应用时变参数建模方法辨识时变模态参数

 应用非平稳时间序列的时变自回归建模方法进行了参数随时间变化的线性系统模态参数的辨识。对线性时变系统在白噪声激励下振动响应的非平稳时间序列进行建模。通过引入基函数将非平稳过程的辨识问题转化为线性时不变过程的辨识。结合信号时频变换确定模型阶次, 通过时变的伯格尔( Bur g) 算法对时变的自回归(AR) 模型系数和时变结构模态频率进行了估算。通过对刚度随时间变化的三自由度系统模态频率的仿真辨识, 验证了辨识方法的有效性。

Identification of Time-Variant Modal Parameters by a Time-Varying Parametric Approach

A time-varying autoregressive model with time-varying coefficients is introduced in this paper to extract modal parameters from non-stationary vibration signals. With this model, the relationship between time-varying modal parameters and time-varying autoregressive model coefficients is established. The time-varying autoregressive modeling is employed in order to obtain the high resolution of the time-frequency distribution of non-stationary responses. A new algorithm is presented by combining the use of base functions with the time-frequency transform of signals, in which the base functions have shift the time-varying modeling to a linear time-invariant identification problem. A simulated linear time-varying system of three degrees of freedom with time-varying stiffness is presented to validate the proposed time-varying autoregressive method.