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Damage Detection and Localization in Structures using Sensitivity of Power Spectral Density Obtained from Dynamic Data and Inverse Vibrations

Soltanzadeh, Farzaneh | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56620 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Bakhshi, Ali
  7. Abstract:
  8. In this dissertation, the location and severity of the damage are obtained using a new robust Power Spectral Density (PSD) sensitivity-based model updating method. PSD of structural response is highly sensitive metric to parameter change and provides vast information about the structure. The proposed damage detection method uses the sensitivities of measured responses in frequency domain, for FE model updating in an efficient way, by developing a quasi-linear sensitivity equation of structural response. The system of equations are solved using Least Square method. Only stiffness parameters were updated through model updating and change in mass parameters were neglected. In this study, proper selection of updating frequency points and the best selection of excitation points and measurement locations are investigated. The proposed method is also extended to strain PSD sensitivities. The performance of the proposed method has also been compared with two other damage detection methods based on the frequency response function and the spectral density sensitivities. The efficiency of the proposed method is verified through some numerical examples that considers the adverse effects of noise-contaminated and incompleteness of measured data. Due to the importance of experimental evaluation of a model updating method, a scaled three-story one-bay aluminum frame has been utilized. To this end, two damage cases were applied stepwise to the beams of structural frame. After signal processing of measured data, the finite element model of the frame was first calibrated with intact state data and then the damage detection was performed for different damage states. Results exhibit robustness of the method against measurement errors
  9. Keywords:
  10. Sensitivity Equations ; Damage Detection ; Experimental Evaluation ; Power Spectral Density (PSD)Analysis ; Least Squares Method ; Finite Element Model Updating ; Dynamic Data ; Inverse Vibration Problem

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