Abstract
The present work tackles the modeling problem concerning the initial steps of a Digital Twin (DT) application in a maneuvering ship. To envision a real implementation, further problems need to be solved, such as architecture design, communication network, digitalization purpose, etc., subjects which will not be aborded here. Instead, we concentrated on developing a well-rounded general system model that will enable the future employment of DT technology. Some examples can include performance analysis due to degradation of the hull, rudder, or thruster; decision support for maintenance scheduling; or even distance monitoring.
The paper focuses on real-time estimation of the main vessel hydrodynamic coefficients — namely the drift and resistance coefficients — through ship motion measurements (obtained from GNSS and Gyrocompass) and the input commands to the propeller and rudder.
Compared to the previous (OMAE2021-62899), we included proper propeller and rudder models; replaced the Extended Kalman Filter (EKF) with the Unscented Kalman Filter (UKF) and estimated the coefficients directly instead of its linear approximation.
Some maneuvers were tested within a simulated environment called pyDyna — a ship maneuvering simulator implemented on python based on the mathematical model adopted in the TPN-USP Ship Maneuvering Simulation Center. Data from motion sensors were mimicked by inducing a Gaussian white noise in the data retrieved from the simulator in real-time intending to better represent a real-world scenario.
Preliminary results show good adherence and low computational, possibly presenting as a convenient preliminary parameter assessment until more precise and time-consuming methods such as CFD are evoked.