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 …

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

W Zhang, C Li, G Peng, Y Chen, Z Zhang - Mechanical systems and signal …, 2018 - Elsevier
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 …

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 …

Interval estimation methods for discrete-time linear time-invariant systems

W Tang, Z Wang, Y Wang, T Raïssi… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This paper investigates interval estimation methods for discrete-time linear time-invariant
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

Y Wang, V Puig, G Cembrano - Automatica, 2018 - Elsevier
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 …

Bearing fault diagnosis using fully-connected winner-take-all autoencoder

C Li, WEI Zhang, G Peng, S Liu - IEEE Access, 2017 - ieeexplore.ieee.org
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 …

Comparison of guaranteed state estimators for linear time-invariant systems

M Althoff, JJ Rath - Automatica, 2021 - Elsevier
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 …

Guaranteed methods based on constrained zonotopes for set-valued state estimation of nonlinear discrete-time systems

BS Rego, GV Raffo, JK Scott, DM Raimondo - Automatica, 2020 - Elsevier
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 …

Set-valued state estimation of nonlinear discrete-time systems with nonlinear invariants based on constrained zonotopes

BS Rego, JK Scott, DM Raimondo, GV Raffo - Automatica, 2021 - Elsevier
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 …

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 …