Covariance-driven stochastic subspace identification(SSI-cov)is a relatively mature operational modal analysis method in recent years.However,its identification accuracy and efficiency are highly sensitive to parameter settings.In this paper,the stability diagram and five evaluation indexes,including the apparent degree of the jump point of the singular entropy increment,the average identification error of the frequency,the total variation coefficient of the damping ratio,the average modal confidence factor of the vibration mode and the running time,are employed for the sensitivity analysis.With a classic 5-DOF layer model as the simulation example,the influence of the number of Toeplitz matrix rows,sampling frequency and data length on the recognition result of SSI-cov is studied.The suggestion of value range of parameters that can meet the demands of the precision as well as control running time of the program is given.Finally,the SSI-cov improved parameter setting is verified by the measured data of a scaled three-story frame model.The results show that the proposed parameter range is reasonable.
关键词
振动与波/随机子空间辨识/敏感性分析/参数优化/Toeplitz矩阵行块数/采样频率
Key words
vibration and wave/stochastic subspace identification/sensitivity analysis/parameter optimization/block rows of Toeplitz matrix/sampling frequency
维普
万方数据