为了实现航空发动机转子叶片的在线振动测量,采用了微波传感技术对发动机转子叶片振动测量进行研究。推导了三自由度叶片机械机构的动力学数学模型,通过状态空间方程得到观测方程和观测向量,进而了解到观测矩阵,其转换矩阵可辨识频率、阻尼比和振幅。建立了一种辨识叶轮失谐时模态性能的仿真模型,解决了微波探头发射波形相位与壳体叶片尖端间隙的拟合关系,对脉冲极值和采样率进行了分析。该方法能较好地进行检测数据的特征提取与分析,获得转子叶片频率、阻尼、振幅等振动信息,得到最大响应频率5 MHz,间隙分辨率为25 μm。改进了转子叶片模态参数辨识和叶间隙振动测量方法,适合在一些苛刻的环境下运作,提升了发动机的振动检测能力。

The status detection for rotating parts is difficult since the sensor is influenced by the rotation in the inflammable, explosive, and strong magnetic environment. Based on the fiber Bragg grating sensing technology, this paper studies the influence of the natural frequency and deformation of a rotor blade affected by the size of crack in the blade. Test results show that the speed of the equipment and blade excited vibration frequency are two main factors or deformation and vibration frequency of the blade. With an increase in the crack depth, the blade deformation is increased while the stimulated natural frequency of the blade is decreased; at a low rotational speed, the deformation is mainly caused by the rotating speed of the blade. On the contrary, the vibration blade itself contributes to the deformation at a high speed. During the process of full speed rotation, the influence of the rotational speed on the blade deformation almost remains the same, and the influence of the natural vibration on blade deformation is increased with an increase in the rotational speed.

提出了一种基于双目视觉的直升机旋翼桨叶共锥度检测方法。首先, 采用平面标定算法对双目视觉系统进行标定, 获取摄像机内外参数; 其次, 采集不同桨叶的立体图像对, 并用Bouguet算法对其进行校正, 获取重投影矩阵; 然后, 对立体图像对中的标记点进行检测与匹配, 获取标记点的视差; 最后, 根据双目视觉测量原理计算出桨尖距地面的高度, 实现桨叶共锥度检测。通过对旋翼塔进行多次测量实验, 结果表明该方法具有动态测量、非接触式、操作简单、危险性小和精度高的优点。