Vessel Stabilizer Control Using Machine Learning for Resource Balance
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Solution Overview
Problem
Existing vessel stabilization systems require manual adjustment by operators to select appropriate settings for different stabilizer systems based on sea and weather conditions, leading to inefficiencies in resource usage and crew comfort, especially when multiple systems are involved.
Innovation Solution
A vessel stability controller that learns optimal stabilizer settings through training based on operator inputs, resource usage, and environmental conditions, allowing it to autonomously adjust stabilizer system settings to conserve resources and enhance stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of stabilizer settings is used, then operators can select appropriate settings based on experience, but resource usage efficiency deteriorates due to lack of optimization
Solution Approach 1:
The control system automatically monitors vessel motion parameters, sea conditions, and stabilizer performance to autonomously adjust stabilizer settings without requiring continuous manual intervention. The system learns from operational data and independently optimizes resource usage while maintaining stabilization effectiveness.
Solution Approach 2:
The system continuously receives feedback from motion sensors and environmental sensors about vessel stability and sea conditions, processes this information through machine learning algorithms, and automatically adjusts stabilizer settings in real-time to optimize both performance and resource consumption based on actual conditions.
2Stability of the object's composition
If multiple stabilizer systems are operated simultaneously, then vessel stability improves through combined effect, but resource consumption increases
Solution Approach 1:
The system evaluates the actual stabilization need based on vessel motion and sea conditions, then activates only the necessary portion of available stabilizer systems. When full stabilization is not required, the system reduces or disables certain stabilizers to conserve resources while maintaining adequate stability through the remaining active systems.
Solution Approach 2:
The control system dynamically adjusts the operation of multiple stabilizer systems based on real-time conditions, transitioning between different combinations of active stabilizers as sea states and vessel response characteristics change, thereby optimizing the balance between stability performance and resource consumption.
3Use of energy by moving object
If automated machine learning control is implemented, then resource optimization improves through intelligent adjustment, but system complexity increases
Solution Approach 1:
The control system integrates multiple functions including motion sensing, environmental monitoring, machine learning processing, and stabilizer control into a single multi-functional platform. This universal controller handles various stabilizer types and coordination scenarios, reducing the need for separate specialized systems and managing complexity through consolidation.
4Stability of the object's composition
If continuous monitoring and adjustment is performed, then vessel stability is maintained under varying conditions, but energy consumption increases
Solution Approach 1:
The system performs monitoring and adjustment operations at optimized intervals rather than continuously, using predictive algorithms to determine when stabilization intervention is actually needed based on sea condition patterns and vessel response characteristics. This periodic action maintains stability while reducing unnecessary energy consumption from constant adjustment cycles.
Data Source
AI summary
A stability controller includes a machine learning engine that outputs stabilizer settings to several on-board stabilizer systems of a vessel based on various inputs. The machine learning engine is first trained based on human selections of stabilizer system settings, and then, once suitably trained, the stability controller can be used to optimize the use and operation of the stabilizer systems as conditions change, based on a quantity or stability quality that the vessel operator desires to optimize.