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

A novel approach to damage detection based on dispersion analysis and signal processing methods is described. The proposed method was used on a scaled experimental model of a jacket-type offshore platform. A forced vibration test was conducted on the platform to acquire the acceleration signals. The frequency spectrum of the first intrinsic mode function of the recorded signals was obtained by the Hilbert transform (HT); it was found that damage engendered dispersion in the extracted frequencies. A novel damage index, capable of accurate damage detection and based on the Mahalanobis distance dispersion of the HT frequency spectrum was thus developed. The results of this work show that the proposed index can determine the location and severity of damage with acceptable accuracy.

Automated summary

A novel approach to damage detection based on dispersion analysis and signal processing methods is described in this study. The proposed method was applied on a scaled experimental model of a jacket-type offshore platform, and a forced vibration test was conducted to acquire the acceleration signals. The frequency spectrum of the first intrinsic mode function of the recorded signals was obtained using the Hilbert transform, revealing that damage caused dispersion in the extracted frequencies. A new damage index, based on the Mahalanobis distance dispersion of the HT frequency spectrum, was developed for accurate damage detection. The results demonstrate that the proposed index can accurately determine the location and severity of damage.