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 der
REAL-TIME MODAL PARAMETER ESTIMATION USING SUBSPACE METHODS: APPLICATIONS
β Scribed by A. Bosse; F. Tasker; S. Fisher
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 365 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0888-3270
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β¦ Synopsis
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. Experimental evaluation of this algorithm demonstrates that the technique accomplishes the objective of tracking multiple modes of a complex dynamical system using multiple sensors. The time-varying behaviour is captured in real time via a graphical display of the frequencies and damping ratios of the system. It is shown that the recursive algorithm provides results similar to the batch algorithm for a time-invariant system. In addition, it is shown that the batch algorithm used to derive the recursive algorithm performs similarly to a newly derived batch algorithm that is closely related to the Eigensystem Realization Algorithm. Details concerning the digital signal processor implementation and off-line monitoring are also presented.
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