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On the development of an onboard sea state estimator based on numerical vessel motion data
Publikationstyp
Conference Paper
Date Issued
2022-06
Sprache
English
Author(s)
Institut
Citation
32nd International Ocean and Polar Engineering Conference (ISOPE 2022)
Contribution to Conference
Scopus ID
Publisher
International Society of Offshore and Polar Engineers
Peer Reviewed
true
Within the Joint Research Project RetroLadung, weight-optimized cell guides with integrated motion sensors and data-driven decision support systems (DSS) are developed. A basic functionality of the DSS is the estimation of sea states based on measurement data from acceleration sensors. A convolutional neural network (CNN) is created for this task and trained with simulation data. This paper presents the early development stage of the network during which unimodal, short-crested seas described with JONSWAP spectra are considered. Thereby, the forward speed is excluded. Model tank tests are conducted by the Institute for Fluid Dynamics and Ship Theory (FDS) and results are used to validate the predictions of the sea state estimation (SSE).
Subjects
Sea state estimation
DDC Class
600: Technik
620: Ingenieurwissenschaften