WP 5 Innovation leads
Reliability of Onboard Ship Sensor Data for Energy Efficiency Analysis
Researchers: Ella-Lovise Hammervold Rørvik and Pauline Røstum Bellingmo (SINTEF Ocean).
Collaborating partner: Grieg Star.
Problem: Shipping companies experience that low-quality onboard sensor data makes it challenging to perform reliable energy efficiency analysis. Common issues include sensor drift, missing data, and inconsistencies, reducing trust in analysis results.
Solution: Develop methods to improve sensor data reliability through:
- Drift detection algorithms to detect and flag sensor degradation
- Data cleaning to identify and remove unreliable measurements based on e.g. drifting.
Purpose & Value: Methods for automatic data cleaning to support:
- Reliable energy efficiency analysis
- Better operational decision-making.
Crane simulator
Researchers: Pauline Bellingmo (SINTEF Ocean) and Esten Ingar Grøtli (SINTEF Digital).
Collaborating partner: NCL.
Problem: Cargo handling in ship operations poses risks due to heavy loads, necessitating innovation to mitigate accidents. Automation and remote control can offer safer and more efficient operations by moving people from hazardous situations. Remote operations poses challenges in operators' situational awareness.
Solution: A modular crane simulator framework has been developed, providing a flexible platform to identifying sensor configurations that can enhance situational awareness in remote control of ship cranes.
Purpose & Value: A new platform for testing and optimizing cargo handling operations, enabling safe remote crane operations.
