基于摄影测量的大型风机叶片运行模态分析

Operation modal analysis of large wind turbine blades based on photogrammetry

针对大型风力发电机叶片振动模态在线测量的问题,运用摄影测量结合协方差驱动随机子空间法对工作中的大型风机叶片进行动态模态分析。首先,通过摄影测量得到叶片上关键测点的轨迹;然后,通过协方差驱动随机子空间法对得到轨迹的进行运行模态分析,得到被测叶片的模态参数,包括固有频率、固有阻尼和模态振型。由于实地测量困难,所以通过GH Bladed仿真建立2MW风机和风场模型并模拟得到叶片上若干目标点的运行轨迹,利用提出的方法计算叶片的模态参数。实验结果表明,一~五阶模态的固有频率相对误差小于1.4%,振型相对误差小于10.0%,验证了摄影测量和协方差驱动随机子空间法应用在大尺寸风机叶片模态分析的正确性。并将该方法应用在一架3.5m叶片的风机实测中,得到其固有频率,验证了摄影测量和协方差驱动随机子空间法的可行性。

Aiming at the problem of on-line measurement of vibration modes of large wind turbine blades,photogrammetry and covariance random subspace method are used to analyze the modes of large wind turbine blades at work.Firstly,the trajectories of key measurement points on the blades are obtained by photogrammetry.Then,the obtained data are analyzed by covariance driven random subspace,and the modal parameters of the tested blade are obtained,including natural frequency,natural damping and modal mode.Because field measurement is difficult,a 2 MW wind turbine and wind field model were set up by GH Bladed,and the moving path of target points on the blade was simulated,and the modal parameters of the blade were calculated by using the proposed method.The experimental results show that the natural frequency relative error of the first to fifth order modes is less than 1.4%,and the relative error of the modes is less than 10.0%,which verifies the feasibility of photogrammetry and covariance driven random subspace method in the modal analysis of large wind turbine blades.The method is applied to a 3.5 m blade wind turbine to obtain its natural frequency,which verifies the feasibility of photogrammetry and covariance driven random subspace method.