在力学显微镜和光力学的研究中,微悬臂是一种被广泛使用的微机械器件.为了了解微悬臂的模态信息,采用ARMA模型对微悬臂进行系统辨识和模态参数识别.针对观测噪声会使时间序列模型辨识精度变低的问题,研究如何将带有观测噪声的ARMA模型转化为无观测噪声的ARMA模型.得到微悬臂的ARMA模型后将其转化为连续系统的传递函数,再从传递函数中求出微悬臂的各模态参数.为了减小微悬臂对外力的延迟响应时间,根据系统辨识得到的模型,构造一个复原滤波器,微悬臂的位移信号通过这个复原滤波器后得到作用力信号.仿真及实验结果证明了所用的系统辨识、模态参数识别及信号复原方法的有效性.%Micro-cantilever is a kind of micromechanical device which is widely used in the research of force microscope and optomechanics. In order to learn the modal information of micro-cantilevers, the ARMA model is employed for system identification and modal parameters identification of the micro-cantilevers. Since observing noise may decrease the identification accuracy of the time series model, the method of converting the ARMA model with observed noise to the ARMA model without observed noise is studied. After micro-cantilever's ARMA model is obtained, this model is converted to a transfer function of the continual system. Then, the micro-cantilever's modal parameters are calculated from the transfer function. In order to decrease the time delay of the micro-cantilever response to external force, a recovery filter is constructed on the basis of the model obtained by system identification. The applied force signal can be obtained by inputting displacement signal into the recovery filter. Simulation result and experimental result verify the effectiveness of the system identification, the modal parameter identification and the signal recovery method presented in this paper.
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