【摘要】 经过正交小波变换后,低尺度上测量信号的信噪比提高。应用小波变换将结构的激励信号和响应信号分解到不同尺度上,得到不同尺度上结构的状态方程和测量方程,结合动力学系统辨识的参数卡尔曼滤波方法,提出了结构物理参数的多尺度参数卡尔曼滤波辨识方法。理论分析和数值算例表明:在多尺度上对结构参数进行辨识比在单一尺度上辨识能获得更高的精度。更多还原

【Abstract】 An efficient multi-scale parameter Kalman filter method is proposed for identification of the physical parameters. The ratio of signal to noise is increased in low scale by orthogonal wavelet transform. The measurement data is decomposed by orthogonal wavelet function and the state and measurement equations can be resolved into different scales. The physical parameters of a dynamic system are estimated by parameter Kalman filter method in different scales. The theoretical analysis and numerical simulations indicate that the identification of system parameters in multi-scale is more efficient than in single scale.更多还原