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Detection of Abrupt Changes in Structural Properties Through Vibration Signal Processing

Morovvati, Vahid | 2016

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 48626 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Kazemi, Mohammad Taghi
  7. Abstract:
  8. Structural system identification from vibration data is one of the most interesting research topics in the structural health monitoring area. Recently, realization and detection of the effects of damage when a structure is subjected to strong ground motion has become a great concern in earthquake and structural engineering communities. Seismic signal processing is one of the most reliable methods of detecting the structural damage during earthquakes. The structural responses during earthquakes are nonstationary with respect to both amplitude and frequency. The state-of-the-art time-frequency distributions when applied to vibration records were studied. Different methods of analysis for time-frequency characteristics of the vibration signals is reviewed and the merits and disadvantages of each are explained. The methods considered here are: Fourier Transform, Short Term Fourier Transform, Wavelet Transform, Wigner-Ville Distribution, Cohen class distributions, and Hilbert-Huang Transform. Wavelet Transform and the Reduced Interference Distribution are found the most suitable methods to analyze the nonstationary characteristics of the structures. Recently, an innovative algorithm has been proposed for the output-only structural identification using blind source separation (BSS). BSS methods have shown considerable potential in the area of vibration system identification. The main objective of these methods is to extract the modal coordinates from the observed output signals, without any knowledge of input excitation.This study presents a simple hybrid procedure to identify the structural dynamic properties, damage instant and location. In this procedure, firstly, the wavelet transform technique is used to preprocess the response of structural vibration. Then the wavelet-domain signals used as inputs of second-order blind identification. The source with sharp spike is marked as ‘‘interesting’’ source. Spike time and recovered mixing matrix of interesting source reveal damage instant and location respectively. In the next step, the time-varying modes are identified by using SOBI for before and after the identified damage instant. Numerical simulations where damage is modeled by abrupt stiffness variation show the accuracy and robustness of the developed algorithm in single or multiple damage events.In this study, the use of the hybrid method of Blind Source Separation (BSS) and Time-Frequency Analysis (TFA) is explored to detect the changes in the structural response data. The combination of the BSS and TFA is applied to the seismic signals due to the non-stationary nature of them. Firstly, the second-order blind identification (SOBI) technique is used to decompose the response signal of structural vibration into modal coordinate signals which will be mono-components for TFA. Then each mono-component signal is analyzed to extract instantaneous frequency of structure. Numerical simulations and a real-world seismic-excited structure with time-varying frequencies show the accuracy and robustness of the developed algorithm. TFA of extracted sources shows that used method can be successfully applied to structural damage detection. The results also demonstrate that the combined method can be used to identify the time instant of structural damage occurrence more sharply and effectively than by the use of TFA alone
  9. Keywords:
  10. Signal Processing ; Damage Detection ; Signal Processing ; Blind Sources Separation (BSS) ; Structural Health Monitoring ; Structural Identification

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