Output-only modal estimation using sparse component analysis and density-based clustering algorithm

This paper proposes a blind source separation (BSS) based modal parameter identification method. A density-based clustering algorithm is introduced to estimate the mode shapes even when the number of measured responses is less than the number of active modes. Different from other BSS methods using traditional clustering algorithms, the proposed method doesn't require the number of active modes. Natural frequencies and damping ratios are extracted from the modal responses recovered by smoothed l0-norm algorithm. The method we proposed in this paper is validated by a five degree-of-freedom mass-spring-damper system. Free and random vibration responses of cantilever beams are analyzed by the proposed method. The comparison of the identified mode shapes and natural frequencies shows good performance of the proposed method in engineering application.