عنوان مقاله [English]
Marine structures are exposed to the harsh sea environment. These structures may suffer physical damages such as collision, explosion, and chemical ones like corrosion during their exploitation. Diagnosis of damages and repairing them in these paramount structures will increase their service life. To find the presence of damage in a structural system, it is necessary to check its effects. According to the theory of structures, the static and dynamic response of any structure is related to its stiffness. As a result, any sudden change in the stiffness will be accompanied by a change in the static and dynamic response of the structure; thus, it is possible to detect the probable damage in a structural system by changing its responses before and after the damage. Extreme importance of civil structures on one hand, and their expensive maintenance costs on the other, have led researchers to strive to find more accurate and useful methods for detecting structural damage in their early stages of occurrence. In this regard, wavelet transform, which is a powerful mathematical tool for signal processing, has attracted the attention of many researchers in the field of health monitoring. In this study, based on laboratory and numerical modeling, the damage detection process in the piles of a dolphin wharf was evaluated using wavelet energy which has a high sensitivity to minor changes in a vibration signal. Also, without extracting the analytical equation of the damage index, the exact location of the damage is determined directly by calculating the continuous wavelet transform energy density (Scalogram). Evaluating the results showed that the proposed method in multiple damage simulation scenarios, accurately predicts the location of the three damages without any additional errors. While in other methods, estimating the location of damages is accompanied by error. Comparison of the results obtained from the proposed method with laboratory results demonstrates the capability of the introduced method in detecting multiple damages by calculating the continuous wavelet transform energy density.