Damage detection of offshore platforms using dispersion analysis in Hilbert–Huang transform

Abstract

This article presents a novel approach to damage detection based on dispersion analysis and signal processing methods. The proposed method is conducted on a scaled experimental model of a jacket type offshore platform. A forced vibration test is conducted on the platform to acquire the acceleration signals. The frequency spectrum of the first Intrinsic Mode Function (IMF) of the recorded signals is obtained by Hilbert transform; as it turns out, damage engenders dispersion in extracted frequencies. Hence, a novel damage index, capable of accurate damage detection, based on Mahalanobis Distance Dispersion (MDD) of the Hilbert transform frequency spectrum is provided. Results show that the proposed index can determine the location and severity of the damage with acceptable accuracy.