Vessel Disturbance Prediction Using an Environment Model
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Solution Overview
Problem
Existing methods struggle to accurately predict and handle rapid changes in external environmental disturbances, such as wind and waves, affecting vessel trajectory, especially in challenging water environments, which can lead to increased energy consumption and wear on vessel actuators.
Innovation Solution
A prediction handling device that uses a vessel environment model based on previous sensor and disturbance measurements to predict external environmental disturbances at future positions, incorporating data from various sources like radar, lidar, and cameras, and potentially a server, to enable proactive control and route planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If disturbance feedforward from onboard sensors is used in closed loop control, then the impact of disturbances can be mitigated before they affect the vessel, but rapid changes of disturbances are difficult to predict since the disturbance is not measurable before it is impacting the motion of the vessel
Solution Approach 1:
The system performs preliminary action by predicting disturbances at future vessel positions before they actually impact the vessel. The predictor uses the vessel environment model to forecast wind and wave conditions at upcoming locations, enabling the control system to prepare compensatory actions in advance rather than reacting after disturbances occur.
Solution Approach 2:
The vessel environment model acts as an intermediary between current sensor measurements and future disturbance predictions. It processes present disturbance measurements and sensor data to generate predictions about future conditions, bridging the gap between what is currently measurable and what will occur at future positions.
2Reliability
If manual control with experienced captains is used to compensate for disturbances, then the vessel can be manoeuvred to compensate for disturbances, but it requires a great deal of experience by the crew
Solution Approach 1:
The system implements self-service by enabling the vessel to automatically predict and compensate for disturbances without requiring experienced human operators. The predictor and vessel environment model autonomously analyze sensor data, forecast disturbances, and provide information for automatic control adjustments, replacing the need for expert human judgment.
Solution Approach 2:
The patent replaces the mechanical system of human expert judgment with an automated computational system. The vessel environment model and predictor use algorithms to process sensor measurements and generate disturbance forecasts, substituting human cognitive processes with automated computing and control systems.
3Measurement precision
If reaction to disturbances occurs after they impact the vessel's motion, then the vessel responds to actual conditions, but it potentially requires more energy and might introduce unwanted wear and tear of the vessel's actuators
Solution Approach 1:
The system performs preliminary action by predicting disturbances at future positions before they impact the vessel, allowing control adjustments to be made proactively. This prevents reactive corrections that would require larger, more energy-intensive actuator movements after disturbances have already affected vessel motion.
Solution Approach 2:
The system applies preliminary anti-action by preparing compensatory control actions in advance based on predicted disturbances. The control system can gradually apply counteracting forces before disturbances fully impact the vessel, reducing the need for large, energy-consuming corrective maneuvers.
Data Source
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AI summary
A prediction handling device obtains at least one present sensor measurement of the environment of the first vessel (22) at a present vessel position (PP), obtains at least one present disturbance measurement (DMP) of a first type of external environmental disturbance on the first vessel (22) at the present vessel position (PP), and obtains a prediction of the external environmental disturbance of the first type (PD1 -PD10) on the first vessel (22) at one or more estimated future positions of the first vessel (22), which prediction has been made by a predictor using the present disturbance measurement of the first type and the present sensor measurement in a vessel environment model that is based on previous sensor measurements of the environment and previous disturbance measurements of the first type.