This article describes the underlying theory and hardware implementation of a newly developed algorithm for online modal parameter identification. An online modal parameter estimation algorithm using subspace methods is applied to both model and experimental data for a 4-m laboratory truss structure
REAL-TIME MODAL PARAMETER ESTIMATION USING SUBSPACE METHODS: THEORY
β Scribed by F. Tasker; A. Bosse; S. Fisher
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 207 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0888-3270
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β¦ Synopsis
This article describes the underlying theory of a newly developed algorithm for online modal parameter identification. These online subspace estimation methods use eigenanalysis for data filtering, and are derived from a recent multi-input, multi-output batch algorithm. One method is obtained by deriving a new efficient data update expression combined with a recently developed modified singular value decomposition known as the URV method. The second method combines an existing data update expression with the URV method. The URV method enables recursive update of the signal subspace. The close relationship of a modified form of the batch estimation approach to the Eigensystem Realization Algorithm (ERA) is also shown through the introduction of an extended ERA method.
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