STUDY ON DETECTION METHOD OF ROTOR AERODYNAMIC IMBALANCE BASED ON CONVOLUTIONAL NEURAL NETWORK

被引：0

作者：

Yang, Wangchun ^{[1
]}

Liang, Xue ^{[2
]}

Sun, Chuanzong ^{[3
]}

机构：

[1] Guodian Power Guangxi Wind Power Development Co.,Ltd., Beihai

[2] Liaoning Zhongke Jingchuang Intelligent Energy Co.,Ltd., Shenyang

[3] School of Mechanical Engineering, Shenyang University of Technology, Shenyang

来源：

Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2025年 / 46卷 / 03期

关键词：

convolutional neural network; fault diagnosis; machine learning; rotor imbalance; wind turbines;

D O I：

10.19912/j.0254-0096.tynxb.2023-1764

中图分类号：

学科分类号：

摘要：

For the problem of identification for rotor imbalance in wind turbine,and to reduce the operation and maintenance cost of wind turbine,an identification method of rotor imbalance based on one-dimensional convolutional neural network is proposed. Firstly, the combination of variational mode decomposition(VMD)and correlation kurtosis calculation is used to realize the perception of the rotor aerodynamic imbalance. Secondly,a recognition method of aerodynamic imbalance based on one-dimensional convolutional neural network is proposed,and the vibration acceleration of the nacelle is taken as the input to identify the specific magnitude of the rotor aerodynamic imbalance. Finally cross-validation was performed in different turbulence intensity and noise environments,and the identification accuracy of the cross validation was more than 95%,which proved that the method could be applied to the diagnosis of rotor imbalance and improve the safety of wind turbine. © 2025 Science Press. All rights reserved.

引用

页码：531 / 537

页数：6

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