Accelerometer dynamic model parametric identification using WLS-SVM
WANG Jianlin1， GUO Yongqi1， WEI Qingxuan1， SUN Qiao2， HU Hongbo2
1.College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
2.National Institute of Metrology, Beijing 100029, China
It is important to improve parametric recognition accuracy of accelerometer dynamic model for studying and improving accelerometer dynamic characteristics.Aiming at the problem of nonlinearity of accelerometer affecting its dynamic model parametric identification accuracy, an accelerometer dynamic model parametric identification method using the weighted least squares (WLS) and the support vector machine (SVM) was proposed.Aiming at the second order nonlinear dynamic model of accelerometer containing a linear part and nonlinear terms, parameters of the linear part of the model were identified using WLS, and the nonlinear characteristics of the model were estimated using SVM.Then the constructed error criterion function was iterated and minimized to realize the optimal identification for accelerometer dynamic model parameters.The simulation tests and the accelerometer calibration tests under shock excitation based on the absolute method showed that the proposed method can be used to reduce influences of nonlinearity of accelerometer on its dynamic model parametric identification accuracy; the identified results for accelerometer dynamic model parameters have a higher accuracy.
王建林1，郭永奇1，魏青轩1，孙桥2，胡红波2. 基于WLS-SVM的加速度计动态模型参数辩识[J]. 振动与冲击, 2018, 37(19): 239-244.
WANG Jianlin1， GUO Yongqi1， WEI Qingxuan1， SUN Qiao2， HU Hongbo2. Accelerometer dynamic model parametric identification using WLS-SVM. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(19): 239-244.
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