Journal
OCEAN ENGINEERING
Volume 279, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2023.114523
Keywords
Dynamic Factor Model; Kalman filter; Simulation; Real-data implementation; Sensor data; Metocean data
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In vessel performance analysis, reliable speed-through-water (STW) information is crucial for accurate modeling of a single ship's fuel efficiency. This paper presents a study that uses three variations of a Dynamic Factor Model to estimate the STW. Simulation and real vessel data are used to validate the model's performance in minimizing systematic STW measurement error, even under non-stationary conditions.
In vessel performance analysis, reliable information about speed-through-water (STW) is key for realistic modeling of the single ship's fuel efficiency. It is paramount that STW measurements are reliable such that they can be adopted as input in fuel consumption forecast models. This paper presents a study where three variations of a Dynamic Factor Model are used to estimate the STW. A simulation study is presented to demonstrate the estimation and smoothing techniques for the Dynamic Factor Model. The model variations are then applied to real vessel data, including STW and propeller measurements, in combination with metocean data (sea currents). The present study suggests that the developed model can minimize the systematic STW measurement error even under highly non-stationary conditions.
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