A Novel Big Data Collection System for Ship Energy Efficiency Monitoring and Analysis Based on BeiDou System

Abstract

The call for green shipping is increasing, and the reduction of greenhouse gas emissions from ships becomes more and more important. Traditional ship energy efficiency monitoring is based on the noon reports, which are susceptible to human error and have a time delay. Many ship energy efficiency monitoring systems have been designed and developed, but they usually cannot send data to the shore in time. In order to identify abnormal fuel consumption in time, this paper realizes a big data collection system for ship energy efficiency monitoring based on the BeiDou System. The system installed on two sister container ships has already collected a lot of data. Big data analysis methods, such as principal component analysis (PCA) and correlation analysis, are applied in the system to realize data visualization and analysis. Using PCA, it turns out that the shaft power of the main engine is related to a certain ship speed, which is also affected by load and weather conditions, and is the biggest factor in determining fuel consumption. To realize the assessment of hull fouling and the optimization of ship trim, a useful physics-based analysis is proposed. The analysis shows that the fouling of ship body greatly increases its resistance. Our analysis method can also find the best trim under specific loading condition. All these points are important for reducing fuel consumption and improving ship efficiency.