Blar i Institutt for havromsoperasjoner og byggteknikk på tidsskrift "IEEE Transactions on Instrumentation and Measurement"
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A Deep Learning Approach to Detect and Isolate Thruster Failures for Dynamically Positioned Vessels Using Motion Data
(Peer reviewed; Journal article, 2020)Vessels today are being fully monitored, thanks to the advance of sensor technology. The availability of data brings ship intelligence into great attention. As part of ship intelligence, the desire of using advanced ... -
A Hybrid Approach to Motion Prediction for Ship Docking— Integration of a Neural Network Model into the Ship Dynamic Model
(Peer reviewed; Journal article, 2020)While automatic controllers are frequently used during transit operations and low-speed maneuvering of ships, ship operators typically perform docking maneuvers. This task is more or less challenging depending on factors ... -
A Novel Densely Connected Convolutional Neural Network for Sea State Estimation Using Ship Motion Data
(Peer reviewed; Journal article, 2020)Sea state estimation is a fundamental problem in the development of autonomous ships. Traditional methods such as wave buoy, satellites, and wave radars are limited by locations, clouds and costs, respectively. Model-based ... -
Online Fault Detection in Autonomous Ferries: Using fault-type in-dependent spectral anomaly detection
(Peer reviewed; Journal article, 2020)Enthusiasm for ship autonomy is flourishing in the maritime industry. In this context, data-driven Prognostics and Health Management (PHM) systems have emerged as the optimal way to improve operational reliability and ...