the second problem a three-bay frame structure is studied. Here the analytical results of a finite element analysis is taken as substitute for measured data. The model differences between this model and a perturbed model are then found by use of error localization methods. When data from a known finite element model take place as substitute for test data, the cause of the differences between the data sets are known. A so-called consistent para- meterization, i.e. a parameterization of the quantities known to be in error, is then possible. The error localization method are compared for both consistent and inconsistent parameterization. A pre-error localization is made. It is based on the finite element model’s properties. Candidate model parameters, possibly in error, for which the experimental data are not informative, are rejected. Non-identifiable parameters are also rejected. Quantification of data information richness and identifiability with newly developed index numbers support the pre-error localization. Four error localization methods are compared. Two of these are developed by Lallement and Piranda. These are the so- called Balancing of Eigenvalue Equation and Best Subspace Methods. The third is developed by Link and Santiago and is the Substructure Energy Function Method. A new localization method, using gradient and Hessian information of the error criterion function, constitute the fourth method