Particle filtering for computer vision-based identification of frame model parameters
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2014, Vol 21, Issue 1
Abstract
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.
Authors and Affiliations
Marcin Tekieli, Marek Słoński
Efficient Markov chain Monte Carlo sampling for electrical impedance tomography
This paper studies electrical impedance tomography (EIT) using Bayesian inference [1]. The resulting posterior distribution is sampled by Markov chain Monte Carlo (MCMC) [2]. This paper studies a toy model of EIT as the...
Numerical studies of dynamic stability under small random parametric excitations
An efficient numerical procedure is proposed to obtain mean-square stability regions for both single-degree-of-freedom and two-degree-of-freedom linear systems under parametric bounded noise excitation. This procedure re...
Identification of aerodynamic coefficients of a projectile and reconstruction of its trajectory from partial flight data
Several optimization techniques are proposed both to identify the aerodynamic coefficients and to reconstruct the trajectory of a fin-stabilized projectile from partial flight data. A reduced ballistic model is used inst...
Transient heat conduction by different versions of the Method of Fundamental Solutions - a comparison study. (Received in the final form September 14, 2010)
The computational accuracy of three versions of the method of fundamental solutions (MFS) is compared. The first version of MFS is based on the Laplace transformation of the governing differential equations and of the bo...
Neural networks for the analysis of mine-induced building vibrations
A study of the capabilities of artificial neural networks in respect of selected problems of the analysis of mine-induced building vibrations is presented. Neural network technique was used for the prediction of building...