环境激励下基于chirplet变换的线性时变系统参数识别

提出了针对时变系统响应的短时频率线性时变假设,通过将时变响应拟合成多分量线调频信号,根据线调频信号互相关理论推导了随机白噪声激励下时变系统的物理参数识别方法。该识别方法只需基于结构的加速度响应,便能识别结构的时变质量和刚度。由于引入了调频斜率刻画响应信号的短时频率线变特征,该方法相比传统识别方法能更好地追踪快变甚至突变参数,对实际工程中的时变问题具有重要的应用价值。仿真算例中构造了1个3自由度时变结构模型,针对线性时变、周期时变和突变等情况进行了物理参数的识别,误差分析显示识别误差均在5%以内,仿真结果验证了方法的正确性和适用性。

Parameter identification of linear time-varying systems based on chirplet transform under environmental excitation

The assumption that frequencies of responses of linear time-varying systems vary linearly in a short-time was proposed. By fitting the time-varying responses to multi-component line frequency modulation signals, a physical parameter identification method of time-varying systems under random white noise excitation was obtained according to the cross-correlation theory of line frequency modulation signals. The mass and stiffness coefficients of time-varying structures were identified only using the acceleration response. Due to the introduction of frequency modulation factor to describe the variation of frequencies of response signals in a short-time, this method could track fast changes or even abrupt changes of parameters better than traditional identification method, so it had important application value for time-varying structures in practical engineering. In the simulation example, a 3-degress of freedom time-varying structure model was constructed to identify linear, periodic and abrupt changes of physical parameters. The error analysis showed that the identification errors were all within 5%. The results verified the correctness and applicability of the method.