Abstract
Finite element model updating based on the design parameter is a kind of inverse problem in structural dynamics, whose theoretical foundation is using the features of the structure to be a function of design parameters. According to the first-order derivative of the features with respect to design parameters, iterative solution is made. This paper presents a new method which treats the model updating as a positive problem. Features are independent variables and design parameters are dependent variables. The least squares support vector machines (LS-SVM) is utilized as a map function. The objective value of the design parameters can be directly estimated due to the generalization character of the LS-SVM. The method avoids solving the complicated nonlinear optimization problem which is difficult in the reported methods. Finite element model updating based on LS-SVM about the GARTEUR aircraft model is studied. Simulation results show the errors of design parameters and modal frequencies are less than 2% and 1%, respectively.
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Zhu, Y., Zhang, L. (2009). Finite Element Model Updating Based on Least Squares Support Vector Machines. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_34
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DOI: https://doi.org/10.1007/978-3-642-01510-6_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01509-0
Online ISBN: 978-3-642-01510-6
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