FedCAE: a new federated learning framework for edge-cloud collaboration based machine fault diagnosis
Y Yu, L Guo, H Gao, Y He, Z You… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the coming of the industrial Big Data era, data-driven fault diagnosis models emerge
recently and show potential results in many studies. However, it is impractical to collect …
recently and show potential results in many studies. However, it is impractical to collect …
Adaptive privacy-preserving federated learning for fault diagnosis in internet of ships
Z Zhang, C Guan, H Chen, X Yang… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The recent appearance of Internet of Things (IoT) technologies applied in the maritime
industry has introduced the Internet of Ships (IoS) paradigm. By leveraging IoS and deep …
industry has introduced the Internet of Ships (IoS) paradigm. By leveraging IoS and deep …
Spatial graph convolutional neural network via structured subdomain adaptation and domain adversarial learning for bearing fault diagnosis
Unsupervised domain adaptation (UDA) has shown remarkable results in fault diagnosis
under changing working conditions in recent years. However, most UDA methods do not …
under changing working conditions in recent years. However, most UDA methods do not …
Federated zero-shot industrial fault diagnosis with cloud-shared semantic knowledge base
B Li, C Zhao - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Recently, a considerable literature has grown up around the few-sample fault diagnosis
task, in which few samples of fault data are available for model training. The lack of fault …
task, in which few samples of fault data are available for model training. The lack of fault …
A novel method based on deep transfer unsupervised learning network for bearing fault diagnosis under variable working condition of unequal quantity
H Su, X Yang, L Xiang, A Hu, Y Xu - Knowledge-based systems, 2022 - Elsevier
Recently, intelligent fault recognition means have been progressed rapidly and have
attained marvelous achievement. Most of them have an assumption where those source and …
attained marvelous achievement. Most of them have an assumption where those source and …
FedRUL: A new federated learning method for edge-cloud collaboration based remaining useful life prediction of machines
L Guo, Y Yu, M Qian, R Zhang, H Gao… - … ASME Transactions on …, 2022 - ieeexplore.ieee.org
In real industrial applications, intelligent methods are recently emerging for remaining useful
life (RUL) prediction. However, their development is hindered by two obstacles. First, it is …
life (RUL) prediction. However, their development is hindered by two obstacles. First, it is …
Semi-supervised federated heterogeneous transfer learning
Federated learning (FL) is a privacy-preserving paradigm that collaboratively train machine
learning models with distributed data stored in different silos without exposing sensitive …
learning models with distributed data stored in different silos without exposing sensitive …
Diagnosis of interturn short-circuit faults in permanent magnet synchronous motors based on few-shot learning under a federated learning framework
J Zhang, Y Wang, K Zhu, Y Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A large amount of labeled data are important to enhance the performance of deep-learning-
based methods in the area of fault diagnosis. Because it is difficult to obtain high-quality …
based methods in the area of fault diagnosis. Because it is difficult to obtain high-quality …
Deep learning framework for predictive modeling of crude oil price for sustainable management in oil markets
AA Salamai - Expert Systems with Applications, 2023 - Elsevier
Crude oil price predictability has continually been considered as a fundamental argument of
finance literature, given its critical propositions for risk management, investment decisions …
finance literature, given its critical propositions for risk management, investment decisions …
An efficient federated transfer learning framework for collaborative monitoring of wind turbines in IoE-enabled wind farms
Wind turbine (WT) condition monitoring has gained increasing interests in the era of the
Internet of Energy (IoE), and existing monitoring approaches mainly focus on training a …
Internet of Energy (IoE), and existing monitoring approaches mainly focus on training a …