【摘要】 对风电叶片进行基于单通道盲源分离的模态参数识别，通过对比损伤前后的模态参数变化，可评估叶片损伤状况。首先，利用优化同步提取变换（OSSET）对振动信号进行时频分析，观察时频图中能量集中频带个数以确定变分模态分解（VMD）参数K的取值。其次，用VMD将振动信号分解形成K个本征模态函数（IMF），对分解后的IMF进行线性混合降维，并与源信号混合形成新的观测信号。然后，基于信号稀疏性的源信号分离算法获取各单模态信号。最后，用单模态识别技术进行模态参数识别，为基于运行模态参数分析的风电叶片损伤识别提供应用参考。更多还原

【Abstract】 Modal parameters of wind turbine blades can be utilized to evaluate damage conditions by comparing changes in modal parameters before and after damage. Firstly, the optimized synchrosqueezing transform(OSSET) is employed to perform time-frequency analysis on vibration signals. The number of energy-concentrated frequency bands in the time-frequency diagram is observed to determine the parameter K for variational mode decomposition(VMD). Subsequently, VMD is applied to decompose the observed signal into K intrinsic mode functions(IMFs). The decomposed IMFs undergo linear mixing for dimensionality reduction and are combined with source signals to form new observed signals. A source separation algorithm based on signal sparsity is then implemented to extract individual modal signals. Finally, single-modal identification techniques are adopted to identify modal parameters, providing a methodological reference for damage detection in wind turbine blades based on operational modal parameter analysis.更多还原