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Autor(en): 
  • Michael J. Perry
  • Koh Chan Ghee
  • Structural Identification and Damage Detection using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juni 2017  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Civil engineering, surveying & building / Civil engineering, surveying and building / experimental modal analysis / Finite element modelling / inverse problem solving / mechanical system diagnostics / output-only damage identification / parameter estimation techniques
    ISBN:  9781138111929 
    EAN-Code: 
    9781138111929 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Structures and Infrastructures  
    Dimensionen:  H 246 mm / B 174 mm / D  
    Gewicht:  300 gr 
    Seiten:  140 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Rapid advances in computational methods and computer capabilities have led to a new generation of structural identification strategies. Robust and efficient methods have successfully been developed on the basis of genetic algorithms (GA). This volume presents the development of a novel GA-based identification strategy that contains several advantageous features compared to previous methods. Focusing on structural identification problems with limited and noise contaminated measurements; it provides insight into the effects of various identification parameters on the identification accuracy for systems with known mass. It then proposes a generalization for systems with unknown mass, stiffness and damping properties. The GA identification strategy is subsequently extended for structural damage detection. The findings of the output-only strategy and substructural identification represent a great leap forward from the practical point of view. This book is intended for researchers, engineers and graduate students in structural and mechanical engineering, particularly for those interested in model calibration, parameter estimation and damage detection of structural and mechanical systems using the state-of-the-art GA methodology.

      



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