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Profil
| Derzeitige Stellung | Post Doc |
|---|---|
| Fachgebiet | Automatisierungstechnik, Mechatronik, Regelungssysteme, Intelligente Technische Systeme, Robotik |
| Keywords | Condition monitoring, Deep learning, Robot system, Reliability analysis, Harmonic reducer |
Aktuelle Kontaktadresse
| Land | China, VR |
|---|---|
| Ort | Hongkong |
| Universität/Institution | Hong Kong Polytechnic University |
| Institut/Abteilung | Department of Industrial and Systems Engineering |
Gastgeber*innen während der Förderung
| Prof. Dr.-Ing. Michael Beer | Institut für Risiko und Zuverlässigkeit, Gottfried Wilhelm Leibniz Universität Hannover, Hannover |
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Programm(e)
| 2026 | Humboldt-Forschungsstipendien-Programm für Postdocs |
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Publikationen (Auswahl)
| 2026 | Yuxin Sun, Huilin Zhu, Yadong Xu*, Ke Feng, Zhenhua Xiong, JC Ji, Michael Beer: A Class-Aware Supervised Contrastive Graph Network for CNC machining condition monitoring with class-imbalanced data. In: Mechanical Systems and Signal Processing, 256, 2026, 114479 |
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| 2026 | Yadong Xu, Sheng Li, Zhihan Li, Kaili Wu, Ruyi Huang, Beibei Sun, JC Ji: Time–frequency fully-connected graph neural network: An effective multiscale spatiotemporal dependency learning method for multisource machine fault diagnosis. In: Advanced Engineering Informatics, 69, 2026, 104023 |
| 2025 | Yadong Xu, JC Ji, Yuxin Sun, Sihan Huang, Zhiheng Zhao, George Q Huang: Self-supervised time–frequency feature alignment for process monitoring of cyber–physical CNC machines. In: Journal of Manufacturing Systems, 82, 2025, 1145-1157 |