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
College
Gokongwei College of Engineering
Department/Unit
Civil Engineering
Document Type
Conference Proceeding
Source Title
50th ASEP Anniversary International Convention & Exposition
Publication Date
9-2011
Abstract
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.
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Recommended Citation
Garciano, L. O., & Yoshida, I. (2011). 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. 50th ASEP Anniversary International Convention & Exposition Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/6033
Disciplines
Civil Engineering | Construction Engineering and Management
Keywords
Kalman filtering; Monte Carlo method; Structural analysis (Engineering); Structural analysis (Engineering)—Approximation methods
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