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The measured frequency response functions (FRFs) in the modal test are usually contaminated with noise that significantly affects the modal parameter identification. In this paper, a modal peak-based Hankel-SVD (MPHSVD) method is proposed to eliminate the noise contaminated in the measured FRFs in order to improve the accuracy of the identification...
Citations
... However, when correlated with residual noise, their peak frequencies occasionally deviate from those of the modal. A simulation based on a frequency trend research 36) revealed a contrasting relationship between the natural frequency trend and noise levels. It became evident from both metrics that lower natural frequency values are inversely proportional to the noise levels. ...
... Usually, the number of non-zero singular values from Singular Value Decomposition (SVD) is used to determine the model order [1]. In practice, the number of non-zero singular values increases due to noise interference, which makes it impossible to determine the model order accurately. ...
... The eigenvalue diagonal array obtained from the eigenvalue decomposition of the state matrix, the eigenvalue exponential entropy increment i E ' at order i can be expressed as 1 1 ...
The covariance-driven stochastic subspace modal parameter identification method has been widely used in the field of engineering structures. Effective determination of the model order of the structural system is the key to applying this method to identify the modal parameters. It is particularly difficult to determine the model order for unstable systems affected by noise disturbances and computational errors. In order to effectively determine the model order, an exponential eigenvalue entropy incremental covariance-driven stochastic subspace identification (EE-COV-SSI) algorithm is proposed. The condition number of the state matrix is used to determine the degree of perturbation of the response signal to the system stability. Meanwhile, the identification accuracy of the modal parameters is reflected by calculating the modal frequency coefficient of variation. Finally, the method is applied to the modal analysis of a four-story frame structure. The results show that the method can accurately identify the model order and improve the identification accuracy of the modal parameters.
... It is known that FRFs are highly prone to noise contamination [20]. While this may significantly affect the modal parameter identification, it can also compromise damage detection results obtained from utilizing FRFs in damage detection methods. ...
