Nonlinear time-varying vibration system identification using parametric time-frequency transform with spline kernel
Nonlinear time-varying vibration system identification using parametric time-frequency transform with spline kernel
复制标题
利用样条核参数时频变换辨识非线性时变振动系统
DOI：
10.1007/s11071-016-2786-1
复制
发表时间：
2016
影响因子：
5.6
通讯作者：
Meng G.
中科院分区：
文献类型：
--
作者：
Yang Y.;Peng Z. K.;Dong X. J.;Zhang W. M.;Meng G.
在实际应用中，机械振动系统不是线性时不变的。例如，在部署、老化、变形、负载变化等过程中会出现时变模式。在系统缺乏完整的基于物理的描述的情况下，系统识别（SI）能够获取未知系统的非平稳模式的丢失信息。当时变系统涉及非线性时，SI就会遇到困难，这使得系统解同时具有非线性和非平稳时频模式。本文旨在利用带样条核的参数时频变换来识别具有线性和非线性时变特性的系统，该变换以时频域能量集中且能够准确提取模型特征而闻名。该方法的有效性在由三种类型的非线性时变刚度组成的单自由度系统上得到了证明，包括时变周期刚度调制、时变非线性刚度分段调制和时变非线性刚度周期调制。与传统时频方法和基于希尔伯特变换的 SI 的比较验证了该方法在表征存在噪声的系统非线性时变刚度方面更加鲁棒。
In real-life applications, mechanical vibration systems are not linear time invariant. Time-varying pattern arise, for instance, during deployment, aging, deformation, load variation, etc. In the absence of a complete physics-based description of a system, system identification (SI) is able to obtain the missed information of nonstationary pattern for the unknown system. The SI will face difficulty when the time-varying system involves the nonlinearity, which makes the system solution have both the nonlinear and nonstationary time–frequency patterns. This paper aimed to identify the system with linear and nonlinear time-varying characteristics using parametric time–frequency transform with spline kernel, which is known for offering great energy concentration in time–frequency domain and allows the accurate extraction of model feature. The efficacy of the proposed method is demonstrated on SDOF systems comprised of three types of nonlinear time-varying stiffness, including time-varying periodic modulation of stiffness, time-varying piecewise modulation of nonlinear stiffness and time-varying periodic modulation of nonlinear stiffness. Comparisons with the conventional time–frequency methods and the Hilbert transform-based SI validated that the proposed method is more robust in characterizing the nonlinear time-varying stiffness of the system with the presence of noise.