Recursive modal parameter estimation using output-only subspace identification for structural health monitoring

Precise identification of structural properties is a vital step towards detection and localization of damage in structures. In this paper the problems of improving accuracy of modal parameter estimates and automatic elimination of spurious modes in covariance driven output-only subspace identification method are addressed. An iterative procedure is proposed, which in the first step, actively modifies the excitation signal, resulting in improvements in identification results. In the second step, for spurious mode elimination, an alternative stabilization histogram is introduced to automatically combine and extract identified modal parameters. It is shown that use of measured output signals, of different sampling rates, along with combination of identified results on a single stabilization histogram, can enhance the effectiveness of spurious modes rejection. One numerical and two experimental examples, on the modal parameter estimation of a composite beam and an aluminum plate (CACTUS) are presented to demonstrate the efficacy of the iterative procedure. The proposed algorithm allows automatic and accurate generation of modal parameter residuals for structural health monitoring applications.