Over the past years, container ships have grown dramatically in size and the largest ships today have more than 21,000 nominal TEU positions.
The increasing size of container ships influences their structural response to waves, and large ships are structurally ‘softer’ than their smaller counterparts. Wave impacts on the hull can cause global high-frequency vibrations in the structure at its natural periods (typically around 2-2.5 seconds). Traditionally, these vibrations are considered from a strength and fatigue point-of-view during the design.
This project aims at developing knowledge of active vibration modes on large container ships in operation, in different weather and operating conditions. This is going to be established by combining automatic operational modal analysis (OMA, including automatic harmonic removal of propeller harmonics), with state-of-the-art Big Data architectures and analysis procedures. Machine learning may also be used to find the patterns between operating conditions and excessive vibration levels