Generalized Eigenvalue Decomposition in Time Domain Modal Parameter Identification

2007 ◽  
Vol 130 (1) ◽  
Author(s):  
Wenliang Zhou ◽  
David Chelidze

This paper is intended to point out the relationship among current time domain modal analysis methods by employing generalized eigenvalue decomposition. Ibrahim time domain (ITD), least-squares complex exponential (LSCE) and eigensystem realization algorithm (ERA) methods are reviewed and chosen to do the comparison. Reformulation to their original forms shows these three methods can all be attributed to a generalized eigenvalue problem with different matrix pairs. With this general format, we can see that single-input multioutput (SIMO) methods can easily be extended to multi-input multioutput (MIMO) cases by taking advantage of a generalized Hankel matrix or a generalized Toeplitz matrix.

Author(s):  
Wenliang Zhou ◽  
David Chelidze

This paper is intended to point out the relationship among current time domain modal analysis methods by employing the generalized eigenvalue decomposition. Various well-known time domain modal analysis algorithms are reviewed. Ibrahim Time Domain (ITD), Least Square Complex Exponent (LSCE) and Eigensystem Realization Algorithm (ERA) methods are chosen to do the comparison. Reformulation to these original forms show these three methods can all be attributed to a generalized eigenvalue problem with different matrix pairs. With this general format, we can see that Single-Input Multi-Output (SIMO) methods can easily be extended to Multi-Input Multi-Output (MIMO) case by taking advantage of the generalized Hankel matrix or generalized Toeplitz matrix.


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