An Experimental Assessment of Transverse Adaptive Fir Filters as Applied to Vibrating Structures Identification

The present work is aimed at assessing the performance of adaptive Finite Impulse Response ( FIR ) filters on the identification of vibrating structures. Four adaptive algorithms were used: Least Mean Squares ( LMS ), Normalized Least Mean Squares ( NLMS ), Transform‐Domain Least Mean Squares ( TD –...

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Bibliographic Details
Published inShock and vibration Vol. 12; no. 3; pp. 197 - 216
Main Authors Castello, Daniel A., Rochinha, Fernando A.
Format Journal Article
LanguageEnglish
Published Wiley 01.01.2005
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ISSN1070-9622
1875-9203
1875-9203
DOI10.1155/2005/917832

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Summary:The present work is aimed at assessing the performance of adaptive Finite Impulse Response ( FIR ) filters on the identification of vibrating structures. Four adaptive algorithms were used: Least Mean Squares ( LMS ), Normalized Least Mean Squares ( NLMS ), Transform‐Domain Least Mean Squares ( TD – LMS ) and Set‐Membership Binormalized Data‐Reusing LMS Algorithm ( SM – BNDRLMS ). The capability of these filters to perform the identification of vibrating structures is shown on real experiments. The first experiment consists of an aluminum cantilever beam containing piezoelectric sensors and actuators and the second one is a steel pinned‐pinned beam instrumented with accelerometers and an electromechanical shaker.
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ISSN:1070-9622
1875-9203
1875-9203
DOI:10.1155/2005/917832