Application of Hilbert-Huang transform and stochastic subspace identification for modal parameter identification of civil engineering structures

Identification of structural parameters from operational vibration measurements is one of the most attractive research topics in the structural health monitoring area. Hilbert-Huang transform: (HHT) was developed recently in order to adaptively analyze non-stationary and nonlinear signals. And as a promising output-only time domain method, stochastic subspace identification (SSI) is especially suitable for operational modal parameter identification. Therefore two approaches are proposed to identify the modal parameters separately in this paper. The first approach is based on the HHT and the random decrement technique (RDT). The second one is based on the empirical mode decomposition (EMD,) and SSI. As case studies, the original signals from the field ambient vibration test of an arch bridge and the shaking table test of a RC frame model are processed and modal parameters are identified using the above two approaches, respectively. Identification results indicate that the proposed approaches are feasible and these kinds of combination can exert each one's advantages and make up the deficiencies.