基于非线性自回归时序模型的振动系统辨识

发布时间：2018-05-28 00:15

本文选题：非线性自回归时序模型 + 振动系统　；参考：《计算机应用研究》2016年10期

【摘要】：针对线性和弱非线性振动系统进行了研究,提出采用非线性自回归时序(GNAR)模型进行系统频率辨识和判断系统性或非线性基本特征的方法。首先根据摄动法求解非线性微分方程的理论,论证GNAR模型与线性和弱非线性系统之间的本质联系,推导出GNAR模型系数与线性和非线性系统频率之间的解析关系;然后给出由GNAR模型系数和结构判断系统是否存在非线性及辨识系统频率和非线性项基本特征的方法;最后,以单自由度线性振动系统和无阻尼Duffing振动系统为算例验证该辨识方法的有效性和准确性。实验结果表明,基于GNAR模型的振动系统基本特征辨识方法具有较好的识别精度,能用于估计系统的动力学特性。
[Abstract]:In this paper, the linear and weakly nonlinear vibration systems are studied, and a method is proposed to identify the frequency of the system and to judge the basic characteristics of system or nonlinearity by using the nonlinear autoregressive time series (GNAR) model. Based on the theory of perturbation method for solving nonlinear differential equations, the essential relation between GNAR model and linear and weakly nonlinear systems is demonstrated, and the analytical relationship between the coefficients of GNAR model and the frequency of linear and nonlinear systems is derived. Then, the method of judging whether the system has nonlinearity and identifying the basic characteristics of system frequency and nonlinear terms by the coefficients of GNAR model and structure is given. The validity and accuracy of the identification method are verified by the examples of linear vibration system with single degree of freedom and undamped Duffing vibration system. The experimental results show that the method based on GNAR model has good recognition accuracy and can be used to estimate the dynamic characteristics of the system.
【作者单位】：南京工程学院汽车与轨道交通学院;
【基金】：国家自然科学基金资助项目(51305194) 江苏省自然科学基金资助项目(BK20130743,BK20130746)
【分类号】：O322

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