The use of the combined method of empirical mode decomposition (EMD) and Wigner-Ville distribution (WVD) is presented for the vibration-based damage detection of offshore platform model. Empirical mode decomposition is a time-series analysis approach that extracts a custom set of basis functions to describe the vibration response of a system. Combined with the WVD technique, the EMD method provides some unique information about the nature of the vibration response. Firstly, EMD technique is used to decompose the response signal of structural vibration into several mono-component signals named intrinsic mode functions (IMFs). Some selected intrinsic mode functions is analyzed via WVD method to detect the occurrence and severity of damage. Experimental study with a three-dimensional offshore structural model containing a simulated damage subjected to excitation was performed to demonstrate the efficiency and validity of the proposed method. The results show that the combined method of EMD and WVD can be used to indicate the presence of structural damages in an efficient manner. This work is the first stage of a project whose objective is to develop a reliable low-cost technique for structural health monitoring using the vibration response of offshore platform.
Offshore structures are frequently subjected to damages caused by aging, environmental, fatigue and other factors during their service life due to. Many damages can significantly affect the structural properties including stiffness, natural frequencies, etc., which are extremely important to the performance and safety of offshore structures. Therefore, the ability of damage detection is becoming increasingly significant for structural health monitoring of offshore structures. As one of structural health monitoring techniques, vibration-based damage identification has been employed broadly over the last decade. A signal measured from the sensors located on a structure can not be analyzed directly to determine the structural condition unless the damage intensity is considerable high.
