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2 Computer Assisted Methods in Engineering and Science

2 2014

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Sequential stochastic identification of elastic constants using Lamb waves and particle filters

Słoński M.

Computer Assisted Methods in Engineering and Science

2014

Vol. 21, no. 1

15--26

Sequential stochastic identification of elastic parameters of thin aluminum plates using Lamb waves is proposed. The identification process is formulated as a Bayesian state estimation problem in which the elastic constants are the unknown state variables. The comparison of a sequence of numerical and pseudoexperimental fundamental dispersion curves is used for an inverse analysis based on particle filter to obtain sequentially the elastic constants. The proposed identification procedure is illustrated by numerical experiments in which the elastic parameters of an aluminum thin plate are estimated. The results show that the proposed approach is able to identify the unknown elastic constants sequentially and that this approach can be also useful for the quantification of uncertainty with respect to the identified parameters.

Particle filtering for computer vision-based identification of frame model parameters

Tekieli M., Słoński M.

Computer Assisted Methods in Engineering and Science

2014

Vol. 21, no. 1

39--48

In this paper we present a new approach for solving identification problems based on a novel combination of computer vision techniques, Bayesian state estimation and finite element method. Using our approach we solved two identification problems for a laboratory-scale aluminum frame. In the first problem, we recursively estimated the elastic modulus of the frame material. In the second problem, for the known elastic constant, we identified sequentially the position of a quasi-static concentrated load.