Structural Identification and Damage Detection using Genetic Algorithms

Structural Identification and Damage Detection using Genetic Algorithms Michael John Perry, Chan Ghee Koh
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 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. Categories:
Computers – Algorithms and Data Structures
Year:
2010
Publisher:
CRC Press
Language:
english
Pages:
150
ISBN 10:
041587629X
ISBN 13:
9780415876292
Series:
Structures and Infrastructures Series, Volume 6
File:
47 MB