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System identification of dynamic structures

โœ Scribed by William T. Hollowell; Walter D. Pilkey; Edwin M. Sieveka

Publisher
Elsevier Science
Year
1988
Tongue
English
Weight
717 KB
Volume
4
Category
Article
ISSN
0168-874X

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๐Ÿ“œ SIMILAR VOLUMES

AN INPUT/OUTPUT-BASED PROCEDURE FOR FULL
AN INPUT/OUTPUT-BASED PROCEDURE FOR FULLY EVALUATING AND MONITORING DYNAMIC PROPERTIES OF STRUCTURAL SYSTEMS VIA A SUBSPACE IDENTIFICATION METHOD
โœ H. XIAO; O.T. BRUHNS; H. WALLER; A. MEYERS ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 363 KB

Dynamic behaviour of complex structural systems may be modelled by a system of second order linear ordinary di!erential equations, i.e., Mw K (t)#Dw (t)#Sw(t)"f (t), by means of either structural analysis for "nite degree-of-freedom systems or discretization procedures (e.g., FE methods) for continu

NEURAL IDENTIFICATION OF NON-LINEAR DYNA
NEURAL IDENTIFICATION OF NON-LINEAR DYNAMIC STRUCTURES
โœ R. LE RICHE; D. GUALANDRIS; J.J. THOMAS; F. HEMEZ ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 401 KB

Neural networks are applied to the identi"cation of non-linear structural dynamic systems. Two complementary problems inspired from customer surveys are successively considered. Each of them calls for a di!erent neural approach. First, the mass of the system is identi"ed based on acceleration record