Extraction of modal parameters for identification of time-varying systems using data-driven stochastic subspace identification-Reference-Cited by-同舟云学术

Extraction of modal parameters for identification of time-varying systems using data-driven stochastic subspace identification

Published:2017-10-16 Issue:20 Volume:24 Page:4781-4796
ISSN:1077-5463
Container-title:Journal of Vibration and Control
language:en
Short-container-title:Journal of Vibration and Control

Author:

Li Wenchao¹,Vu Viet-Hung¹,Liu Zhaoheng¹^ORCID,Thomas Marc¹,Hazel Bruce²

Affiliation:

1. Department of Mechanical Engineering, École de technologie supérieure Canada

2. Institut de recherche d’Hydro-Québec, Canada

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.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science

Link

http://journals.sagepub.com/doi/pdf/10.1177/1077546317734670

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