Damage detection of piles in a pile-supported wharf using the energy density function of a signal

Marine structures are exposed to harsh sea environments. These structures may suffer physical damages such as collision, explosion, and chemical ones like corrosion during their exploitation. Diagnosis of damages and their repair in these important structures increase their service life. To find the damage to a structural system, it is necessary to consider its effects. According to the theory of structures, the static and dynamic responses of any structure are related to its stiffness. As a result, any sudden change in the stiffness is accompanied by a change in the static and dynamic responses 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 the one hand and their expensive maintenance costs on the other hand have led researchers to strive to find more accurate and useful methods for detecting structural damage to 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 that had 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). Evaluation of the results demonstrated that the proposed method in multiple damage simulation scenarios accurately predicted the location of three damages without any additional errors. While estimating the location of damages is accompanied by error in other methods. Comparison between the results obtained from the proposed method and laboratory results demonstrates the capability of the introduced method to detect multiple damages by calculating the continuous wavelet transform energy density.