Deep learning modelling techniques: current progress, applications, advantages, and challenges
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
[HTML][HTML] A systematic review of rolling bearing fault diagnoses based on deep learning and transfer learning: Taxonomy, overview, application, open challenges …
M Hakim, AAB Omran, AN Ahmed, M Al-Waily… - Ain Shams Engineering …, 2023 - Elsevier
Rolling bearing fault detection is critical for improving production efficiency and lowering
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …
Intelligent fault diagnosis by fusing domain adversarial training and maximum mean discrepancy via ensemble learning
Y Li, Y Song, L Jia, S Gao, Q Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Nowadays, the industrial Internet of Things (IIoT) has been successfully utilized in smart
manufacturing. The massive amount of data in IIoT promote the development of deep …
manufacturing. The massive amount of data in IIoT promote the development of deep …
A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
A hybrid generalization network for intelligent fault diagnosis of rotating machinery under unseen working conditions
The data-driven methods in machinery fault diagnosis have become increasingly popular in
the past two decades. However, the wide applications of this scheme are generally …
the past two decades. However, the wide applications of this scheme are generally …
Deep learning algorithms for bearing fault diagnostics—A comprehensive review
In this survey paper, we systematically summarize existing literature on bearing fault
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review
A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
Intelligent fault diagnosis of rolling bearings under imbalanced data conditions using attention-based deep learning method
J Li, Y Liu, Q Li - Measurement, 2022 - Elsevier
Data-driven intelligent method has been widely used in fault diagnostics. However, it is
observed that previous research studies focusing on imbalanced datasets for fault diagnosis …
observed that previous research studies focusing on imbalanced datasets for fault diagnosis …
Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions
Intelligent fault detection and diagnosis, as an important approach, play a crucial role in
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …