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ORCIDZhe Yang 0014
Person information
- affiliation: Dongguan University of Technology, School of Mechanical Engineering, China
- affiliation (PhD 2020): Politecnico di Milano, Department of mechanical engineering, Energy Department, Milan, Italy
Other persons with the same name
- Zhe Yang — disambiguation page
- Zhe Yang 0001 — Microsoft Corporation
- Zhe Yang 0002 — Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Zhe Yang 0003 — Department of Computer Science and Technology, Tongji University, Shanghai, China
- Zhe Yang 0004
![[0000-0001-8483-4616]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-8483-4616")
— Shanghai University of Finance and Economics, School of Economics, China (and 1 more) - Zhe Yang 0005 — Soochow University, Provincial Key Laboratory for Computer Information Processing Technology, China
- Zhe Yang 0006 — University of Posts and Telecommunications, Intelligent Computing and Communication Lab, Beijing, China
- Zhe Yang 0007 — Hong Kong Polytechnic University, Department of Electrical Engineering, Hong Kong (and 2 more)
- Zhe Yang 0008 — Northwestern Polytechnical University, School of Computer Science, Xian, China (and 1 more)
- Zhe Yang 0009 — Blekinge Institute of Technology, Karlskrona, Sweden
- Zhe Yang 0010 — University of Illinois at Urbana-Champaign, Department of Computer Science, Urbana, IL, USA
- Zhe Yang 0011 — Zhengzhou University, School of Mathematics and Statistics, China
- Zhe Yang 0012 — Tsinghua University, Department of Computer Science and Technology, BNRist, China
- Zhe Yang 0013 — Peking University, National Key Laboratory for Multimedia Information Processing, School of Computer Science, China
- Zhe Yang 0015 — New York University, Department of Computer Science, NY, USA
- Zhe Yang 0016 — Harbin Institute of Technology, School of Information Science and Engineering, Weihai, China (and 1 more)
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2020 – today
- 2025
[j16]Zhe Yang, Rongbing Ye, Lingli Jiang, Jianyu Long, Yunwei Huang, Chuan Li:
Few-shot fault diagnosis of particle accelerator power system using a bidirectional discriminative prototype network. Appl. Soft Comput. 170: 112726 (2025)- 2024
- [j15]Liangwei Zhang, Jing Lin, Zhe Yang, Haidong Shao, Biyu Liu, Chuan Li:
Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform. IEEE Internet Things J. 11(13): 23096-23109 (2024) - [j14]Jianyu Long, Yibin Chen, Huiyu Huang, Zhe Yang, Yunwei Huang, Chuan Li:
Multidomain variance-learnable prototypical network for few-shot diagnosis of novel faults. J. Intell. Manuf. 35(4): 1455-1467 (2024) - [j13]Yang Li, Haifeng Gao, Hongtian Chen, Chun Liu, Zhe Yang, Enrico Zio:
Accelerated degradation testing for lifetime analysis considering random effects and the influence of stress and measurement errors. Reliab. Eng. Syst. Saf. 247: 110101 (2024) - [j12]Jianyu Long, Jing Lin, Lingli Jiang, Zhe Yang, Jianwen Guo, Tao Yin, Chuan Li:
Masked Autoencoder via End-to-End Zero-Shot Learning for Fault Diagnosis of Unseen Classes. IEEE Trans. Instrum. Meas. 73: 1-10 (2024) - 2023
- [j11]Zhe Yang, Yunwei Huang, Faisal Nazeer, Yanyang Zi, Gianluca Valentino, Chuan Li, Jianyu Long, Huiyu Huang:
A novel fault detection method for rotating machinery based on self-supervised contrastive representations. Comput. Ind. 147: 103878 (2023) - [j10]Mingjing Xu, Piero Baraldi, Zhe Yang, Enrico Zio:
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. 213(Part): 118962 (2023) - [j9]Jianyu Long, Yibin Chen, Zhe Yang, Yunwei Huang, Chuan Li:
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis. Int. J. Prod. Res. 61(23): 8238-8251 (2023) - [j8]Yuxuan He, Huai Su, Enrico Zio, Shiliang Peng, Lin Fan, Zhaoming Yang, Zhe Yang, Jinjun Zhang:
A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data. Reliab. Eng. Syst. Saf. 237: 109333 (2023) - [j7]Chuan Li, Xiaotong Lei, Yunwei Huang, Faisal Nazeer, Jianyu Long, Zhe Yang:
Incrementally Contrastive Learning of Homologous and Interclass Features for the Fault Diagnosis of Rolling Element Bearings. IEEE Trans. Ind. Informatics 19(11): 11182-11191 (2023) - [c3]Xiaotong Lei, Zhe Yang, Yunwei Huang, Jianyu Long, Chuan Li, Huiyu Huang:
Anomaly Detection of Rolling Element Bearings Based on Contrastive Representation. CSCWD 2023: 528-532 - 2022
- [j6]Zhe Yang, Piero Baraldi, Enrico Zio:
A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks. Reliab. Eng. Syst. Saf. 220: 108278 (2022) - [j5]Zhe Yang, Jianyu Long, Yanyang Zi, Shaohui Zhang, Chuan Li:
Incremental Novelty Identification From Initially One-Class Learning to Unknown Abnormality Classification. IEEE Trans. Ind. Electron. 69(7): 7394-7404 (2022) - [j4]Yong Chang, Nana Li, Jiyuan Zhao, Yu Wang, Zhe Yang:
A Novel Ultrasonic Guided Wave-Based Method for Railway Contact Wire Defect Detection. IEEE Trans. Instrum. Meas. 71: 1-9 (2022) - [j3]Jianyu Long, Rongxin Zhang, Zhe Yang, Yunwei Huang, Yu Liu, Chuan Li:
Self-Adaptation Graph Attention Network via Meta-Learning for Machinery Fault Diagnosis With Few Labeled Data. IEEE Trans. Instrum. Meas. 71: 1-11 (2022) - 2021
- [c2]Yadong Wei, Xiaoman Cai, Jianyu Long, Zhe Yang, Chuan Li:
Self-supervised Contrastive Representation Learning for Machinery Fault Diagnosis. NCAA 2021: 347-359 - 2020
- [j2]Zhe Yang, Piero Baraldi, Enrico Zio:
A novel method for maintenance record clustering and its application to a case study of maintenance optimization. Reliab. Eng. Syst. Saf. 203: 107103 (2020) - [j1]Zhe Yang, Sameer Al-Dahidi, Piero Baraldi, Enrico Zio, Lorenzo Montelatici:
A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments. IEEE Trans. Neural Networks Learn. Syst. 31(1): 309-320 (2020)
2010 – 2019
- 2018
- [c1]Zhe Yang, Piero Baraldi, Enrico Zio:
Automatic Extraction of a Health Indicator from Vibrational Data by Sparse Autoencoders. ICSRS 2018: 328-332
Coauthor Index
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