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Multi‐stage parameter identification of structural models from experimental data of varying assembly levels
Author(s) -
Greiner Benjamin,
Wagner Jörg F.
Publication year - 2017
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201710120
Subject(s) - identification (biology) , aerospace , finite element method , system identification , experimental data , computer science , estimation theory , structural health monitoring , test data , engineering , control engineering , data mining , algorithm , mathematics , structural engineering , aerospace engineering , measure (data warehouse) , programming language , statistics , botany , biology
Classical applications of the Finite Element Method (FEM) in the aerospace industry use structural models to predict dynamical properties during all design and integration phases. During development, test results are used for the identification and updates of model parameters. In recent years, the availability of structures with electromechanical components, such as actively controlled subsystems or systems with structural health monitoring, has extended the amount of available data suitable for parameter identification in operational conditions even beyond the development phase. The contribution presents an approach of using measurement data from different stages of structural assemblies for the identification and update of model parameters. Estimating parameters for subassembly models is preferred, because it is often more intuitive than a global approach in a complex model. Estimation uncertainties propagating to higher assembly levels have to be considered when assessing the model accuracy of a composed model. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)