Structural Health Monitoring using Bayesian Optimization of the finite element model of structures and Kalman filter, M.Sc. Thesis Sharif University of Technology ; Bakhshi, Ali (Supervisor)
Abstract
With confidence in the recorded observations, the RLS method no longer estimates the recorded measurements by sensors, i.e. the displacement and speed of the floors, and only estimates the parameters. In contrast, in the EKF method, in addition to estimating the structure's parameters, a more precise estimation of the observations recorded by the sensors has been done by accepting the noise in the recorded observations. These methods, which are based on the Bayesian updating, investigate the two primary sources of uncertainty in a problem: a) measurement noise or observation noise, and b) process noise, which includes modeling errors. In these methodologies, the unknown system parameters,...
Cataloging briefStructural Health Monitoring using Bayesian Optimization of the finite element model of structures and Kalman filter, M.Sc. Thesis Sharif University of Technology ; Bakhshi, Ali (Supervisor)
Abstract
With confidence in the recorded observations, the RLS method no longer estimates the recorded measurements by sensors, i.e. the displacement and speed of the floors, and only estimates the parameters. In contrast, in the EKF method, in addition to estimating the structure's parameters, a more precise estimation of the observations recorded by the sensors has been done by accepting the noise in the recorded observations. These methods, which are based on the Bayesian updating, investigate the two primary sources of uncertainty in a problem: a) measurement noise or observation noise, and b) process noise, which includes modeling errors. In these methodologies, the unknown system parameters,...
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