This thesis covers the development of a model updating technique which relies on the introduction of correction factors to the elemental stiffness matrix of a beam Finite Element Model (FEM). A Genetic Algorithm selects the values of correction factors by minimizing the difference between an experimentally measured Frequency Response Function (FRF) and the FRF calculated from the FEM being updated. The model updating technique was employed as a damage detection algorithm. The first phase of damage detection is to use model updating to eliminate experimental and modeling errors between the FRF of a beam measured experimentally and the FRF of the same beam calculated by FEM. The second step of damage detection is to employ the model updating process to match the FRF of a damaged beam measured experimentally to the response of the updated FEM. A damage index based on the change in FEM correction factors during the second phase is applied to locate damage. Three different cost functions were evaluated and tuned against two different damage cases measured experimentally. Later the best cost function was tested against two damage cases with smaller damage magnitude. The damage detection algorithm showed reasonable accuracy in determining the damage location in all cases. Additionally, this thesis covers the adaptation of strain gauges for dynamic measurement and the associated signal processing and filtering.
Mechanical Engineering Department
MS in Mechanical Engineering
Date of Award
Online Submission Date
Committee Member 1
El Haggar, Salah
Committee Member 2
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(2010).Damage detection via structural model updating using frequency response functions and genetic algorithms [Master’s thesis, the American University in Cairo]. AUC Knowledge Fountain.
Elsaid, Bassam. Damage detection via structural model updating using frequency response functions and genetic algorithms. 2010. American University in Cairo, Master's thesis. AUC Knowledge Fountain.