基于DSC-LS的加速度计动态模型参数辨识

加速度计动态模型参数辨识对提高振动与冲击动态测试和动态分析精度等具有重要作用.针对加速度计动态模型参数频域辨识方法中栅栏效应对参数辨识精度的影响，提出了一种基于离散频谱校正-最小二乘（DSC-LS）的加速度计动态模型参数辨识方法，该方法利用H₁估计获得零频点坐标，并将FFT+FT离散频谱校正与LS方法相结合，高精度估计出谐振点坐标，然后通过特征点坐标计算加速度计动态模型参数.实验结果表明，该方法能够有效消除栅栏效应对加速度计动态模型参数辨识的影响，具有较高的加速度计动态模型参数辨识精度和抗低频窄带噪声干扰性能. 

Dynamic Model Parameter Identification of Accelerometer Using Discrete Spectrum Correction and Least Square

Dynamic model parameter identification of accelerometer plays an important role in improving the accuracy of dynamic testing and analysis for vibration and shock. To overcome the influence of the fence effect (FE) on the accuracy of the parameters obtained with dynamic model parameter identification method for accelerometer frequency domain, a dynamic model parameter identification method of accelerometer based on discrete spectrum correction and least square (DSC-LS) was presented. Firstly, the point coordinates at zero frequency of accelerometer were estimated by using H₁ estimator, and the resonant point coordinates were estimated with higher accuracy by combining FFT+FT discrete spectrum correction and LS. Then, according to the feature points coordinates, the dynamic model parameters of accelerometer were calculated. The experimental results show that, the presented method can eliminate the influence of FE efficiently on the accuracy of accelerometer''s dynamic model parameters identification and improve the anti-interference capacity for low frequency noise with narrow-band, and improve the identification accuracy of the dynamic model parameters of accelerometer.