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 …
Intelligent fault diagnosis of rolling bearing based on novel CNN model considering data imbalance
Z Xing, R Zhao, Y Wu, T He - Applied Intelligence, 2022 - Springer
The intelligent fault diagnosis method based on deep learning has become a powerful tool
for analyzing mechanical big data. However, a large proportion of collected data belong to …
for analyzing mechanical big data. However, a large proportion of collected data belong to …
Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization
Deep learning has attracted attentions in intelligent fault diagnosis of machinery because it
allows a deep network to accomplish the tasks of feature learning and fault classification …
allows a deep network to accomplish the tasks of feature learning and fault classification …
A unified framework incorporating predictive generative denoising autoencoder and deep Coral network for rolling bearing fault diagnosis with unbalanced data
X Li, H Jiang, S Liu, J Zhang, J Xu - Measurement, 2021 - Elsevier
In practical engineering, data imbalance is an urgent problem to be solved for rolling
bearing fault diagnosis. This paper proposes a unified framework incorporating predictive …
bearing fault diagnosis. This paper proposes a unified framework incorporating predictive …
Imbalanced fault diagnosis of rolling bearing using improved MsR-GAN and feature enhancement-driven CapsNet
Traditional fault diagnosis approaches of rolling bearing often need abundant labeled data
in advance while some certain fault data are difficult to be acquired in engineering …
in advance while some certain fault data are difficult to be acquired in engineering …
Bearing fault diagnosis with a feature fusion method based on an ensemble convolutional neural network and deep neural network
H Li, J Huang, S Ji - Sensors, 2019 - mdpi.com
Rolling bearings are the core components of rotating machinery. Their health directly affects
the performance, stability and life of rotating machinery. To prevent possible damage, it is …
the performance, stability and life of rotating machinery. To prevent possible damage, it is …
Imbalanced fault diagnosis of rolling bearing using enhanced generative adversarial networks
H Zhang, R Wang, R Pan, H Pan - IEEE Access, 2020 - ieeexplore.ieee.org
Machinery fault diagnosis tasks have been well addressed when sufficient and abundant
data are available. However, the data imbalance problem widely exists in real-world …
data are available. However, the data imbalance problem widely exists in real-world …
A multi-input and multi-task convolutional neural network for fault diagnosis based on bearing vibration signal
Y Wang, M Yang, Y Li, Z Xu, J Wang… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Bearing fault diagnosis is essential for the safe and stable operation of rotating machinery.
Existing methods use signals from a single dimension, limiting diagnostic generality and …
Existing methods use signals from a single dimension, limiting diagnostic generality and …
Rolling bearing fault diagnosis using hybrid neural network with principal component analysis
K You, G Qiu, Y Gu - Sensors, 2022 - mdpi.com
With the rapid development of fault prognostics and health management (PHM) technology,
more and more deep learning algorithms have been applied to the intelligent fault diagnosis …
more and more deep learning algorithms have been applied to the intelligent fault diagnosis …