Accelerometer dynamic model parametric identification using WLS-SVM

WANG Jianlin1, GUO Yongqi1, WEI Qingxuan1, SUN Qiao2, HU Hongbo2

Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (19) : 239-244.

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PDF(1009 KB)
Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (19) : 239-244.

Accelerometer dynamic model parametric identification using WLS-SVM

  • WANG Jianlin1, GUO Yongqi1, WEI Qingxuan1, SUN Qiao2, HU Hongbo2
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Abstract

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.

Key words

accelerometer / nonlinear dynamic model / support vector machine / weighted least squares / parameter identification

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WANG Jianlin1, GUO Yongqi1, WEI Qingxuan1, SUN Qiao2, HU Hongbo2. Accelerometer dynamic model parametric identification using WLS-SVM[J]. Journal of Vibration and Shock, 2018, 37(19): 239-244

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