Modal parameter identification of time-varying structures using a forward-backward time series model based on joint estimation
YANG Wu, LIU Li, ZHOU Si-da, MA Zhi-sai
Key Laboratory of Dynamics and Control of Flight Vechile, Ministry of Education, School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
Abstract：To improve modal parameter identification precision and anti-noise performance, this paper presents an identification approach using a forward-backward functional series vector time-dependent ARMA time series model (FS-VTARMA) based on joint estimation. Firstly, a cost function in the form of mean square error for joint forward-backward estimation of FS-VTARMA model is established. Secondly, the estimated parameters are approximately complex conjugate between forward and backward model for non-stationary signal. Once more, the time-varying model coefficients are obtained using two stages least square (2SLS) method. Finally, modal parameters are extracted from a generalized eigenvalue problem, which is transformed from an eigenvalue equation of the time-varying model. The identification approach is validated by non-stationary vibration signals of a system with time-varying stiffness. The results indicate that the proposed method not only can overcome the shortages of one-step delay and initial prediction error in forward model estimated parameter, but also one-step lead and terminal prediction error in backward model estimated parameters, and has higher modal parameter identification precision and better anti-noise performance.
杨 武;刘 莉;周思达;马志赛. 前后向时间序列模型联合估计的时变结构模态参数辨识[J]. , 2015, 34(3): 129-135.
YANG Wu;LIU Li;ZHOU Si-da;MA Zhi-sai. Modal parameter identification of time-varying structures using a forward-backward time series model based on joint estimation. , 2015, 34(3): 129-135.
2015, Vol. 34 
