Jun Wang
Orcid: 0000-0002-3392-1020Affiliations:
- University of Nebraska-Lincoln, Power and Energy Systems Laboratory, NE, USA
- University of Science and Technology of China, Department of Precision Machinery and Precision Instrumentation, Hefei, China (former)
According to our database1,
Jun Wang
authored at least 25 papers
between 2012 and 2024.
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Bibliography
2024
Multi-scale style generative and adversarial contrastive networks for single domain generalization fault diagnosis.
Reliab. Eng. Syst. Saf., March, 2024
Sparse Optimization Model Based on Sparse Matrix and Singular Value Vector for Fault Diagnosis of Rolling Bearings.
IEEE Trans. Instrum. Meas., 2024
2023
Federated contrastive prototype learning: An efficient collaborative fault diagnosis method with data privacy.
Knowl. Based Syst., December, 2023
Domain-invariant feature fusion networks for semi-supervised generalization fault diagnosis.
Eng. Appl. Artif. Intell., November, 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
Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.
IEEE Trans. Instrum. Meas., 2023
Sparse Low-Rank Matrix Estimation With Nonconvex Enhancement for Fault Diagnosis of Rolling Bearings.
IEEE Trans. Instrum. Meas., 2023
Dual Contrastive Learning for Semi-Supervised Fault Diagnosis Under Extremely Low Label Rate.
IEEE Trans. Instrum. Meas., 2023
Categorical Feature GAN for Imbalanced Intelligent Fault Diagnosis of Rotating Machinery.
IEEE Trans. Instrum. Meas., 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
Dynamic Balanced Domain-Adversarial Networks for Cross-Domain Fault Diagnosis of Train Bearings.
IEEE Trans. Instrum. Meas., 2022
Federated adversarial domain generalization network: A novel machinery fault diagnosis method with data privacy.
Knowl. Based Syst., 2022
2020
Nonconvex Group Sparsity Signal Decomposition via Convex Optimization for Bearing Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2020
2019
IEEE Trans. Instrum. Meas., 2019
IEEE Access, 2019
2018
Multiscale Filtering Reconstruction for Wind Turbine Gearbox Fault Diagnosis Under Varying-Speed and Noisy Conditions.
IEEE Trans. Ind. Electron., 2018
An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder.
Eng. Appl. Artif. Intell., 2018
2017
Sensor fault detection and isolation for a wireless sensor network-based remote wind turbine condition monitoring system.
Proceedings of the 2017 IEEE Industry Applications Society Annual Meeting, 2017
Rotor current-based fault diagnosis for DFIG wind turbine drivetrain gearboxes using frequency analysis and a deep classifier.
Proceedings of the 2017 IEEE Industry Applications Society Annual Meeting, 2017
2016
IEEE Trans. Instrum. Meas., 2016
Current-Aided Order Tracking of Vibration Signals for Bearing Fault Diagnosis of Direct-Drive Wind Turbines.
IEEE Trans. Ind. Electron., 2016
2015
Adaptive Multiscale Noise Tuning Stochastic Resonance for Health Diagnosis of Rolling Element Bearings.
IEEE Trans. Instrum. Meas., 2015
2012
IEEE Trans. Instrum. Meas., 2012
Effects of multiscale noise tuning on stochastic resonance for weak signal detection.
Digit. Signal Process., 2012