您当前的位置：
首页 >
文章列表页 >
Fatigue Load Prediction of Wind Turbine Drive Train Based on CNN-BiLSTM
Key Technologies for Transient Operation Control and Test Verification of Wind Turbines | 更新时间：2025-10-29

    • Fatigue Load Prediction of Wind Turbine Drive Train Based on CNN-BiLSTM

    • “In the field of wind turbine transmission systems, experts have proposed a fatigue load prediction model based on CNN BiLSTM, which effectively improves the accuracy of load prediction.”
    • Electric Power   Vol. 58, Issue 4, Pages: 90-97(2025)

    • DOI：10.11930/j.issn.1004-9649.202409072    

      CLC：

    • Received：18 September 2024，

      Revised：2025-03-14，

      Published：28 May 2025

    移动端阅览

  • Xiaodong WANG, Qing LI, Deyi FU, et al. Fatigue Load Prediction of Wind Turbine Drive Train Based on CNN-BiLSTM[J]. Electric power, 2025, 58(4): 90-97. DOI： 10.11930/j.issn.1004-9649.202409072.

  •  
  •  

0

Views

0

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Wind Turbine Generator Winding Temperature Prediction Based on XGBoost and LSTM
Research and Development of Nondestructive Detection Technology for Wind Turbine Blades
Compound Fault Feature Extraction of Wind Power Gearbox Based on DRS and Improved Autogram
Influence of Converter DC Bus Overvoltage on Wind Turbine High Voltage Ride Through Capabilities

Related Author

Yibing LIU
Shiming WU
Yike HUANG
Wei TENG
Xinwei HUANG
Yibing LIU
Wei TENG
Lei WANG

Related Institution

Key Laboratory of Power Station Energy Transfer Conversion and System, North China Electric Power University
Beijing Envada Software Engineering Co., Ltd.
Key Laboratory of Power Station Energy Transfer, Conversion and System, Ministry of Education, North China Electric Power University
Key Laboratory of Power Station Energy Transfer Conversion and System (North China Electric Power University)
North China Electric Power University
0