A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: Shallow and deep learning
The objective of this paper is to present a comprehensive review of the contemporary
techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs) …
techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs) …
A systematic review of machine learning algorithms for prognostics and health management of rolling element bearings: fundamentals, concepts and applications
This article aims to present a comprehensive review of the recent efforts and advances in
applying machine learning (ML) techniques in the area of diagnostics and prognostics of …
applying machine learning (ML) techniques in the area of diagnostics and prognostics of …
Application of Artificial Intelligence-Based Technique in Electric Motors: A Review
Electric motors find widespread application across various industrial fields. The pursuit of
enhanced comprehensive electric motors performance has consistently drawn significant …
enhanced comprehensive electric motors performance has consistently drawn significant …
Three-stage hybrid fault diagnosis for rolling bearings with compressively sampled data and subspace learning techniques
To avoid the burden of much storage requirements and processing time, this paper
proposes a three-stage hybrid method, compressive sampling with correlated principal and …
proposes a three-stage hybrid method, compressive sampling with correlated principal and …
Compressive sampling and feature ranking framework for bearing fault classification with vibration signals
Failures of rolling element bearings are amongst the main causes of machines breakdowns.
To prevent such breakdowns, bearing health monitoring is performed by collecting data from …
To prevent such breakdowns, bearing health monitoring is performed by collecting data from …
Fault detection of a VTOL UAV using acceleration measurements
This paper proposes an actuator fault detection algorithm for vertical take-off and landing
(VTOL) unmanned aerial vehicle (UAV), based on acceleration signals provided by a high …
(VTOL) unmanned aerial vehicle (UAV), based on acceleration signals provided by a high …
Fault detection of elevator systems using multilayer perceptron neural network
KM Mishra, KJ Huhtala - 2019 24th IEEE International …, 2019 - ieeexplore.ieee.org
In this research, we propose a generic multilayer perceptron (MLP) neural network model
based on deep learning algorithm for automatic calculation of highly informative deep …
based on deep learning algorithm for automatic calculation of highly informative deep …
[HTML][HTML] Feature learning for bearing prognostics: A comprehensive review of machine/deep learning methods, challenges, and opportunities
Mechanical bearings are common elements in a wide range of applications, such as wind
turbines and manufacturing. Therefore, bearing prognostics are crucial to preventing …
turbines and manufacturing. Therefore, bearing prognostics are crucial to preventing …
An unmanned marine vehicle thruster fault diagnosis scheme based on OFNDA
In recent years, there has been a growing interest in the use of fault analysis techniques in
unmanned marine vehicles (UMVs) owing to their significant impact on marine operations …
unmanned marine vehicles (UMVs) owing to their significant impact on marine operations …
Compressive sensing strategy for classification of bearing faults
Owing to the importance of rolling element bearings in rotating machines, condition
monitoring of rolling element bearings has been studied extensively over the past decades …
monitoring of rolling element bearings has been studied extensively over the past decades …