Extraction of modal parameters for identification of time-varying systems using data-driven stochastic subspace identification. (October 2018)

• Record Type: Journal Article
• Authors: Li, Wenchao; Vu, Viet-Hung; Liu, Zhaoheng; Thomas, Marc; Hazel, Bruce
• Is Part Of: Journal of vibration and control. Volume 24:Number 20(2018)
• Page Start: 4781
• Page End: 4796
• Publication Date: 2018-10
• Subjects: Identification -- modal analysis -- modal parameters -- stochastic subspace identification -- time-varying system; Vibration -- Periodicals; Damping (Mechanics) -- Periodicals; 620.3
• DOI: 10.1177/1077546317734670
• Languages: English
• ISSNs: 1077-5463

Abstract

This paper presents a method for the extraction of modal parameters for identification of time-varying systems using Data-Driven Stochastic Subspace Identification (SSI-DATA). In practical applications of SSI-DATA, both the modal parameters and computational ones are mixed together in the identified results. In order to differentiate the structural ones from computational ones, a new method based on the eigen-decomposition of the state matrix constructed in SSI-DATA is proposed. The efficiency of the proposed method is demonstrated through numerical simulation of a lumped-mass system and experimental test of a moving robot for extracting excited natural frequencies of the system.