摘要
为提高时变结构模态参数辨识精度和抗噪声能力,提出一种前后向泛函向量时变自回归滑动平均(FSVTARMA)时间序列模型联合估计的模态参数辨识方法。首先建立前后向FS-VTARMA模型联合估计的均方误差形式的费用函数,其次引入非平稳信号中前向模型和后向模型估计系数的近似共轭关系,再利用两步最小二乘法(2SLS)得到时变模型系数,最后把时变模型特征方程转换为广义特征值问题提取出模态参数。利用时变刚度系统非平稳振动信号验证该方法,结果表明:能有效地克服前向模型估计中模态参数一步延迟以及起始时刻无法准确获得,以及后向模型估计中模态参数一步超前以及终止时刻无法准确获得的缺点,具有更高的模态参数辨识精度和更强的抗噪声能力。
To improve modal parameter identification precision and anti-noise performance for time-varying structures an identification approach using a forward-backward functional series vector time-dependent ARMA time series model （FS-VTARMA）based on joint estimation was presented.Firstly,a cost function in the form of mean square error for joint forward-backward estimation of FS-VTARMA model was established.Secondly,the estimated parameters of forward and backward models for a non-stationary signal were approximately complex conjugate.Then,the time-varying model coefficients were obtained using the two-stage least square （2SLS）method.Finally,its modal parameters were extracted from a generalized eigenvalue problem transformed from an eigenvalue equation of the time-varying model.The identification approach was validated with non-stationary vibration signals of a system with time-varying stiffness.The results indicated that the proposed method can not only overcome shortages of one-step delay and initial prediction error in the forward model＇s modal parameter estimation,but also overcome shortages of one-step step lead and terminal prediction error in the backward model＇s modal parameter estimation,it has higher modal parameter identification precision and better anti-noise performance.
出处
《振动与冲击》
EI
CSCD
北大核心
2015年第3期129-135,共7页
Journal of Vibration and Shock
基金
北京理工大学基础研究基金(20120142009)
关键词
时变结构
模态参数辨识
前后向时间序列
向量
泛函
time-varying structures
modal parameter identification
forward-backward time series
vector
functional series
