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Structural Damage Detection by Using Signal-Based and Artificial Intelligence Methods; Case Study 'Moment-Resisting Frame Structure

Vazirizade, Mohsen | 2015

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 47412 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Bakhshi, Amin; Bahar, Omid
  7. Abstract:
  8. Civil structures are on the verge of changing which leads energy dissipation capacity to decline. Structural Health Monitoring (SHM) as a process in order to implement a damage detection strategy and assess the condition of structure plays a key role in structural reliability. Earthquake is a recognized factor in variation of structures condition, inasmuch as inelastic behavior of a building subjected to design level earthquakes is plausible. In this study Hilbert Hunag Transformation (HHT) is superseded by Ensemble Empirical Mode decomposition (EEMD) and Hilbert Transform (HT) together. Albeit this method is closely resemble HHT, EEMD brings more appropriate Intrinsic Mode Functions (IMFs). IMFs are employed to assess 1st mode frequency and mode shape. Afterward, Artificial Neural Networks (ANN) is applied to predict story acceleration based on acceleration of structure during pervious moments. ANN functions precisely. Therefore, any congruency between predicted and measured acceleration provides onset of damage. Then another ANN method is applied to estimate stiffness matrix. Though 1st mode shape and frequency is calculated in advance, It essentially requires an inverse problem to be solved in order to find stiffness matrix. This task is done by ANN. In other words, these two ANN method are exercised to forecast location and measure severity of damage respectively. This algorithm is implemented on two nonlinear moment-resisting steel frame and the results are acceptable
  9. Keywords:
  10. Damage Detection ; Structural Health Monitoring ; Artificial Neural Network ; Hilbert Transform ; Time-frequency Domain ; Nonlinear Moment-Resisting Steel Frame ; Ensembled Emprical Mode Decomposition (EEMD)

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