Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges
Abstract Fault Diagnosis and Health Monitoring (FD-HM) for modern control systems have
been an active area of research over the last few years. Model-based FD-HM computational …
been an active area of research over the last few years. Model-based FD-HM computational …
Structural health monitoring techniques implemented on IASC–ASCE benchmark problem: a review
Various structural health monitoring techniques have been developed over the years. Due to
the lack of a common platform to test the efficiency of these methods, the damage analysis …
the lack of a common platform to test the efficiency of these methods, the damage analysis …
Input-state-parameter estimation of structural systems from limited output information
A successive Bayesian filtering framework for addressing the joint input-state-parameter
estimation problem is proposed in this study. Following the notion of analytical, rather than …
estimation problem is proposed in this study. Following the notion of analytical, rather than …
A survey on model-based fault diagnosis for linear discrete time-varying systems
To meet the rising demands for safety and reliability of modern industrial control systems, the
model-based fault diagnosis problem has attracted much attention in the past few decades …
model-based fault diagnosis problem has attracted much attention in the past few decades …
Input-state-parameter-noise identification and virtual sensing in dynamical systems: A Bayesian expectation-maximization (BEM) perspective
Structural identification and damage detection can be generalized as the simultaneous
estimation of input forces, physical parameters, and dynamical states. Although Kalman-type …
estimation of input forces, physical parameters, and dynamical states. Although Kalman-type …
A modal‐based Kalman filtering framework for mode extraction and decomposition of damped structures
JS Hwang, DK Kwon, A Kareem - Computer‐Aided Civil and …, 2023 - Wiley Online Library
The mode shape is one of the important modal parameters that enables to visualize the
intrinsic behavior of a structure as well as the quantity of interest by extracting or separating …
intrinsic behavior of a structure as well as the quantity of interest by extracting or separating …
[HTML][HTML] Multiple local particle filter for high-dimensional system identification
Nonlinearity and high dimensionality emerge as two primary challenges in the realm of
system identification within the context of structural health monitoring (SHM) applications …
system identification within the context of structural health monitoring (SHM) applications …
Load identification of a 2.5 MW wind turbine tower using Kalman filtering techniques and BDS data
D Wei, D Li, T Jiang, P Lyu, X Song - Engineering Structures, 2023 - Elsevier
The rapid increase in the number of wind turbine installations and operations, is increasing
the importance of the health monitoring of these wind turbines. To assess the remaining …
the importance of the health monitoring of these wind turbines. To assess the remaining …
Auto-regressive model based input and parameter estimation for nonlinear finite element models
A novel framework to accurately estimate nonlinear structural model parameters and
unknown external inputs (ie, loads) using sparse sensor networks is proposed and …
unknown external inputs (ie, loads) using sparse sensor networks is proposed and …
A generalized extended Kalman particle filter with unknown input for nonlinear system‐input identification under non‐Gaussian measurement noises
Y Lei, J Lai, J Huang, C Qi - Structural Control and Health …, 2022 - Wiley Online Library
It is necessary to investigate the identification of structural systems and unknown inputs
under non‐Gaussian measurement noises. In recent years, a few scholars have proposed …
under non‐Gaussian measurement noises. In recent years, a few scholars have proposed …