Ship Dynamic Speed Optimization Algorithm And System Development Based On Measured Data

Under the background of the continuous reduction of fossil energy and the continuous increase of greenhouse gas emissions.Optimizing the speed of ships using fossil energy as the main fuel is an important means for ships to save energy and reduce emissions.The ship’s sailing speed plan has an important impact on the ship’s sailing efficiency and operating costs.With the rapid development of computer technology in recent years and the more urgent need for the development of intelligent ships,it is imperative to generate the optimal ship speed plan through computer automation and provide auxiliary decision-making for the crew.The research goal of this paper is to study the ship’s dynamic speed optimization algorithm and develop the ship’s intelligent speed system.Firstly,the mathematical model of ship speed optimization is established based on the measured data.Secondly,the corresponding intelligent optimization algorithm is designed to realize the establishment of the speed plan automatically by computer and provide the optimized speed.Finally,the corresponding development and application of the ship’s intelligent speed system are carried out.Based on this goal,the main contents of this paper are as follows:Considering the fact that the measured data collected by the shipborne sensors has the characteristics of a large number of outliers,missing values and data noise.In this paper,the clipping filtering method,boxplot and Lagrangian interpolation method are used to remove outliers in the original data and fill in the missing values,and use wavelet change to reduce the data noise in the data,and obtain a data set that can be used for subsequent analysis.A multi-objective segmented speed optimization mathematical model is established to reduce fuel consumption and sailing time as optimization goals.Considering the relationship between fuel consumption and main engine power and speed,the calculation model of main engine power and speed under still water is established through theoretical analysis.Considering the influence of wind,waves and currents on the still water sailing of ships,the calculation method of main engine power,speed and fuel consumption rate during actual sailing of the ship is proposed based on the measured data,and the calculation model of the main engine fuel consumption of the ship is established.Basing on the measured data,the segment is divided based on the K-Means clustering algorithm.Finally,aiming at the problem of the wear of the propeller after the ship’s operating time increases,a correction method of the propeller’s open-water characteristic curve is proposed.According to the relevant characteristics of the mathematical model of ship speed optimization,combining with the idea of dynamic programming and basing on nondominated quick-sort multi-objective genetic algorithm and TOPSIS decision-making algorithm,a ship dynamic speed optimization algorithm is designed to solve the mathematical model,and the optimal speed of each sub-segment after segment division is obtained.The effectiveness of the algorithm is verified by a practical example,and the computer can automatically formulate an optimized ship speed plan.By analyzing the requirements of the ship’s intelligent speed system,the overall architecture,system hardware architecture,system database and system software architecture of the system are designed.The 20000 t river-sea direct bulk carrier is as the application object to deploy the system hardware.And with SQL Server 2012 as the database management system and Python as the development language,the development and application of the system database and system software are realized.