In recent years significant research efforts have been dedicated to evaluate the possibility of estimating directional wave spectrum by monitoring vessel motions. In previous papers the authors addressed the problem of estimating the sea spectrum from stationary FPSO units as an alternative to the use of wave-buoys or radar systems. Many aspects of the problem have been discussed; particularly the sensitivity to errors concerning the parameters that control the transfer function of motions (RAOs). Different statistical methods have been confronted in numerical simulations for unimodal and bimodal spectra and a preliminary experimental validation was obtained in towing tank tests. This paper complements the on-going research by evaluating the performance of the proposed methodology based on field measurements. The real-scale data was obtained in an extensive monitoring campaign based on an FPSO unit operating at Campos Basin, Brazil. Data included vessel motions, heading and tanks loads. A heave-pitch-roll buoy was installed in the vicinity of the unit for monitoring the waves. Comparison between the spectra estimated from vessel motions and wave-buoy allowed evaluating the reliability of the methodology proposed. The performance based on two different statistical methods (Bayesian and Parametric models) is compared and the sensitivity to input parameters is discussed. A particularly interesting issue is addressed regarding the possible elimination of roll motion in the estimation process. It was shown that this option enhances the reliability of the estimations since roll motion is extremely sensitive to viscous damping level, which is difficult to estimate.


The possibility of estimating directional wave spectrum based on ships motions has been investigated for many years. The idea is to use the vessel as a wave buoy to predict the sea characteristics that induced the 1st order motions measured on-board. Undoubtedly the main appeal of this methodology resides in the operational simplicity of the hardware system required to perform such estimations.

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