A method for damage detection of a jacket platform under random wave excitations using cross correlation analysis and PCA-based method

Abstract

In order to achieve accurate identification of structural damages, the structure health monitoring (SHM) has been developed rapidly for the jacket platform during the latest decades. However, the damage detection in structure health monitoring should consider the variation caused by ocean environmental conditions. Many researchers have shown that the cross correlation function is a good approach in extracting structural characteristics by proceeding it between the vibration responses from various structural locations. Besides, the principal component analysis (PCA) method has been proved effective in eliminating the environmental variations. As a consequence, this paper proposes an approach in developing a PCA-based method for identifying the structural state from the feature vector constructed by cross correlation functions. The proposed method was firstly applied on detecting the damage of numerical model of a jacket platform in the Bohai Sea. Subsequently, a scaled model of the studied jacket platform was made and, model tests were carried out to validate the proposed method. After summarizing the damage detection results of numerical simulations and model tests, it can be concluded that the proposed method behaves good in different damage scenarios under the random wave excitations and, the accuracy varies with the damage location and severity.