Rui Wang
Orcid: 0000-0001-8960-596XAffiliations:
- Soochow University, School of Rail Transportation, Suzhou, China
- Anhui University, Anhui Engineering Laboratory of Human Robot Integration System Equipment, Hefei, China
According to our database1,
Rui Wang
authored at least 12 papers
between 2020 and 2024.
Collaborative distances:
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Bibliography
2024
Non-Uniformly Weighted Multisource Domain Adaptation Network For Fault Diagnosis Under Varying Working Conditions.
Neural Process. Lett., April, 2024
2023
Graph embedding deep broad learning system for data imbalance fault diagnosis of rotating machinery.
Reliab. Eng. Syst. Saf., December, 2023
Federated contrastive prototype learning: An efficient collaborative fault diagnosis method with data privacy.
Knowl. Based Syst., December, 2023
A novel domain generalization network with multidomain specific auxiliary classifiers for machinery fault diagnosis under unseen working conditions.
Reliab. Eng. Syst. Saf., October, 2023
Cross-domain privacy-preserving broad network for fault diagnosis of rotating machinery.
Adv. Eng. Informatics, October, 2023
Prototype-Driven Class-Wise Adversarial Transfer Networks for Partial Domain Fault Diagnosis of Rolling Bearings.
IEEE Trans. Instrum. Meas., 2023
Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.
IEEE Trans. Instrum. Meas., 2023
Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis.
Knowl. Based Syst., 2023
Multi-stage distribution correction: A promising data augmentation method for few-shot fault diagnosis.
Eng. Appl. Artif. Intell., 2023
2022
Multisource Domain Feature Adaptation Network for Bearing Fault Diagnosis Under Time-Varying Working Conditions.
IEEE Trans. Instrum. Meas., 2022
Federated adversarial domain generalization network: A novel machinery fault diagnosis method with data privacy.
Knowl. Based Syst., 2022
2020
Imbalanced Fault Diagnosis of Rolling Bearing Using Enhanced Generative Adversarial Networks.
IEEE Access, 2020