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On Nonlinear Parameter Estimation with Random Noise Signals
Ansvarlig organisasjon
2007 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert) Published
Abstract [en]

In the field of nonlinear dynamics it is essential to have well tested and reliable tools for estimating the nonlinear parameters from measurement data. This paper presents an identification technique based on using random noise signals, as initially developed by Julius S. Bendat. With this method the nonlinearity is treated as a feedback forcing term acting on an underlying linear system. The parameter estimation is then performed in the frequency domain by using conventional MISO/MIMO techniques. To apply this method successfully it is necessary to have some pre-information about the model structure and thus methods for nonlinear characterization and localization are studied. The paper also demonstrates the various ways the method can be formulated for multiple-degree-of-freedoms. The implementation of the method is illustrated with simulated data as well as a practical application, where the method is used to create a dynamic model of a test-rig with a significant nonlinearity.

sted, utgiver, år, opplag, sider
Orlando, Florida: Society for Experimental Mechanics , 2007.
Emneord [en]
nonlinear, characterization, localization, parameter estimation, reverse-path, geometric nonlinearity
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-9042Lokal ID: oai:bth.se:forskinfo38E598522AC23766C1257336004CD245ISBN: 0-912053-96-8 (tryckt)OAI: oai:DiVA.org:bth-9042DiVA, id: diva2:836818
Konferanse
IMAC XXV
Tilgjengelig fra: 2012-09-18 Laget: 2007-08-13 Sist oppdatert: 2015-06-30bibliografisk kontrollert

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