Artificial Neural Network (ANN)-Bayesian Probability Framework (BPF) based method of dynamic force reconstruction under multi-source uncertainties

Y Liu, L Wang, K Gu, M Li - Knowledge-based systems, 2022 - Elsevier
In view of the universal existence of multi-source uncertainty factors in engineering
structures, a novel method of dynamic force reconstruction is investigated based on Artificial …

Sequential Bayesian inference for uncertain nonlinear dynamic systems: a tutorial

KE Tatsis, VK Dertimanis, EN Chatzi - arXiv preprint arXiv:2201.08180, 2022 - arxiv.org
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 …

[HTML][HTML] An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics

S Vettori, E Di Lorenzo, B Peeters, MM Luczak… - … Systems and Signal …, 2023 - Elsevier
The establishment of a Digital Twin of an operating engineered system can increase the
potency of Structural Health Monitoring (SHM) tools, which are then bestowed with …

An unscented Kalman filter method for real time input-parameter-state estimation

M Impraimakis, AW Smyth - Mechanical Systems and Signal Processing, 2022 - Elsevier
The input-parameter-state estimation capabilities of a novel unscented Kalman filter is
examined herein on both linear and nonlinear systems. The unknown input is estimated in …

Physics-informed machine learning for structural health monitoring

EJ Cross, SJ Gibson, MR Jones, DJ Pitchforth… - … Health Monitoring Based …, 2022 - Springer
The use of machine learning in structural health monitoring is becoming more common, as
many of the inherent tasks (such as regression and classification) in developing condition …

Extraction of contact-point response in indirect bridge health monitoring using an input estimation approach

R Nayek, S Narasimhan - Journal of Civil Structural Health Monitoring, 2020 - Springer
Identification of bridge dynamic properties from moving vehicle responses presents several
practical benefits. However, a problem that arises when working with vehicle responses for …

Information theoretic-based optimal sensor placement for virtual sensing using augmented Kalman filtering

T Ercan, O Sedehi, LS Katafygiotis… - Mechanical Systems and …, 2023 - Elsevier
An optimal sensor placement (OSP) framework for virtual sensing using the augmented
Kalman Filter (AKF) technique is presented based on information and utility theory. The …

[HTML][HTML] A hierarchical output-only Bayesian approach for online vibration-based crack detection using parametric reduced-order models

KE Tatsis, K Agathos, EN Chatzi… - Mechanical Systems and …, 2022 - Elsevier
This contribution presents a hierarchical Bayesian filter for recursive input, state and
parameter estimation using spatially incomplete and noisy output-only vibration …

On the application of Gaussian process latent force models for joint input-state-parameter estimation: With a view to Bayesian operational identification

TJ Rogers, K Worden, EJ Cross - Mechanical Systems and Signal …, 2020 - Elsevier
The problem of identifying dynamic structural systems is of key interest to modern
engineering practice and is often a first step in an analysis chain, such as validation of …

A linear Bayesian filter for input and state estimation of structural systems

M Ebrahimzadeh Hassanabadi, Z Liu… - … ‐Aided Civil and …, 2023 - Wiley Online Library
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) …