A critical review for trustworthy and explainable structural health monitoring and risk prognosis of bridges with human-in-the-loop

Z Sun, T Chen, X Meng, Y Bao, L Hu, R Zhao - Sustainability, 2023 - mdpi.com
Trustworthy and explainable structural health monitoring (SHM) of bridges is crucial for
ensuring the safe maintenance and operation of deficient structures. Unfortunately, existing …

A new Kalman filter approach for structural parameter tracking: Application to the monitoring of damaging structures tested on shaking-tables

M Diaz, PÉ Charbonnel, L Chamoin - Mechanical Systems and Signal …, 2023 - Elsevier
In this paper, a new data assimilation framework for correcting finite element models from
datasets acquired on-the-fly in low-frequency dynamics is presented. An Unscented Kalman …

Bayesian updating and identifiability assessment of nonlinear finite element models

MK Ramancha, R Astroza, R Madarshahian… - … Systems and Signal …, 2022 - Elsevier
A promising and attractive way of performing structural health monitoring (SHM) and
damage prognosis (DP) of engineering systems is through utilizing a nonlinear finite …

A dual adaptive filtering approach for nonlinear finite element model updating accounting for modeling uncertainty

R Astroza, A Alessandri, JP Conte - Mechanical Systems and Signal …, 2019 - Elsevier
This paper proposes a novel approach to deal with modeling uncertainty when updating
mechanics-based nonlinear finite element (FE) models. In this framework, a dual adaptive …

Finite element model updating through derivative-free optimization algorithm

D Li, J Zhang - Mechanical Systems and Signal Processing, 2023 - Elsevier
Finite element (FE) model of updating is the process of calibrating model parameters to
improve the accuracy of numerical prediction. This goal is usually achieved by solving an …

A Kalman filter algorithm for identifying track irregularities of railway bridges using vehicle dynamic responses

X Xiao, Z Sun, W Shen - Mechanical Systems and Signal Processing, 2020 - Elsevier
Track irregularities affect the running safety of railway vehicles and ride comfort, hence track
irregularity identification using the dynamic responses of in-service vehicles is of great …

Input-state-parameter-noise identification and virtual sensing in dynamical systems: A Bayesian expectation-maximization (BEM) perspective

D Teymouri, O Sedehi, LS Katafygiotis… - … Systems and Signal …, 2023 - Elsevier
Structural identification and damage detection can be generalized as the simultaneous
estimation of input forces, physical parameters, and dynamical states. Although Kalman-type …

Effects of model uncertainty in nonlinear structural finite element model updating by numerical simulation of building structures

R Astroza, A Alessandri - Structural Control and Health …, 2019 - Wiley Online Library
Uncertainties in finite element (FE) model updating arise from two main sources:
measurement noise and modeling errors. The latter includes model parameter uncertainty …

Estimation of time-varying noise parameters for unscented Kalman filter

KV Yuen, YS Liu, WJ Yan - Mechanical Systems and Signal Processing, 2022 - Elsevier
The unscented Kalman filter (UKF) is a promising method for system state and structural
parameters estimation. However, its performance depends on the process noise and …

Structural nonlinear boundary condition identification using a hybrid physics data-driven approach

L Luo, L Sun, Y Li, Y Xia - Nonlinear Dynamics, 2024 - Springer
As civil infrastructures often exhibit nonlinearities, the identification of nonlinear behaviors is
crucial to assess the structural safety state. However, existing physics-driven methods can …