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Ship As a Wave Buoy - Estimating Full Direction Wave Spectra From In-service Ship Motion Measurements Using Deep Learning

AuthorsScholcz, T.P., Mak, B.
Conference/Journal39th International Conference on Ocean, Offshore & Arctic Engineering (OMAE 2020)
Date1 Aug 2020
The ocean wave directional spectrum is an important wave characteristic for maritime safety and navigation. Accurate estimation of directional spectra in real-time is a challenge. In this study we aim to reconstruct the directional spectra from ship motions using a deep convolutional encoding-decoding neural network. In-service measurements of ship motions and wave spectra from a WAMOS II wave scanning radar were used to train the neural network. The data was collected from a frigate type ship for a period of two years. We demonstrate that the deep convolutional encoding-decoding neural network is successful in predicting the directional spectra in real-time. At the same time, we conclude that more data is needed for a better prediction performance , including a more complete coverage of operational conditions.


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Thomas Scholcz


Bart Mak

Senior Researcher

data scienceresearch and developmentseakeepingnavywaves, impacts and hydrostructuralonboard advisorymarine systems