Chenye Hu
Orcid: 0000-0002-8424-1615
According to our database1,
Chenye Hu
authored at least 13 papers
between 2023 and 2025.
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Bibliography
2025
Unified Flowing Normality Learning for Rotating Machinery Anomaly Detection in Continuous Time-Varying Conditions.
IEEE Trans. Cybern., January, 2025
Learning Interpretable and Transferable Representations via Wavelet-Constrained Transformer for Industrial Acoustic Diagnosis.
IEEE Trans. Instrum. Meas., 2025
An Incremental Learning Method With Feature-Attention Distillation and Logit Adjustment for Rotating Machinery Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2025
Normality Aggregation and Abnormality Separation Contrastive Learning for Mechanical Anomaly Detection.
IEEE Trans. Instrum. Meas., 2025
Sequence to sequence network with Bayesian attention and state transition for self-data-driven remaining useful life estimation.
Expert Syst. Appl., 2025
Learning globally ordered and locally consistent degradation representations for remaining useful life prediction.
Adv. Eng. Informatics, 2025
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2025
T2Net: An Attention-Enhanced Network for Trustworthy Thermal Imaging-Based Lubrication System Condition Assessment.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2025
2024
WavFormer: An Interpretable Wavelet-Constrained Transformer for Industrial Acoustics Diagnosis.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2024
NorCLR: A Normality-Aggregated Contrastive Learning Framework for Mechanical Anomaly Detection.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2024
2023
Intelligent temporal detection network for boundary-sensitive flight regime recognition.
Eng. Appl. Artif. Intell., November, 2023
Interinstance and Intratemporal Self-Supervised Learning With Few Labeled Data for Fault Diagnosis.
IEEE Trans. Ind. Informatics, May, 2023
Eng. Appl. Artif. Intell., April, 2023