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 …
Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions
Incipient fault diagnosis of a bearing requires robust feature representation for an accurate
condition-based monitoring system. Existing fault diagnosis schemes are mostly confined to …
condition-based monitoring system. Existing fault diagnosis schemes are mostly confined to …
A hybrid feature model and deep-learning-based bearing fault diagnosis
Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary
machines. It can reduce economical losses by eliminating unexpected downtime in industry …
machines. It can reduce economical losses by eliminating unexpected downtime in industry …
Bearing fault diagnosis under variable rotational speeds using stockwell transform-based vibration imaging and transfer learning
MJ Hasan, JM Kim - Applied Sciences, 2018 - mdpi.com
In this paper, discrete orthonormal Stockwell transform (DOST)-based vibration imaging is
proposed as a preprocessing step for supporting load and rotational speed invariant …
proposed as a preprocessing step for supporting load and rotational speed invariant …
Deep learning-based bearing fault diagnosis method for embedded systems
Bearing elements are vital in induction motors; therefore, early fault detection of rolling-
element bearings is essential in machine health monitoring. With the advantage of fault …
element bearings is essential in machine health monitoring. With the advantage of fault …
Bearing fault diagnosis under variable speed using convolutional neural networks and the stochastic diagonal levenberg-marquardt algorithm
This paper presents a novel method for diagnosing incipient bearing defects under variable
operating speeds using convolutional neural networks (CNNs) trained via the stochastic …
operating speeds using convolutional neural networks (CNNs) trained via the stochastic …
Intelligent fault diagnosis method using acoustic emission signals for bearings under complex working conditions
Recent convolutional neural network (CNN) models in image processing can be used as
feature-extraction methods to achieve high accuracy as well as automatic processing in …
feature-extraction methods to achieve high accuracy as well as automatic processing in …
Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder‐Based Deep Neural Network
M Sohaib, JM Kim - Shock and Vibration, 2018 - Wiley Online Library
Due to enhanced safety, cost‐effectiveness, and reliability requirements, fault diagnosis of
bearings using vibration acceleration signals has been a key area of research over the past …
bearings using vibration acceleration signals has been a key area of research over the past …
Efficient fault diagnosis of rolling bearings using neural network architecture search and sharing weights
Bearing is one of the most vital components of industrial machinery. The failure of bearing
causes severe problems in the machinery. Therefore, continuous monitoring for the bearings …
causes severe problems in the machinery. Therefore, continuous monitoring for the bearings …
Rotational machine Fault diagnosis using Artificial Intelligence (AI) strategies for the operational challenges under variable speed condition: A Review
S Sowmya, M Saimurugan, I Edinbarough - IEEE Access, 2024 - ieeexplore.ieee.org
Rotational machines in industries often encounter uncertainties during operation, are
monitored and diagnosed through machine condition monitoring. Particularly when speed …
monitored and diagnosed through machine condition monitoring. Particularly when speed …