摘要
模态参数可以为风机日常运行和健康预警提供关键的数据支持。分析盲信号原理与振动信号之间的关系,提出了一种改进的二阶盲辨识法识别风机结构的模态参数,并利用该方法对某风电场2 MW风机结构的现场实测数据进行分析,得到其一阶自振频率为0.416 Hz,与风机厂家给出的一阶自振频率和基于数据驱动的随机子空间法的识别结果基本一致,验证了该方法的有效性。该识别方法具有快捷方便和所需测试数据易于获得等优点。
Model parameters can provide key data support for the daily operation and health warning of wind turbines.By analyzing the relationship between the blind signal principle and the vibration signals,an improved second-order blind identification method(SOBI)is proposed to identify the modal parameters of wind turbine structures.Then,the on-site measured data of a 2 MW wind turbine structure is analyzed with the proposed method.It shows that the first-order natural frequency of the structure is 0.416 Hz,which is consistent with the value provided by the manufacturer and the identification result based on the data-driven stochastic subspace method.The effectiveness of the proposed method is thus verified.It also shows that the method is of advantages of being fast,convenient,and easy to get the required test data.
作者
易晓波
曾腾
YI Xiaobo;ZEN Teng(Jiangxi Datang International New Energy Co.,Ltd.,Nanchang 330100,China)
出处
《水电与新能源》
2023年第12期19-22,39,共5页
Hydropower and New Energy
关键词
风电塔筒
SOBI
矩阵束法
模态参数识别
wind turbine tower
SOBI
matrix pencil method
modal parameter identification
