Abstract

Output-only modal identification has been attracting increasing research efforts in civil engineering community. The aim of this study was to develop a robust output-only modal identification methodology to improve the performance of the existing methods. The proposed method combines the second-order blind identification (SOBI) with the covariance driven stochastic subspace identification (SSI-COV) by introducing a new system model. Instead of employing single degree-of-freedom fitting methods to obtain local modal information of each mode like it usually does in SOBI, modal responses identified by SOBI are regarded as the output of a system to form the block Toeplitz matrix of the SSI-COV. More accurate global modal parameters are expected to be obtained since a parametric system model is included and the contributions of different modes are considered. It is also easy to select physical modes based on the time and frequency characteristics of source signals and thus can avoid the ambiguous work related to the stabilization diagrams. The proposed method is validated by a simulated 8-DOF system with emphasize on identification accuracy and parameter sensitivity. The results confirm the insensitivity of input parameters and demonstrate the high accuracy. It is then applied to estimate the modal parameters of a reinforced concrete shear core building and a concrete arch-gravity dam. It is demonstrated that a total of twelve building modes and six dam modes are successfully identified respectively, and the results in both applications are accord well with the existing modal identification methods, especially SSI-COV. The promising results show that the physical modes can be well separated, and the associated modal parameters can be reliably identified with high accuracy, even if closely-spaced modes and spurious harmonics occur. As expected, the modes discrimination step that associated with the proposed method tends to be more distinct and intuitive than the stabilization diagrams.

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