Structural Identification and Damage Detection Using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6 » książka
Structural Identification and Damage Detection Using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6
ISBN-13: 9780415461023 / Angielski / Twarda / 2009 / 140 str.
Structural Identification and Damage Detection Using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6
ISBN-13: 9780415461023 / Angielski / Twarda / 2009 / 140 str.
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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.
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). To this end, this book presents readers with the background and recent developments required to conduct research and apply GA-based methods for parameter identification, model updating and damage detection of structural dynamic systems. This is believed to be the first book on this topic. Of significance, a novel identification strategy is developed which contains several advantageous features compared to many previous methods. The application of the strategy focuses on structural identification problems with limited and noise contaminated measurements. Identification of systems with known mass is first presented to provide physical insight into the effects of various identification parameters on the identification accuracy. Generalisation is then made to systems with unknown mass, stiffness and damping properties – a challenging problem rarely considered due to the difficulty encountered in many identification methods with regards to separating effects of mass and stiffness properties. The GA identification strategy is extended for structural damage detection whereby the undamaged state of the structure is first identified and used to direct the search for parameters of the damaged structure. The power of the strategy is illustrated by numerical simulation as well as model tests of a steel frame structure. Furthermore, another rarely studied problem of structural identification where measurement of forces is not available is addressed. The findings represent a great leap forward from the practical point of view. Finally, parameter estimation of non-linear structural systems is presented to illustrate the power and versatility of the GA-based identification strategy.
This book will be useful for researchers, engineers and graduate students in structural/mechanical engineering – particularly with interests in model calibration, parameter estimation and damage detection of structural and mechanical systems using the state-of-the-arts GA methodology.
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