Dr. Shengfei Ji , China University of Mining and Technology, China
Shengfei Ji is a dedicated Ph.D. candidate in Mechatronic Engineering at the School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, P.R. China. With a strong academic and technical background, he focuses on developing intelligent systems to enhance the operational reliability of hydraulic machinery. His passion for research and innovation in fault diagnosis and predictive modeling has led to several impactful publications in renowned journals.
Publication Profile
Scopus
ORCID
🎓 Education Background
Shengfei Ji is currently pursuing his Ph.D. in Mechatronic Engineering at China University of Mining and Technology, where he is engaged in advanced studies on intelligent condition monitoring systems. His academic foundation includes rigorous training in machine learning, system dynamics, and hydraulic machinery.
💼 Professional Experience
As a Ph.D. researcher, Shengfei has collaborated with a multidisciplinary team on projects involving construction machinery and intelligent fault detection. His work involves both theoretical research and practical application, integrating AI technologies like graph convolutional networks and LSTM models with mechanical systems. He has co-authored research with industry and academic experts, further expanding his expertise in smart diagnostics.
🏆 Awards and Honors
While formal awards and grants are not currently listed, Shengfei Ji’s work has gained recognition in the academic community with citations in 19 documents and a Scopus h-index of 2, reflecting growing interest in his innovative contributions to intelligent machinery diagnostics.
🔬 Research Focus
Shengfei Ji’s core research interests lie in intelligent fault diagnosis 🛠️, anomaly detection 🚨, and condition monitoring 📡 of hydraulic systems used in construction machinery. His work primarily applies deep learning and graph-based methods to create predictive models that enhance machine efficiency and reliability.
📝 Conclusion
With a strong commitment to integrating AI with mechanical systems, Shengfei Ji is emerging as a promising researcher in the field of mechatronic engineering. His scientific contributions reflect a unique intersection of engineering insight and computational intelligence, positioning him for continued academic and industrial impact 🌐.
📚 Top Publications
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Multivariate Prediction Soft Sensor Model for Truck Cranes Based on Graph Convolutional Network and Random Forest
Published in: Actuators, 2024
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A Soft Sensor Model for Predicting the Flow of a Hydraulic Pump Based on Graph Convolutional Network–Long Short-Term Memory
Published in: Actuators, 2024
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Bucket Teeth Detection Based on Faster Region Convolutional Neural Network
Published in: IEEE Access, 2021
Cited by: 19 articles