Data fusion approaches for structural health monitoring and system identification: Past, present, and future
During the past decades, significant efforts have been dedicated to develop reliable
methods in structural health monitoring. The health assessment for the target structure of …
methods in structural health monitoring. The health assessment for the target structure of …
Bayesian methods for updating dynamic models
Abstract Model updating of dynamical systems has been attracting much attention because it
has a very wide range of applications in aerospace, civil, and mechanical engineering, etc …
has a very wide range of applications in aerospace, civil, and mechanical engineering, etc …
Transitional Markov chain Monte Carlo method for Bayesian model updating, model class selection, and model averaging
J Ching, YC Chen - Journal of engineering mechanics, 2007 - ascelibrary.org
This paper presents a newly developed simulation-based approach for Bayesian model
updating, model class selection, and model averaging called the transitional Markov chain …
updating, model class selection, and model averaging called the transitional Markov chain …
[BOOK][B] Bayesian methods for structural dynamics and civil engineering
KV Yuen - 2010 - books.google.com
Bayesian methods are a powerful tool in many areas of science and engineering, especially
statistical physics, medical sciences, electrical engineering, and information sciences. They …
statistical physics, medical sciences, electrical engineering, and information sciences. They …
Adaptive Kalman filters for nonlinear finite element model updating
This paper presents two adaptive Kalman filters (KFs) for nonlinear model updating where,
in addition to nonlinear model parameters, the covariance matrix of measurement noise is …
in addition to nonlinear model parameters, the covariance matrix of measurement noise is …
Bayesian operational modal analysis: theory, computation, practice
Ambient vibration tests have attracted increasing attention over the last few decades
because they can be performed economically with the structure under working condition …
because they can be performed economically with the structure under working condition …
Structural identification with systematic errors and unknown uncertainty dependencies
When system identification methodologies are used to interpret measurement data taken
from structures, uncertainty dependencies are in many cases unknown due to model …
from structures, uncertainty dependencies are in many cases unknown due to model …
Structural model updating and health monitoring with incomplete modal data using Gibbs sampler
A new Bayesian model updating approach is presented for linear structural models. It is
based on the Gibbs sampler, a stochastic simulation method that decomposes the uncertain …
based on the Gibbs sampler, a stochastic simulation method that decomposes the uncertain …
Ambient interference in long-term monitoring of buildings
It is a normal practice to consider the reduction of modal frequencies as an indicator for
structural damage but some long-term monitoring studies revealed that the structural modal …
structural damage but some long-term monitoring studies revealed that the structural modal …
Hierarchical sparse Bayesian learning for structural damage detection: theory, computation and application
Structural damage due to excessive loading or environmental degradation typically occurs
in localized areas (in the absence of collapse) where it leads to local stiffness reductions …
in localized areas (in the absence of collapse) where it leads to local stiffness reductions …