عنوان مقاله [English]
Natural occurrences, such as earthquake and wind, cause damages to structures (e.g., buildings and bridges) through enforcing extreme loads. Consequently, they might result in catastrophic structural collapse and failures. Most importantly, this brings the necessity of safety assessment of the structures, especially of the large concrete dams affecting the lives of many on the downstream of a dam. Hence, it is required to develop a damage detection system able to recognize the cracks or discontinuity on the dam before they start to propagate. To this end, the Structural Health Mentoring (SHM) process should be adopted to control and keep the structures safe. This safety system will provide with the possibility to detect the damages quickly so that the engineers will be more capable of doing safety operation in terms of maintenance and repairing of structures. Wavelet transform was introduced as an efficient SHM process to achieve the objective of damage detection. This approach can extract hidden information from the obtained results of structural analysis. In this research, using wavelet transform, the static and model analysis of the Koyna gravity dam was done, and the supposed cracks were identified. The obtained results showed that during the damage detection process based on the static data, factors such as vicinity of the crack to the location of sample points were found to be affecting the wavelet coefficients. On the contrary, the modal analysis indicated that the aforementioned relation would not be revealed, and the damage could be properly detected over the regions with high expectation of failures. It was observed that the height of the dam reservoir in the static analysis was not affected to accurately identify damages by the wavelet transform. In addition, the results including the effect of damages under higher modes and multiple cracks during the damage detection process were thoroughly explained and clarified.