Data fusion approaches for structural health monitoring and system identification: Past, present, and future
RT Wu, MR Jahanshahi - Structural Health Monitoring, 2020 - journals.sagepub.com
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 …
Dynamic load identification for mechanical systems: A review
R Liu, E Dobriban, Z Hou, K Qian - Archives of Computational Methods in …, 2022 - Springer
Due to the great challenges of measuring forces directly, identifying dynamic loads based on
accessible responses is a crucial problem in engineering, helping ensure integrity and …
accessible responses is a crucial problem in engineering, helping ensure integrity and …
Structural identification with physics-informed neural ordinary differential equations
This paper exploits a new direction of structural identification by means of Neural Ordinary
Differential Equations (Neural ODEs), particularly constrained by domain knowledge, such …
Differential Equations (Neural ODEs), particularly constrained by domain knowledge, such …
A novel unscented Kalman filter for recursive state-input-system identification of nonlinear systems
Y Lei, D Xia, K Erazo, S Nagarajaiah - Mechanical Systems and Signal …, 2019 - Elsevier
The unscented Kalman filter (UKF) has proven to be an effective approach for the
identification of nonlinear systems from limited output measurements. However, the …
identification of nonlinear systems from limited output measurements. However, the …
Online structural health monitoring by model order reduction and deep learning algorithms
Within a structural health monitoring (SHM) framework, we propose a simulation-based
classification strategy to move towards online damage localization. The procedure combines …
classification strategy to move towards online damage localization. The procedure combines …
Dynamic strain estimation for fatigue assessment of an offshore monopile wind turbine using filtering and modal expansion algorithms
Offshore wind turbines are exposed to continuous wind and wave excitation. The monitoring
of high periodic strains at critical locations is important to assess the remaining lifetime of the …
of high periodic strains at critical locations is important to assess the remaining lifetime of the …
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 …
[HTML][HTML] An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
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 …
potency of Structural Health Monitoring (SHM) tools, which are then bestowed with …
A Gaussian process latent force model for joint input-state estimation in linear structural systems
The problem of combined state and input estimation of linear structural systems based on
measured responses and a priori knowledge of structural model is considered. A novel …
measured responses and a priori knowledge of structural model is considered. A novel …
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 …
examined herein on both linear and nonlinear systems. The unknown input is estimated in …