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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 41992 (09)
- University: Sharif University of Technology
- Department: Civil Engineering
- Advisor(s): Golafshani, Ali Akbar
- Abstract:
- Extracting modal parameters is necessary for future vibration-based health monitoring studies of the structures. Due to the reason that it is difficult to measure the input excitation forces acting on a real large structure in its operational condition, it is preferable to use the output-only methods which estimate the modal model by using responses data only. Also, the output-only dynamic testing has advantages of being inexpensive since no equipment is needed to excite the structure and the service condition does not have to be interrupted.This paper presents the results of modal identification of an offshore jacket platform using output-only methods with the assumption of ambient vibration excitation. The sensors are assumed to be located in 3 cases and the accelerations are measured in the horizontal direction. The data has been considered in 3 forms include without noise, with 5 percent noise and with 10 percent noise. Two output-only system identification techniques are applied to an offshore jacket platform and the comparison between these methods is performed. The techniques examined include the frequency domain-based peak picking method and the time domain-based data-driven stochastic subspace identification method.The peak picking method is the simplest known method for identifying the modal parameters. The natural frequencies are simply determined from the observation of the peaks on the graphs of the averaged normalized power spectral densities (ANPSDs). The data-driven stochastic subspace identification technique is more advanced and determines the system model in state-space. One advantage of this method is that it does not require any pre-processing of the measurements. In addition, robust numerical techniques such as QR factorization and singular value decomposition are involved in this method. The results of applying these methods to the offshore jacket platform show that the frequencies can be obtained with both methods and a good agreement of identified frequencies has been found between two methods but in some cases the data-driven stochastic subspace identification method shows more efficiency in obtaining the frequencies that may possibly be missed by the peak picking method
- Keywords:
- System Identification ; Offshore Platforms ; Structural Health Monitoring ; Peak Picking ; Stochastic Subspace Identification
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