Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/16495
Title: GA-based substructural identification with static measurements
Authors: MAK SWEE CHIANG
Keywords: genetic algorithm substructural identification static interface
Issue Date: 15-Jun-2004
Source: MAK SWEE CHIANG (2004-06-15). GA-based substructural identification with static measurements. ScholarBank@NUS Repository.
Abstract: Today, there are many methods of system identification designed for structural systems. However, most of them need large amount of computational time when handling large systems. To reduce computational time, static measurements are used instead of dynamic measurements. Here, GA works as an optimization tool to identify the unknown stiffness and displacement parameters. The fitness function formulated uses a combination of displacement errors and static equation errors. In addition, substructuring is introduced to reduce the number of unknown parameters at each stage to help convergence. Lastly, another algorithm is that avoids the need for interface measurements, as in the above technique, is introduced. Numerical examples of structural systems of up to 50 degrees of freedom are presented. Also, the method is demonstrated using an eight-storey structural model to show its effectiveness to assess damage.
URI: http://scholarbank.nus.edu.sg/handle/10635/16495
Appears in Collections:Master's Theses (Open)

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Acknowledgement.pdf16.86 kBAdobe PDF

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Table of Contents.1.pdf24.35 kBAdobe PDF

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List of References.pdf35.73 kBAdobe PDF

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