On the data-driven damage detection of offshore structures using statistical and clustering techniques under various uncertainty sources: An experimental study

Damage detection procedure of offshore structures based on data-driven techniques is of paramount importance to ensure their safety and integrity, especially in real-world applications. Therefore, the main aim of this article is to propose an improved clustering-based method for data-driven damage detection with the aid of a distance scaling technique. The feasibility and reliability of the method presented in this study is exemplified by application in a laboratory jacket-type offshore platform under different damage scenarios along with several comparative studies. Results are demonstrated to be effective and successful in detecting early damage of the offshore structure in the presence of various uncertainty sources.