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Fault Data Identification in Condition Monitoring Systems for Wind Turbine Generator Bearings Based on BERT Model
Power Generation Technology Vol. 47, Issue 4, Pages: 731-741(2026)
Frontier AI Technologies and Large Model Applications for New Power Systems|Updated：2026-09-01
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Fault Data Identification in Condition Monitoring Systems for Wind Turbine Generator Bearings Based on BERT Model
- “It is difficult to identify faults in the bearings of wind turbine generators in a timely manner. In order to reduce safety hazards and economic losses, a data processing and analysis method for the condition monitoring system (CMS) of wind turbine generator bearings based on the BERT large model is proposed, with a recognition accuracy of 98.75%. This provides a reference for improving the intelligence and refinement level of wind turbine condition monitoring.”
DOI：10.12096/j.2096-4528.pgt.260405
Revised：2026-01-24
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Related Author
LIU Zhan
LIU Jianxun
BAO Yanyang
LI Dazi
ZHANG Bo
TANG Wei
ZHOU Yiming
FU Mingzhi
Related Institution
Beijing Pukang Measurement and Monitoring Tech Co., Ltd., Fengtai District
College of Information Science and Technology, Beijing University of Chemical Technology, Chaoyang District
Huaneng Clean Energy Research Institute, Changping District
Huadian Coal Industry Group Co., Ltd., Xicheng District
School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Haidian District
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