Abstract
It is usually of great importance to identify modal parameters for dynamic analysis and vibration control of civil structures. Unlike the cases in many other fields such as mechanical engineering where the input excitation of a dynamic system may be well quantified, those in civil engineering are commonly characterized by unknown external forces. During the last two decades, stochastic subspace identification (SSI) method has been developed as an advanced modal identification technique which is driven by output-only records. This method combines the theory of system identification, linear algebra (e.g., singular value decomposition) and statistics. Through matrix calculation, the so-called system matrix can be identified, from which the modal parameters can be determined. The SSI method can identify not only the natural frequencies but also the modal shapes and damping ratios associated with multiple modes of the system simultaneously, making it of particular efficiency. In this study, main steps involved in the modal identification process via the covariance-driven SSI method are introduced first. A case study is then presented to demonstrate the accuracy and efficiency of this method, through comparing the corresponding results with those via an alternative method. The effects of noise contaminated in output signals on identification results are stressed. Special attention is also paid to how to determine the mode order accurately.
Highlights
Modal analysis aims to identify the modal parameters of a dynamic system that include natural frequency, damping ratio and modal shape
During the last two decades, stochastic subspace identification (SSI) method has been developed as an advanced modal identification technique which is driven by output-only records
The SSI method can identify the natural frequencies and the modal shapes and damping ratios associated with multiple modes of the system simultaneously, making it of particular efficiency
Summary
Modal analysis aims to identify the modal parameters of a dynamic system that include natural frequency, damping ratio and modal shape. The modal identification problems cannot be solved via the traditional transform-function-based methods which rely on both the input and output information It would be considerably costly and/or difficult for high-rise buildings and large-span bridges to be excited by artificial devices with a controllable pattern. The SSI method identifies modal parameters from the so-called state space matrix based on either input-and-output records or output-only records It involves a number of robust numerical techniques, such as QR decomposition, SVD and least-square fitting, which are of great importance for reducing computational amount and for suppressing noise. It overcomes some typical shortcomings associated with a frequency domain method, such as inadequacy for identification of closely-spaced modes and insufficient resolution in the frequency domain This method is able to identify modal frequencies, mode shapes and damping ratios of multiple modes of the system simultaneously, which makes it of pretty efficiency. Special attention is paid to how to determine the mode order accurately
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