Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation

This paper focuses on determining the limit state exceeding probability of a deteriorating model using optimal and sub-optimal Bayesian algorithms. Specifically the Kalman filter (for a linear system), extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation (for non...

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Main Authors: Garciano, Lessandro Estelito O., Yoshida, Ikumasa
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Published: Animo Repository 2011
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/6033
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-67162022-06-02T01:47:27Z Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation Garciano, Lessandro Estelito O. Yoshida, Ikumasa This paper focuses on determining the limit state exceeding probability of a deteriorating model using optimal and sub-optimal Bayesian algorithms. Specifically the Kalman filter (for a linear system), extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation (for non-linear systems) are used to approximate the present state of a deteriorating system given measurements tainted with noise of the system output. In addition to the comprehensive discussion of the theory, numerical implementation and comparison of the results through numerical examples are shown. 2011-09-01T07:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/6033 Faculty Research Work Animo Repository Kalman filtering Monte Carlo method Structural analysis (Engineering) Structural analysis (Engineering)—Approximation methods Civil Engineering Construction Engineering and Management
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Kalman filtering
Monte Carlo method
Structural analysis (Engineering)
Structural analysis (Engineering)—Approximation methods
Civil Engineering
Construction Engineering and Management
spellingShingle Kalman filtering
Monte Carlo method
Structural analysis (Engineering)
Structural analysis (Engineering)—Approximation methods
Civil Engineering
Construction Engineering and Management
Garciano, Lessandro Estelito O.
Yoshida, Ikumasa
Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
description This paper focuses on determining the limit state exceeding probability of a deteriorating model using optimal and sub-optimal Bayesian algorithms. Specifically the Kalman filter (for a linear system), extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation (for non-linear systems) are used to approximate the present state of a deteriorating system given measurements tainted with noise of the system output. In addition to the comprehensive discussion of the theory, numerical implementation and comparison of the results through numerical examples are shown.
format text
author Garciano, Lessandro Estelito O.
Yoshida, Ikumasa
author_facet Garciano, Lessandro Estelito O.
Yoshida, Ikumasa
author_sort Garciano, Lessandro Estelito O.
title Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_short Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_full Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_fullStr Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_full_unstemmed Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_sort estimating the limit state exceeding probability of a deteriorating structure using the kalman filter, extended kalman filter, unscented kalman filter and the sequential monte carlo simulation
publisher Animo Repository
publishDate 2011
url https://animorepository.dlsu.edu.ph/faculty_research/6033
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