Wei Zhang
Orcid: 0000-0001-6478-3110Affiliations:
- Shenyang Aerospace University, School of Aerospace Engineering, China
- Northeastern University, MOE Key Laboratory of Vibration and Control of Aero-Propulsion System, Shenyang, China
- Tianjin University, China (PhD 2017)
According to our database1,
Wei Zhang
authored at least 21 papers
between 2017 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2025
Denoising diffusion probabilistic model-enabled data augmentation method for intelligent machine fault diagnosis.
Eng. Appl. Artif. Intell., 2025
2023
Blockchain-based decentralized federated transfer learning methodology for collaborative machinery fault diagnosis.
Reliab. Eng. Syst. Saf., 2023
2022
Degradation Alignment in Remaining Useful Life Prediction Using Deep Cycle-Consistent Learning.
IEEE Trans. Neural Networks Learn. Syst., 2022
2021
Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning.
IEEE Trans. Ind. Informatics, 2021
Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning.
IEEE Trans. Ind. Informatics, 2021
Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics.
IEEE Trans. Ind. Electron., 2021
Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions.
Reliab. Eng. Syst. Saf., 2021
Federated learning for machinery fault diagnosis with dynamic validation and self-supervision.
Knowl. Based Syst., 2021
2020
Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning.
IEEE Trans. Ind. Informatics, 2020
Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different Places.
IEEE Trans. Ind. Electron., 2020
Partial transfer learning in machinery cross-domain fault diagnostics using class-weighted adversarial networks.
Neural Networks, 2020
Data alignments in machinery remaining useful life prediction using deep adversarial neural networks.
Knowl. Based Syst., 2020
Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation.
J. Intell. Manuf., 2020
Domain generalization in rotating machinery fault diagnostics using deep neural networks.
Neurocomputing, 2020
Intelligent cross-machine fault diagnosis approach with deep auto-encoder and domain adaptation.
Neurocomputing, 2020
2019
Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks.
IEEE Trans. Ind. Electron., 2019
Signal Process., 2019
Understanding and improving deep learning-based rolling bearing fault diagnosis with attention mechanism.
Signal Process., 2019
Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction.
Reliab. Eng. Syst. Saf., 2019
2018
A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning.
Neurocomputing, 2018
2017
Dynamic Analysis of a Rotor System Supported on Squeeze Film Damper with Air Entrainment.
Int. J. Bifurc. Chaos, 2017