Federated transfer learning for machinery fault diagnosis: A comprehensive review of technique and application
As a crucial role in the prognostic and health management of mechanical equipment, fault
diagnosis encounters serious challenges, such as the scarcity of fault samples, the high cost …
diagnosis encounters serious challenges, such as the scarcity of fault samples, the high cost …
Intelligent diagnosis method for machine faults based on federated transfer learning
Z Li, Z Li, F Gu - Applied Soft Computing, 2024 - Elsevier
Intelligent fault diagnosis model based on federated learning can effectively solve the
problem of fault data privacy and sharing, and ignores the difference of fault data …
problem of fault data privacy and sharing, and ignores the difference of fault data …
Multi-task federated learning-based system anomaly detection and multi-classification for microservices architecture
J Hao, P Chen, J Chen, X Li - Future Generation Computer Systems, 2024 - Elsevier
The microservices architecture is extensively utilized in cloud-based application
development, characterized by the construction of applications through a series of …
development, characterized by the construction of applications through a series of …
An innovative multisource multibranch metric ensemble deep transfer learning algorithm for tool wear monitoring
Z Gao, N Chen, Y Yang, L Li - Advanced Engineering Informatics, 2024 - Elsevier
The efficient monitoring of tool wear is crucial in ensuring precise part manufacturing and
enhancing machining efficiency during the cutting process. However, the presence of …
enhancing machining efficiency during the cutting process. However, the presence of …
A robust source-free unsupervised domain adaptation method based on uncertainty measure and adaptive calibration for rotating machinery fault diagnosis
Y Lin, Y Wang, M Zhang, M Zhao - Reliability Engineering & System Safety, 2025 - Elsevier
Unsupervised domain adaptation (UDA), usually trained jointly with labeled source data and
unlabeled target data, is widely used to address the problem of lack of labeled data for new …
unlabeled target data, is widely used to address the problem of lack of labeled data for new …
A novel self-supervised representation learning framework based on time-frequency alignment and interaction for mechanical fault diagnosis
Recently, supervised learning methods for intelligent mechanical fault diagnosis have
achieved considerable advancements, while they heavily rely on labeled information and …
achieved considerable advancements, while they heavily rely on labeled information and …
An innovative Multisource Lightweight Adaptive Replayed Online Deep Transfer Learning algorithm for tool wear monitoring
Z Gao, N Chen, Y Yang, L Li - Journal of Manufacturing Processes, 2024 - Elsevier
Accurately monitoring tool wear during the cutting process is crucial for ensuring the
precision manufacturing of components and enhancing machining efficiency. However …
precision manufacturing of components and enhancing machining efficiency. However …
Federated transfer learning-based distributed fault diagnosis method for rolling bearings
G Yang, J Su, S Du, Q Duan - Measurement Science and …, 2024 - iopscience.iop.org
Current methods for bearing fault diagnosis often fall short in addressing data privacy
concerns and typically rely on one-to-one transfer strategies, which are inadequate for …
concerns and typically rely on one-to-one transfer strategies, which are inadequate for …
Structural graph federated learning: Exploiting high-dimensional information of statistical heterogeneity
With the recent progress in graph-federated learning (GFL), it has demonstrated a promising
performance in effectively addressing challenges associated with heterogeneous clients …
performance in effectively addressing challenges associated with heterogeneous clients …
PersistVerify: Federated model ownership verification with spatial attention and boundary sampling
Federated learning, known for its emphasis on privacy and resource efficiency, has emerged
as a transformative paradigm in the fields of artificial intelligence and industrial machine …
as a transformative paradigm in the fields of artificial intelligence and industrial machine …