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.

Digital Green Shipping Innovation

“…Given the advantages of big data technology in processing diverse and valuable data in large volumes with high speed, big data-based evaluation of energy efficiency in shipping also receives research attention. It helps estimate and predict the energy consumption of shipping equipment (Altarriba & Halonen, 2020); therefore, it is the core engine of the big data collection system for ship energy efficiency monitoring and analysis (Zeng & Chen, 2021;Greene et al, 2020;Man et al, 2018). Together with machine learning, big data is widely used to estimate ship fuel consumption (Zhu et al, 2021;Ji, 2021;Yan et al, 2021;Tran, 2020), analyze aircraft energy consumption (Kim et al, 2019), and predict power consumption in shipping (J. et al, 2022).…”

A Method for Assessing the Security of Energy Trading Data Based on Big Data and the Pagerank Algorithm

“…In this paper's approach to assessing the security of energy trading data, the assessment requirements are set out in six different dimensions, as shown in the table 1: As shown in Table 5, based on these six dimensions, big data technology is used to obtain relevant information. Fast access to relevant information in the storage terminal for energy trading data [4]. The terminal vector space v for energy transaction data is calculated as equation ( 1): 1122 ( ) (, , ,)…”

A Pilot Study of Stacked Autoencoders for Ship Mode Classification

“…Research on smart ships has been actively pursued, and various methodologies and network architectures that can smoothly collect data from ships in operation have been proposed. This research has included areas such as big data collection systems [3], cyber security considerations [4], data management to reduce learning costs [5], framework structures for index systems [6], surveys of architectures and applications [7], and priority items for smart shipping [8]. Furthermore, various data on actual ships is being collected, Appl.…”