A Novel Wavelet Packet Transform-Fuzzy Pattern Recognition-Based Method for Leakage Fault Diagnosis of Sail Slewing Hydraulic System

When the wind direction changes, rotating the sail to keep it at the optimal angle of attack can effectively utilize offshore wind resources to improve the ship’s energy efficiency. The hydraulic system usually drives the slewing of the sail onboard. The functioning, as well as the safety of hydraulic system will be directly affected in case of leakage failure occurs. Therefore, the leakage fault diagnosis is essential to improve the sail-assisted effect as well as the reliability of the sail slewing system. In this paper, a novel wavelet packet transform (WPT)–fuzzy pattern recognition (FPR) based leakage fault diagnosis method is proposed. In order to analyze the different leakage fault features of the hydraulic system, a simulation model is established, and its effectiveness is verified by the hydraulic testbed. Then, the sensitive feature of flow and pressure signal for different leakage faults is extracted by a WPT-based method. On this basis, an FPR-based leakage fault diagnosis method is proposed. The diagnosis results show that the proposed method has an accuracy of 94% for nine leakage fault modes. This work contributes to realizing the greenization of the shipping industry by improving the utilization rate of offshore wind resources

Leakage Fault Diagnosis of Lifting and Lowering Hydraulic System of Wing-Assisted Ships Based on WPT-SVM

Wing-assisted technology is an effective way to reduce emissions and promote the decarbonization of the shipping industry. The lifting and lowering of wing-sail is usually driven by hydraulic system. Leakage, as an important failure form, directly affects the safety as well as the functioning of hydraulic system. To increase the system reliability and improve the wing-assisted effect, it is essential to conduct leakage fault diagnosis of lifting and lowering hydraulic system. In this paper, an AMESim simulation model of lifting and lowering hydraulic system of a Very Large Crude Carrier (VLCC) is established to analyze the operation characteristics of the hydraulic system. The effectiveness of the model is verified by the operation data of the actual hydraulic system. On this basis, a wavelet packet transform (WPT)-based sensitive feature extracting method of leakage fault for the hydraulic system is proposed. Subsequently, a support vector machine (SVM)-based multi-classification model and diagnosis method of leakage fault are proposed. The study results show that the proposed method has an accuracy of as high as 97.5% for six leakage fault modes. It is of great significance for ensuring the reliability of the wing-sail operation and improving the utilization rate of the offshore wind resources

A novel method for joint optimization of the sailing route and speed considering multiple environmental factors for more energy efficient shipping

Energy saving and emission reduction have attracted a great deal of attention in the maritime industry. The optimization of a ship's energy efficiency can reduce energy consumption and CO2 emissions effectively. However, most of the available studies only focus on either the sailing speed or route optimization, and the interaction between speed and route under the influence of multiple environmental factors was not accounted properly. In this paper, a novel joint optimization method of the sailing route and speed, which considers the interaction between route and speed as well as multiple environmental factors, is proposed to fully exploit the energy efficiency's potential. Moreover, a joint optimization model of the sailing route and speed, which is based on an energy consumption model that considers multiple environmental factors, is established. Next, a solution algorithm for the joint optimization model is investigated in order to achieve joint decision-making with regard to the sailing route and speed. Finally, a case study is conducted that demonstrates the effectiveness of the proposed method. The results show that the proposed method can achieve the optimal sailing route and speed under complex environmental conditions, as well as a reduction in fuel consumption and CO2 emissions of about 4%.</p

A novel bi-level distributed dynamic optimization method of ship fleets energy consumption

The optimization of ship energy consumption is attracting a great deal of attention, as societies seek to save energy and reduce emissions. Shipping companies are more concerned with the energy consumption of a ship fleet, as opposed to that of a single ship. Because the energy consumption of a fleet is influenced by multiple factors including environmental factors, port operations and transport demands, an improvement in a single ship's energy consumption does not necessarily mean that the overall energy consumption of a fleet is good. In addition, those factors are usually varying over time, making it hard to optimize the fleet's energy consumption by methods that do not consider these time-varying factors. Therefore, a bi-level distributed dynamic optimization method based on distributed model predictive control is proposed. Moreover, an upper-level optimization model for fleet operational decision-making and a lower-level dynamic optimization model of fleet energy consumption are established. Based on these, a control algorithm for the dynamic optimization of fleet energy consumption is developed. Finally, a case study is carried out to demonstrate the effectiveness of the method. It can further reduce the energy consumption of each ship by at least 1.1% and about 6.8% for the whole fleet.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic

A novel method for joint optimization of the sailing route and speed considering multiple environmental factors for more energy efficient shipping

Energy saving and emission reduction have attracted a great deal of attention in the maritime industry. The optimization of a ship's energy efficiency can reduce energy consumption and CO2 emissions effectively. However, most of the available studies only focus on either the sailing speed or route optimization, and the interaction between speed and route under the influence of multiple environmental factors was not accounted properly. In this paper, a novel joint optimization method of the sailing route and speed, which considers the interaction between route and speed as well as multiple environmental factors, is proposed to fully exploit the energy efficiency's potential. Moreover, a joint optimization model of the sailing route and speed, which is based on an energy consumption model that considers multiple environmental factors, is established. Next, a solution algorithm for the joint optimization model is investigated in order to achieve joint decision-making with regard to the sailing route and speed. Finally, a case study is conducted that demonstrates the effectiveness of the proposed method. The results show that the proposed method can achieve the optimal sailing route and speed under complex environmental conditions, as well as a reduction in fuel consumption and CO2 emissions of about 4%.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic

Joint energy consumption optimization method for wing-diesel engine-powered hybrid ships towards a more energy-efficient shipping

Wing-diesel engine-powered hybrid ships can effectively reduce fuel consumption and CO2 emissions by using wind energy as the auxiliary driving power. The energy optimization management of the hybrid system can further improve the ship's energy efficiency. To achieve this purpose, it is significant to establish an effective energy consumption model for the energy optimization management of the hybrid system. Therefore, an energy consumption model is established based on the energy conversion analysis of the hybrid power system in this paper. This model can effectively describe the energy consumption of the hybrid ship under different navigational environmental conditions. Then, a joint optimization method of the wing attack angle and of the sailing speed for the hybrid ship is proposed by adopting a swarm intelligence optimization algorithm, in order to reduce energy consumption and CO2 emissions of the hybrid ship under different navigational environmental conditions. Finally, the energy consumption optimization potentials by adopting the hybrid power system and the proposed joint optimization method are analyzed. The results show that the energy consumption and CO2 emissions along a typical route can be reduced by about 4.5%. This study provides an important basis for future practical operations of wing-diesel engine-powered hybrid ships.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic

A novel dynamical collaborative optimization method of ship energy consumption based on a spatial and temporal distribution analysis of voyage data

It is of significant importance to optimize the energy consumption of ships in order to improve economy and reduce CO2 emissions. However, the energy use of ships is affected by a series of navigational environmental parameters, which have certain spatial and temporal differences and variability. Therefore, the dynamic collaborative optimization method of sailing route and speed, which fully considers the spatial and temporal distribution characteristics of those factors, is of great importance. In this paper, the spatial and temporal distribution characteristics of the environmental factors and their related ship energy consumption profiles are first analyzed. Subsequently, a ship energy consumption model considering various environmental factors is established to realize the prediction of energy use of ships within the navigation region. Then, a novel dynamic collaborative optimization algorithm, which adopts the Model Predictive Control (MPC) strategy and swarm intelligence algorithm, is proposed, to further improve the ship's energy consumption optimization. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The results show that the newly developed dynamic collaborative optimization method, which fully considers the continuously time-varying characteristics of environmental and operational parameters, could effectively reduce the energy consumption in comparison to the original operational mode. In addition, the adoption of the MPC strategy produces better performance results compared to the optimization method without the MPC strategy.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic