Zhe Yang
Orcid: 0000-0002-4881-0008Affiliations:
- Dongguan University of Technology, School of Mechanical Engineering, China
- Politecnico di Milano, Department of mechanical engineering, Energy Department, Milan, Italy (PhD 2020)
According to our database1,
Zhe Yang
authored at least 19 papers
between 2018 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Few-shot fault diagnosis of particle accelerator power system using a bidirectional discriminative prototype network.
Appl. Soft Comput., 2025
2024
Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform.
IEEE Internet Things J., July, 2024
Multidomain variance-learnable prototypical network for few-shot diagnosis of novel faults.
J. Intell. Manuf., April, 2024
Masked Autoencoder via End-to-End Zero-Shot Learning for Fault Diagnosis of Unseen Classes.
IEEE Trans. Instrum. Meas., 2024
Accelerated degradation testing for lifetime analysis considering random effects and the influence of stress and measurement errors.
Reliab. Eng. Syst. Saf., 2024
2023
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis.
Int. J. Prod. Res., December, 2023
Incrementally Contrastive Learning of Homologous and Interclass Features for the Fault Diagnosis of Rolling Element Bearings.
IEEE Trans. Ind. Informatics, November, 2023
A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data.
Reliab. Eng. Syst. Saf., September, 2023
A novel fault detection method for rotating machinery based on self-supervised contrastive representations.
Comput. Ind., May, 2023
A two-stage estimation method based on Conceptors-aided unsupervised clustering and convolutional neural network classification for the estimation of the degradation level of industrial equipment.
Expert Syst. Appl., 2023
Proceedings of the 26th International Conference on Computer Supported Cooperative Work in Design, 2023
2022
Self-Adaptation Graph Attention Network via Meta-Learning for Machinery Fault Diagnosis With Few Labeled Data.
IEEE Trans. Instrum. Meas., 2022
A Novel Ultrasonic Guided Wave-Based Method for Railway Contact Wire Defect Detection.
IEEE Trans. Instrum. Meas., 2022
Incremental Novelty Identification From Initially One-Class Learning to Unknown Abnormality Classification.
IEEE Trans. Ind. Electron., 2022
A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks.
Reliab. Eng. Syst. Saf., 2022
2021
Proceedings of the Neural Computing for Advanced Applications, 2021
2020
A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments.
IEEE Trans. Neural Networks Learn. Syst., 2020
A novel method for maintenance record clustering and its application to a case study of maintenance optimization.
Reliab. Eng. Syst. Saf., 2020
2018
Automatic Extraction of a Health Indicator from Vibrational Data by Sparse Autoencoders.
Proceedings of the 3rd International Conference on System Reliability and Safety, 2018