CAJ | 학술논문

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（FS-VTARMA）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。
위제고시변결구모태삼수변식정도화항조성능력，제출일충전후향범함향량시변자회귀활동평균（FS-VTARMA）시간서렬모형연합고계적모태삼수변식방법。수선건립전후향FS-VTARMA모형연합고계적균방오차형식적비용함수，기차인입비평은신호중전향모형화후향모형고계계수적근사공액관계，재이용량보최소이승법（2SLS）득도시변모형계수，최후파시변모형특정방정전환위엄의특정치문제제취출모태삼수。이용시변강도계통비평은진동신호험증해방법，결과표명：능유효지극복전향모형고계중모태삼수일보연지이급기시시각무법준학획득，이급후향모형고계중모태삼수일보초전이급종지시각무법준학획득적결점，구유경고적모태삼수변식정도화경강적항조성능력。
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.