Deep transfer learning models for industrial fault diagnosis using vibration and acoustic sensors data: A review
MR Bhuiyan, J Uddin - Vibration, 2023 - mdpi.com
In order to evaluate final quality, nondestructive testing techniques for finding bearing flaws
have grown in favor. The precision of image processing-based vision-based technology has …
have grown in favor. The precision of image processing-based vision-based technology has …
A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
In recent years, intelligent fault diagnosis algorithms using machine learning technique have
achieved much success. However, due to the fact that in real world industrial applications …
achieved much success. However, due to the fact that in real world industrial applications …
An Extended Zonotopic and Gaussian Kalman Filter (EZGKF) merging set-membership and stochastic paradigms: Toward non-linear filtering and fault detection
C Combastel - Annual Reviews in Control, 2016 - Elsevier
A framework merging the set-membership and the stochastic paradigms is formalized and
used to design an Extended Zonotopic and Gaussian Kalman Filter (EZGKF) dealing with …
used to design an Extended Zonotopic and Gaussian Kalman Filter (EZGKF) dealing with …
Interval estimation methods for discrete-time linear time-invariant systems
This paper investigates interval estimation methods for discrete-time linear time-invariant
systems. We propose a novel interval estimation method by integrating robust observer …
systems. We propose a novel interval estimation method by integrating robust observer …
Set-membership approach and Kalman observer based on zonotopes for discrete-time descriptor systems
This paper proposes a set-membership state estimator and a zonotopic Kalman observer for
discrete-time descriptor systems. Both approaches are developed in a set-based context …
discrete-time descriptor systems. Both approaches are developed in a set-based context …
Bearing fault diagnosis using fully-connected winner-take-all autoencoder
Intelligent fault diagnosis of bearings has been a heated research topic in the prognosis and
health management of rotary machinery systems, due to the increasing amount of available …
health management of rotary machinery systems, due to the increasing amount of available …
Comparison of guaranteed state estimators for linear time-invariant systems
Guaranteed state estimation computes the set of possible states of dynamical systems given
the bounds of model uncertainties, disturbances, and noises. For the first time, we evaluate …
the bounds of model uncertainties, disturbances, and noises. For the first time, we evaluate …
Guaranteed methods based on constrained zonotopes for set-valued state estimation of nonlinear discrete-time systems
This paper presents new methods for set-valued state estimation of nonlinear discrete-time
systems with unknown-but-bounded uncertainties. A single time step involves propagating …
systems with unknown-but-bounded uncertainties. A single time step involves propagating …
Set-valued state estimation of nonlinear discrete-time systems with nonlinear invariants based on constrained zonotopes
This paper presents new methods for set-valued state estimation of discrete-time nonlinear
systems whose trajectories are known to satisfy nonlinear equality constraints, called …
systems whose trajectories are known to satisfy nonlinear equality constraints, called …
Bayesian and Dempster–Shafer reasoning for knowledge-based fault diagnosis–A comparative study
K Verbert, R Babuška, B De Schutter - Engineering Applications of Artificial …, 2017 - Elsevier
Even though various frameworks exist for reasoning under uncertainty, a realistic fault
diagnosis task does not fit into any of them in a straightforward way. For each framework …
diagnosis task does not fit into any of them in a straightforward way. For each framework …