Abstract
The paper deals with application of AI tools in experimental modal analysis. The example of Stabilization Diagram processing, that is an intermediate stage of m,odal parameter estimation procedure, was selected. In order to automate decision-making carried out during Stabilization Diagram processing a set of tools employing: fuzzy reasoning and artificial neural nets was applied. The application of these tools enabled to ease and shorten execution time of Stabilization Diagram processing. Additionally, the result of processing has become operator-independent.
References
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[2] KS. Chhipwadia, D.C. Zimmerman, G.H. James III. Evolving autonomous modal parameter estimation. Proc. of 17th IMAC, SEM USA, 819-825, 1999.
[3] I. Goethals, B. Vanluyten, B. De Moor. Reliable spurious mode rejection using self learning algorithms. Proc. of ISMA2004, KU. Leuven, 991-1003 , 2004
[4] W. Heylen, S. Lammens, P. Sas. Modal Analysis Theory and Testing. KU. Leuven, Departement Werktuigkunde, Leuven, 1997
[5] G.J. Klir, B. Yuan. Fuzzy Sets and Fuzzy Logic. Prentice Hall. 1995.
