Automatic Extraction of a Health Indicator from Vibrational Data by Sparse Autoencoders. - Zhe Yang 014; Piero Baraldi; Enrico Zio (ICSRS, 2018)

A novel method for maintenance record clustering and its application to a case study of maintenance optimization. - Zhe Yang 014; Piero Baraldi; Enrico Zio (Reliab. Eng. Syst. Saf., 2020)

A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments. - Zhe Yang 014; Sameer Al-Dahidi; Piero Baraldi; Enrico Zio; Lorenzo Montelatici (IEEE Trans. Neural Networks Learn. Syst., 2020)

Self-supervised Contrastive Representation Learning for Machinery Fault Diagnosis. - Yadong Wei; Xiaoman Cai; Jianyu Long; Zhe Yang 014; Chuan Li 003 (NCAA, 2021)

A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks. - Zhe Yang 014; Piero Baraldi; Enrico Zio (Reliab. Eng. Syst. Saf., 2022)

Incremental Novelty Identification From Initially One-Class Learning to Unknown Abnormality Classification. - Zhe Yang 014; Jianyu Long; Yanyang Zi; Shaohui Zhang; Chuan Li 003 (IEEE Trans. Ind. Electron., 2022)

A Novel Ultrasonic Guided Wave-Based Method for Railway Contact Wire Defect Detection. - Yong Chang; Nana Li; Jiyuan Zhao; Yu Wang 043; Zhe Yang 014 (IEEE Trans. Instrum. Meas., 2022)

Self-Adaptation Graph Attention Network via Meta-Learning for Machinery Fault Diagnosis With Few Labeled Data. - Jianyu Long; Rongxin Zhang; Zhe Yang 014; Yunwei Huang; Yu Liu; Chuan Li 003 (IEEE Trans. Instrum. Meas., 2022)

Anomaly Detection of Rolling Element Bearings Based on Contrastive Representation. - Xiaotong Lei; Zhe Yang 014; Yunwei Huang; Jianyu Long; Chuan Li 003; Huiyu Huang (CSCWD, 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. - Mingjing Xu; Piero Baraldi; Zhe Yang 014; Enrico Zio (Expert Syst. Appl., 2023)

A novel fault detection method for rotating machinery based on self-supervised contrastive representations. - Zhe Yang 014; Yunwei Huang; Faisal Nazeer; Yanyang Zi; Gianluca Valentino; Chuan Li 003; Jianyu Long; Huiyu Huang (Comput. Ind., 2023)

A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data. - Yuxuan He; Huai Su; Enrico Zio; Shiliang Peng; Lin Fan; Zhaoming Yang; Zhe Yang 014; Jinjun Zhang (Reliab. Eng. Syst. Saf., 2023)

Incrementally Contrastive Learning of Homologous and Interclass Features for the Fault Diagnosis of Rolling Element Bearings. - Chuan Li 003; Xiaotong Lei; Yunwei Huang; Faisal Nazeer; Jianyu Long; Zhe Yang 014 (IEEE Trans. Ind. Informatics, 2023)

A novel self-training semi-supervised deep learning approach for machinery fault diagnosis. - Jianyu Long; Yibin Chen; Zhe Yang 014; Yunwei Huang; Chuan Li 003 (Int. J. Prod. Res., 2023)

Accelerated degradation testing for lifetime analysis considering random effects and the influence of stress and measurement errors. - Yang Li 088; Haifeng Gao; Hongtian Chen; Chun Liu 006; Zhe Yang 014; Enrico Zio (Reliab. Eng. Syst. Saf., 2024)

Masked Autoencoder via End-to-End Zero-Shot Learning for Fault Diagnosis of Unseen Classes. - Jianyu Long; Jing Lin 003; Lingli Jiang; Zhe Yang 014; Jianwen Guo; Tao Yin; Chuan Li 003 (IEEE Trans. Instrum. Meas., 2024)

Multidomain variance-learnable prototypical network for few-shot diagnosis of novel faults. - Jianyu Long; Yibin Chen; Huiyu Huang; Zhe Yang 014; Yunwei Huang; Chuan Li 003 (J. Intell. Manuf., 2024)

Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform. - Liangwei Zhang; Jing Lin 003; Zhe Yang 014; Haidong Shao; Biyu Liu; Chuan Li 003 (IEEE Internet Things J., 2024)

Few-shot fault diagnosis of particle accelerator power system using a bidirectional discriminative prototype network. - Zhe Yang 014; Rongbing Ye; Lingli Jiang; Jianyu Long; Yunwei Huang; Chuan Li 003 (Appl. Soft Comput., 2025)