| Maritime transport plays a crucial role in the volume of international trade.With the continuous development of economies around the world and the rapid growth of international trade,the volume of maritime transport continues to rise.Global environmental governance faces significant challenges.The International Maritime Organization constantly updates its ship pollution prevention regulations,promoting the renewal and upgrading of energy-saving and emission-reduction technologies for ships.During the navigation of ships,water flow creates friction on the surface of the hull,resulting in frictional resistance.Frictional resistance accounts for the vast majority of the total resistance of a ship,and a greater frictional resistance requires the ship to consume more fuel to maintain the same speed.Therefore,in order to reduce the fuel consumption of ships,it is necessary to minimize the frictional resistance as much as possible.Air curtain drag reduction technology is a novel energy-saving technology and an effective method for reducing the frictional resistance of ships.However,current traditional air curtain drag reduction technologies are based on fixed jet forms,resulting in low drag reduction efficiency and suboptimal energy-saving rates.To address these issues,this research project focuses on the study of an intelligent control system for air curtain drag reduction based on support vector ships.First,the feasibility of the support vector machine algorithm is verified through two stages of flat plate experiments.The first stage involves measuring the drag ratio data for different jet volumes at different flow velocities using a flat plate.The second stage,building on the first stage,considers the water depth in shallow water environments,measuring the drag ratio data under different flow velocities,water depths,and jet volumes.The experimental data is preprocessed,and the support vector machine algorithm is used to train and test the preprocessed experimental data.The parameters of the support vector machine algorithm have a significant impact on the model’s accuracy,so an improved fireworks algorithm is used for optimization.Based on the experimental data,a support vector machine prediction model with drag ratio as the output variable is obtained.The model’s accuracy and precision are tested and compared with three other models.The validation demonstrates the applicability of the improved fireworks support vector machine prediction model in air curtain drag reduction.Moreover,the improved fireworks model exhibits better accuracy and precision compared to traditional prediction models.Finally,based on the prediction model,inverse calculations are performed to obtain the optimal jet volume data sets for air curtain drag reduction under the two different experimental conditions in the first and second stages.Next,the design and implementation of the ship model hardware for the air curtain drag reduction control system of ships were carried out according to the control scheme.The overall architecture of the control system hardware was presented,including the signal acquisition module,the signal processing module,and the signal output module.The signal acquisition module consists of depth sensors and flow velocity sensors.The control system uses the STM32 control chip as its core for signal processing,and the output module is a flowmeter.The depth and flow velocity signals collected by the sensors are transmitted to the control chip,realizing the data acquisition process.The control chip processes the data and outputs the corresponding control signals to adjust the bubble volume through the flowmeter.Finally,the control system is validated.The control system is applied in a circulating water tank for system validation,and data is collected for data acquisition and model training.This enables intelligent dynamic adjustment of the optimal jet volume under various operating conditions.Compared to the fixed jet operation under multiple conditions,the intelligent jetting achieves an average drag reduction rate increase of 8%.This validates that the air curtain drag reduction system for ships based on the support vector machine algorithm can improve the drag reduction rate of air curtain technology,thus enhancing its energysaving efficiency. |
