A dual implementation of the Kalman filter is proposed for estimating the unknown input and
states of a linear state-space model by using sparse noisy acceleration measurements. The …

In this article, an overview of Bayesian methods for sequential simulation from posterior
distributions of nonlinear and non-Gaussian dynamic systems is presented. The focus is …

The emerging noncontact vision-based displacement sensor system offers a promising
alternative to the conventional sensors for quantitative structural integrity assessment …

This paper proposes a Bayesian framework based on particle filters for online fatigue
damage diagnosis and prognosis for wind turbine blades (WTBs). The framework integrates …

A hybrid optimization methodology is presented for the probabilistic finite element model
updating of structural systems. The model updating process is formulated as an inverse …

Damage detection is one important target in structural health monitoring (SHM). Vibration‐
based damage detection has attracted more attention in the past decades by tracking the …

This contribution presents a hierarchical Bayesian filter for recursive input, state and
parameter estimation using spatially incomplete and noisy output-only vibration …

This paper proposes a linear recursive Bayesian filter for minimum variance unbiased joint
input and state estimation of structural systems. Unlike the augmented Kalman filter (AKF) …

Recent events of significant seismic activity (L'Aquila 2009, Christchurch 2011), have
highlighted the importance of accurately assessing the properties of structures, for …

A digital twin is a powerful new concept in computational modelling that aims to produce a
one-to-one mapping of a physical structure, operating in a specific context, into the digital …