3 citations · 4 across the 5 of their papers we have counts for
5 papers
PHM-Bench: A Domain-Specific Benchmarking Framework for Systematic Evaluation of Large Models in Prognostics and Health Management
Puyu Yang, Laifa Tao, Zijian Huang +11
With the rapid advancement of generative artificial intelligence, large language models (LLMs) are increasingly adopted in industrial domains, offering new opportunities for Progno…
UBMF: Uncertainty-Aware Bayesian Meta-Learning Framework for Fault Diagnosis with Imbalanced Industrial Data
Zhixuan Lian, Shangyu Li, Qixuan Huang +5
Fault diagnosis of mechanical equipment involves data collection, feature extraction, and pattern recognition but is often hindered by the imbalanced nature of industrial data, int…
Pre-Trained Large Language Model Based Remaining Useful Life Transfer Prediction of Bearing
Laifa Tao, Zhengduo Zhao, Xuesong Wang +8
Accurately predicting the remaining useful life (RUL) of rotating machinery, such as bearings, is essential for ensuring equipment reliability and minimizing unexpected industrial…
LLM-R: A Framework for Domain-Adaptive Maintenance Scheme Generation Combining Hierarchical Agents and RAG
Laifa Tao, Qixuan Huang, Xianjun Wu +5
The increasing use of smart devices has emphasized the critical role of maintenance in production activities. Interactive Electronic Technical Manuals (IETMs) are vital tools that…
An Outline of Prognostics and Health Management Large Model: Concepts, Paradigms, and Challenges
Laifa Tao, Shangyu Li, Haifei Liu +18
Prognosis and Health Management (PHM), critical for ensuring task completion by complex systems and preventing unexpected failures, is widely adopted in aerospace, manufacturing, m…