457 results about "Ship control" patented technology

The invention discloses a ship control auxiliary method based on machine learning, and relates to the technical field of ship intelligent control, and the method comprises the steps of ship data collection, fuel oil energy consumption prediction, dynamic navigational speed planning and energy-saving feedback control. According to the method, the fuel energy consumption is predicted by adopting a prediction method combining multi-mode and disturbance self-adaption, modeling multi-dimensional data is unified, perception of environmental disturbance is enhanced, accurate prediction of the fuel energy consumption under complex navigation conditions is realized, and the reliability of subsequent dynamic navigational speed planning is effectively improved; dynamic speed planning is carried out by adopting a speed planning method combining multiple targets and segmented constraints, three core factors of fuel energy consumption, navigation time and safety risks are comprehensively considered, a multi-target cost function is constructed, segmented constraints are introduced, the physical feasibility and risk control of speed adjustment are guaranteed, the speed is optimized through a reinforcement learning mechanism, and the speed planning efficiency is improved. Intelligent self-adaptive navigational speed adjustment is achieved, and the energy-saving capacity, the navigation efficiency and the operation safety of the ship under the complex navigation condition are improved.

The invention relates to a high sea condition unmanned ship dynamic anti-interference control method based on intelligent body.The method comprises the following steps that information is collected, multi-source data are integrated through a data fusion algorithm, and multi-mode sensing data are obtained; constructing a body-equipped intelligent model, taking the multi-modal sensing data as input and the unmanned ship control instruction as output, and performing offline training; constructing an interference prediction model to predict the change trend of interference factors under the high sea condition, and performing adaptive interference compensation according to an interference prediction result; a hierarchical control structure is designed, a task planning layer makes a global navigation plan based on risk assessment, a motion control layer adopts a model prediction control and adaptive sliding mode control combined algorithm to convert instructions, and an execution mechanism layer drives an execution mechanism; meanwhile, online self-adaptive optimization is carried out, and the intelligent model with the body is updated and optimized according to feedback information. Compared with the prior art, the dynamic anti-interference capability, the operation precision and the reliability of the unmanned surface vehicle under the high sea condition are remarkably improved, the environment adaptability and the autonomous operation level of the unmanned surface vehicle are enhanced, and the unmanned surface vehicle is suitable for various high sea condition ocean operation scenes.

The invention relates to the technical field of ship control, in particular to a fishing boat control system based on data analysis, which comprises a traction load analysis module, a fluctuation condition division module, an attitude disturbance estimation module, a propulsion power regulation module and a rudder angle correction output module. According to the method, by analyzing the traction force load sequence value and the moment arm length of the fishing net traction point, calculating the left and right side offset torque and marking the action direction, the attitude adjustment precision of the ship is optimized, the operation sea condition level is adjusted according to data, and the ship can be subjected to more reasonable attitude estimation and adjustment under the dynamic working condition; the wind pressure change rate and the pitch angle rate are combined to judge the direction resultant force trend, and the navigation attitude is adjusted according to the sea condition grade, so that the ship can more accurately resist the influence of sea surface storm waves and maintain the course stability, and the rudder angle is corrected by adjusting the propulsion power in real time, limiting the adjustment amplitude of the propulsion power and correcting the rudder angle according to the real-time data of the navigation attitude. And the propulsive efficiency and the navigation precision are optimized.

The invention relates to the technical field of ship control, and particularly provides an energy optimization method and device for a pure electric tug, a storage medium and a control system. According to the method, the operation navigation data, collected in real time, of the pure electric tug can be input into the pre-constructed operation classification model, and the real-time operation state is obtained. If the real-time operation state of the pure electric tug is a heavy load dragging state, determining the current propulsion power demand and the total power demand of a propulsion system in the pure electric tug, and inputting the operation navigation data, the current propulsion power demand and the total power demand into a pre-constructed power distribution model, and performing power distribution according to a power distribution coefficient output by the model. Therefore, the power distribution response can be quickly and accurately made based on the intelligent power distribution model, and the intelligent ship is realized. Moreover, electric energy supply of the propulsion system can be guaranteed preferentially, so that sufficient power supply of the propulsion system can be guaranteed, and the operation efficiency of the pure electric tug can be improved.

The invention relates to the technical field of unmanned ship control, and provides an unmanned ship cluster formation cooperative control method applying a large language model. According to the method, multi-source information such as unmanned ship operation data and marine environment data is collected, deep customization training is carried out based on a large language model, and by combining transfer learning and reinforcement learning technologies, the method has autonomous learning and intelligent decision-making capabilities. During task execution, the model receives unmanned ship states, task requirements and marine environment information in real time, intelligently judges task types, plans formation forms by using an optimization algorithm and reasonably allocates tasks. For example, in a seabed surveying and mapping task, an optimal formation scheme and an optimal surveying and mapping route are determined according to surveying and mapping area characteristics and unmanned ship performance, task progress and environment change are continuously monitored, and a cooperation strategy is rapidly adjusted. According to the method, the cooperative control capability of the unmanned ship cluster formation in the complex marine environment is effectively improved, and compared with a traditional method, the method has higher autonomous learning, intelligent decision making and dynamic cooperative capabilities.

The invention discloses a dynamic sea condition ship-machine cooperative attitude control system and method for sea grass transplantation, and belongs to the crossing field of marine ecological restoration and intelligent ship control. The system comprises a mother ship attitude control layer, a communication management layer, an underwater operation end and a sensor network layer, the mother ship attitude control layer, the communication management layer, the underwater operation end and sensor network layer and the mother ship attitude control layer are sequentially connected through lines; the method integrates inertial navigation, visual measurement, event-triggered communication and adaptive filtering technologies, realizes high-precision attitude synchronization and stable operation of the ship and the underwater operation device in sea conditions of four levels and below, and can be widely applied to marine ecological engineering scenes such as seaweed bed restoration, coral transplantation and submerged vegetation reconstruction. And the operation efficiency and the environmental adaptability are effectively improved.

The invention discloses a ship attitude prediction method and system based on FT-Mama architecture. The method comprises the following steps: collecting training data of multiple modes; performing feature extraction on the training data of various modes to obtain time domain features and Fourier transform frequency domain features corresponding to the training data of various modes; according to the time domain feature and the Fourier transform frequency domain feature, training a preset FT-Mama multi-modal fusion model to obtain a ship attitude prediction model; obtaining to-be-processed multi-modal ship data, inputting the to-be-processed multi-modal ship data into the ship attitude prediction model, and outputting a ship attitude prediction result; wherein the training data comprises ship attitude data, sea condition data and meteorological data. The method can effectively improve the ship attitude prediction precision under the complex sea condition, reduces the prediction delay, provides reliable look-ahead information for boarding compensation control, and can be widely applied to the technical field of ship control.

The invention discloses a ship dynamic collision avoidance decision-making method based on an improved DWA algorithm. The ship dynamic collision avoidance decision-making method comprises the steps of constructing sea chart environment data containing obstacle density through a grid method; establishing a dynamic elliptical ship domain based on a quaternion ship domain (QSD) model, and calculating a distance collision risk degree (NCRI) between ships based on the dynamic elliptical ship domain; improving a DWA algorithm evaluation function, and adding a path yaw evaluation function and a collision avoidance rule evaluation function on the basis of optimizing a speed and azimuth angle evaluation function; fusing the multiple evaluation functions by adopting a weight distribution method; and finally, generating a local collision avoidance optimization route based on environment data, NCRI and an improved DWA algorithm. According to the method, safety boundary dynamic adjustment, rule compliance constraint and ship control characteristic cooperation are realized, and the robustness and practicability of collision avoidance decision making under complex sea conditions are remarkably improved.

A marine vessel includes a vessel steering system including a boat controller configured or programmed to include an automatic vessel steering mode and a manual vessel steering mode as vessel steering modes. When a password to release a locked state is input to a multifunction display in a locked state where the vessel steering mode is fixed in the automatic vessel steering mode, the boat controller is configured or programmed to shift the automatic vessel steering mode to the manual vessel steering mode.

The invention discloses a ship intelligent energy efficiency optimization method and system, and relates to the technical field of ship energy efficiency optimization control, and the method comprises the steps: collecting the operation data of a ship navigation process, and carrying out the preprocessing of the operation data; inputting the preprocessed operation data into a ship energy efficiency evaluation model, and outputting a current energy efficiency index value of the ship; based on the energy efficiency index value, solving a ship energy efficiency optimization objective function through a particle swarm optimization algorithm to obtain an optimal navigational speed parameter and an optimal course parameter; and issuing the optimal navigational speed parameter and the optimal course parameter to a ship control system, and adjusting the ship navigation state. According to the system, the ship navigation safety is ensured, meanwhile, the fuel consumption is effectively reduced, the overall energy efficiency level is improved, and the high practical value and the intelligent degree are achieved.

The invention discloses an unattended screw ship unloader material and ship control method and system, and the method comprises the steps: collecting multi-dimensional sensing data including visual images, material weight, material types and spatial poses in real time through multiple types of sensors disposed on a screw ship unloader; performing space-time registration and fusion processing on the acquired multi-dimensional sensing data to obtain an operation scene situation sensing result for comprehensively representing the real-time state of the ship unloading operation scene; based on the operation scene situation perception result, driving a screw ship unloader digital twin model to perform real-time simulation to obtain a simulation result including a future material accumulation spatial form, equipment operation performance parameters and / or potential risk probability; and according to a simulation result of the digital twinborn model, an optimization control instruction is generated based on a preset decision rule, so that self-adaptive adjustment of ship unloading operation parameters and intelligent disposal of abnormal working conditions are realized.

The invention discloses an automatic ship driving control method and system based on artificial intelligence, and relates to the technical field of ship control, and the driving control steps are as follows: S1, obtaining a current two-dimensional coordinate position of a ship based on a satellite map, and obtaining wind direction data of the current two-dimensional coordinate position in a ship route based on a weather bureau, obtaining a ship route state construction data set; and S2, establishing a ship running model, predicting position and attitude changes of the ship in a future route in combination with real-time wind direction data, calculating a ship displacement control quantity in advance through a control algorithm, and counteracting offset generated by wind direction factors. According to the invention, the ship can timely and accurately return to a correct route, the navigation accuracy of the ship in a complex environment is greatly improved, fine adjustment of ship navigation parameters is realized, unnecessary energy waste is avoided, deviation from a target route is avoided, and the risks of collision and stranding are increased.

The invention discloses an unmanned ship-oriented task priority scheduling and resource awareness management method, and belongs to the technical field of unmanned ship control. The method comprises the steps of obtaining a task request generated by an unmanned ship system, inputting the task request into a task classifier for task classification and priority allocation, performing real-time monitoring on resources of the unmanned ship system based on a resource perception and threshold grading model, judging an alarm interval where the resources of the current unmanned ship system are located, and sending the alarm interval to the unmanned ship system. Obtaining a target scheduling strategy; allocating each task in the task request to a corresponding thread pool for execution, dynamically adjusting the scheduling of each task according to a multi-thread pool cooperation and preemption mechanism, and dynamically optimizing the load and channel of the unmanned ship system based on a load balancing and channel selection mechanism; feedback information during execution of each task is collected, a target scheduling strategy is adjusted through an adaptive optimization mechanism, and scheduling and resource allocation of each task are updated in real time. The method improves the resource utilization rate of the unmanned ship system.

The invention discloses an unmanned ship control method based on deep reinforcement learning in a multi-task scene. The method comprises the following steps: constructing dynamics and kinematics models of an unmanned ship; the method comprises the following steps: constructing a high-fidelity simulation environment based on Isaac Sim and a parallel training framework thereof, and respectively designing a state space and an action space for various unmanned ship tasks; reward functions are respectively designed; constructing an unmanned ship control strategy, and designing an algorithm framework of a centralized importance sampling and shearing strategy optimization mechanism based on an end-to-end deep reinforcement learning algorithm; and for different task scenes, multiple times of training-verification are performed on the strategy network through a PPO algorithm, and the trained strategy network is used for realizing multiple control tasks of the unmanned ship. According to the method, a high-fidelity simulation environment is constructed through Isaac Sim and a parallel training framework thereof, parallelization support which is crucial to deep reinforcement learning training is achieved, and various actual control tasks of the unmanned ship can be achieved.

The invention relates to the technical field of intelligent ship control, and particularly discloses an area control integration method and system based on an intelligent ship engine room, original operation data and multi-source communication data of equipment in each area of the engine room are collected, a unified real-time state vector is generated through protocol analysis and standardization processing, and a plurality of redundant processing nodes are processed in a unified mode. Synchronizing and verifying state data through a high-speed channel, constructing a global consistent state synchronization set, disassembling composite logic into atomic operation units with state constraints according to an upper-layer instruction and the synchronization set, packaging the atomic operation units into a private instruction sequence bound with the state, executing the instruction sequence by a main node, and executing the state synchronization set by a slave node; seamless switching to a standby node is realized through independent hardware monitoring when a fault occurs, and the standby node continuously executes based on the continuity of a state synchronization set, so that high-reliability uninterrupted operation of area control is realized; according to the method, the problems of instruction semantic distortion and single-point fault risk in heterogeneous equipment integration are solved, and the control accuracy and the intelligent level are improved.

The invention discloses a water surface unmanned ship control method and system under path tracking, and relates to the technical field of attitude control, and the method comprises the steps: building a kinetic model of a water surface unmanned ship; establishing a path tracking error equation for describing a system error of the unmanned surface ship relative to an expected path under a Serret-Frenet coordinate system; constructing a path tracking controller based on a linear active disturbance rejection controller; inputting the system error and a water surface unmanned ship control signal into a fuzzy RBF neural network, and outputting an optimal control parameter of a path tracking controller by taking minimization of the system error as a target; updating a path tracking controller according to the optimized control parameters; and re-estimating external disturbance by using the updated path tracking controller, outputting a control signal for optimizing the water surface unmanned ship, and controlling the water surface unmanned ship to advance along an expected path. According to the invention, the attitude control precision under strong ocean current and changeable weather is improved, and the path tracking precision of the water surface unmanned ship is greatly improved.

The invention discloses a geometric constraint fitting point cloud filtering method for sea surface three-dimensional reconstruction, and belongs to the technical field of computer vision and three-dimensional reconstruction. The objective of the invention is to solve the problem of insufficient subsequent three-dimensional reconstruction precision caused by interference of reflection noise, mismatching points and the like in sea surface point cloud. The method specifically comprises the following seven steps: firstly, acquiring sea surface original point cloud through three-dimensional data acquisition equipment; a filtering technology is adopted to obtain a to-be-fitted point cloud; fitting a quadric surface through an improved RANSAC (Random Sample Consensus) algorithm to solve an initial parameter; constructing a comprehensive error function, and optimizing the model through gradient descent; effective inner points are screened through quadratic term coefficient constraint and a distance threshold value; and finally, iterating until a termination condition is met, and outputting an optimal effective point cloud. The method is high in noise rejection rate, the point cloud fits the sea surface form, and high-quality data support can be provided for sea surface fitting, sea wave simulation and unmanned ship control.

The invention belongs to the technical field of unmanned ship control, and particularly discloses a control method of a fixed time event triggering terminal sliding mode with preset performance constraints. The control method comprises the following steps: S1, establishing an all-drive model of a multi-under-actuated unmanned ship system; s2, designing a fixed time disturbance observer; s3, constructing a cooperative tracking error system according to the cooperative control target and the interactive topological structure; s4, restraining and converting the cooperative tracking error by using a preset performance function, and updating a cooperative tracking error system; and S5, constructing a relative threshold event triggering mechanism, designing a distributed event triggering-fixed time terminal sliding mode controller, generating an actuator control instruction, and realizing cooperative tracking control of the system through an output instruction of an actuator. According to the method, the problem of fixed-time cooperative tracking control under the preset performance constraint is solved, two indexes of'rapid cooperative control 'and'communication resource saving' are realized at the same time, and the method is applied to a cluster scene of multiple unmanned ships.

Embodiments for a battery pack for an electric marine vessel are described herein. In a particular embodiment, a battery pack for an electric marine vessel comprises a waterproof chassis, a high voltage battery comprising a plurality of battery cells disposed within the chassis, positive and negative high voltage connectors disposed on a front flange of the chassis, a manual disconnect connector disposed on the front flange of the chassis, and a signals connector disposed on the front flange of the chassis, the signals connector configured for signal communication with at least a power distribution unit and a vessel control unit. A battery management system disposed within the chassis and coupled to the signals connector comprises a battery management controller, a plurality of relays operable by the battery management controller, and a plurality of sensors electrically coupled to the battery management controller.

The invention discloses a ship control cabinet network security protection method and system, and relates to the technical field of network security, and the method comprises the steps: carrying out the function partitioning of a ship control cabinet network, and collecting the security protection configuration of each function local area network; multi-mode security threat detection is carried out, and security threat feature distribution is established; then, combining a protection degree evaluation model to optimize protection configuration, and predicting a propagation path based on threat feature distribution; compensating the protection scheme according to a prediction result; and enhancing the protection capability of each functional local area network according to an optimization result. The technical problem that when a certain area of the control cabinet network is attacked in the ship operation process, threats are prone to being diffused to networks connected with one another in other functional areas, and then normal operation of the ship is affected is solved, and the purposes of effectively preventing diffusion of security threats in the ship control cabinet network and improving the safety of the ship are achieved. Stable operation of the ship control cabinet network is guaranteed, and normal sailing of the ship is further guaranteed.

The invention discloses an electric ship remote intelligent control method and system based on cloud-side cooperation, and relates to the technical field of cloud-side cooperation computing, and the method comprises the steps: carrying out the feature extraction of images around a ship and time-space aligned multi-modal data, obtaining visual features, motion features and environment features, carrying out the feature fusion, and generating an environment situation vector; inputting the environment situation vector into a channel boundary detection model, analyzing the emergency degree of the current situation, generating a collision avoidance instruction, and generating a ship control decision through a three-level collaborative decision; combining a ship control decision with ship control characteristics, simulating a traffic development situation in a navigation area, comparing with historical ship navigation conflict data, and identifying potential conflict data; through collaborative fusion of the ship-end decision-making unit, the shore-end decision-making unit and the cloud-end decision-making unit, an optimal control strategy is generated in combination with respective advantages, intelligent decision-making of global optimization in a complex environment is realized, and adaptability and safety of ship control are enhanced.

The invention discloses an intelligent ship control system which comprises a ship interaction data acquisition module, a ship state extraction module, a navigation experience screening module, a multi-ship cooperative control agent training module, a ship parameter adaptive adjustment module and a ship control module. The invention belongs to the field of intelligent control, and particularly relates to an intelligent ship control system. According to the scheme, core features are extracted through double-branch extraction, and a dynamic transition probability similarity coefficient is introduced, so that similarity judgment adapts to interaction strength; for positive sample pairs, ship low-dimensional features of similar behaviors are forced to approach, and for negative sample pairs, the feature distance is increased, so that a collision avoidance strategy can migrate across ship types; navigation experience screening is carried out through safe sampling guided by a reference path, and dangerous data interference is avoided; extreme risk punishment is added to strengthen fitting of the close-range collision sample; and an environment perception dynamic period is introduced, an adjusted safety reward is set, and environment change is dynamically adapted, so that the ship control effect is improved.

A marine maneuvering system for a marine vessel is provided. The marine maneuvering system comprises a marine vessel control unit configured to: obtain a requested movement of a joystick indicating a speed value and a direction value for an upcoming navigation of the marine vessel; obtain proximity signals from a proximity sensor in response to a target being sensed in at least portions of an environment surrounding the marine vessel at least towards a direction indicated by a direction value of the joystick; determine a distance between the marine vessel and the target based on the proximity signals; and control a force feedback device to apply a force feedback to the joystick based on the determined distance.

The invention discloses a river surface flow velocity measurement method, system and product based on a video image, and the method comprises the steps: firstly selecting N unmanned ship control points, and calculating a perspective matrix through the geographic coordinate data of an unmanned ship and the pixel coordinates of the unmanned ship in the video image; wherein N is a preset value; converting the geographic coordinates of the point with the speed to be measured into pixel coordinates through the perspective matrix; using an RAFT optical flow model to generate a pixel-level speed of each pixel of the video image, namely an optical flow field; acquiring the pixel-level speed of the to-be-measured speed point from the optical flow field by using the pixel coordinates of the to-be-measured speed point; and finally, obtaining the real-level speed of the river by using a multi-layer perceptron. According to the method, the real speed measured by the ADCP carried by the unmanned ship is utilized to supervise and train the multi-layer perceptron model, the combined loss function is utilized to restrain the model, and the real-level speed can be predicted by combining river position features and numerical value features. According to the invention, a non-contact video acquisition mode is adopted, the equipment cost is reduced, and the measurement efficiency is improved.

The embodiment of the invention provides a ship control method and device, electronic equipment, a readable storage medium and a chip, and the method comprises the steps: determining a first distance range and a second distance range corresponding to a target ship; determining an obstacle tracking detection result obtained based on perception fusion in the first distance range; determining information parameters of a plurality of ships in the ship automatic identification system within the second distance range; determining a sailing ship according to the obstacle tracking detection result and the information parameters; determining a relative position type of at least one sailing ship corresponding to the target ship; determining a traffic flow value of the current driving water area of the target ship according to the information parameters; and according to the relative position type and the traffic flow numerical value, switching a driving mode of the target ship, wherein the driving mode comprises a tracking mode and a ship following mode. According to the scheme, the safety of tracking or following the ship by the automatic driving ship in the inland river environment is improved.

The invention discloses a ship control method and device in an inland river scene, electronic equipment and a storage medium, and can be applied to the technical field of intelligent navigation of ships. According to the method, the ship traveling wave energy distribution rule is calculated according to the first state information and the second state information which are acquired in real time, then the first following distance is determined, and then path planning is performed by combining the ship energy consumption, the ship traveling wave energy distribution rule, the safety margin and the total navigation time which are acquired in real time to obtain the first navigation path of the target ship; a first sailing control instruction of the target ship is predicted by adopting a nonlinear model control method so as to control the sailing process of the target ship in the inland river scene, and meanwhile, the sailing process of the target ship in the inland river scene is controlled by a second sailing control instruction generated by dynamically adjusting the first sailing path according to the channel environment change information. Therefore, the balance between the energy efficiency and the sailing efficiency can be realized in the whole sailing process of the target ship, and emergencies in the sailing process can be effectively coped with.

A boat control system includes a plurality of boat propulsion devices each being steerable by 180 degrees or more about a steering axis, a controller configured or programmed to control a thrust and a steering angle of each of the plurality of boat propulsion devices, an operator to accept an operation request to move a boat body and output an operation signal to the controller, and a sensor to detect a turning of the boat body and output a detection signal to the controller. The controller is configured or programmed to perform, when the sensor detects a turning of the boat body in a status where the operator is not accepting an operation request to turn the boat body, a steering angle change process to change the steering angle of at least one of the plurality of boat propulsion devices to cancel the turning of the boat body.

The invention provides an unmanned surface vehicle course tracking control method with signal quantization based on a double-expansion observer, and the method comprises the steps: building a third-order response type unmanned surface vehicle course control mathematical model according to the characteristics of a ship and the sea condition information of a surrounding environment; designing a double-expansion observer model for simultaneously estimating matched interference and non-matched interference in the ship course tracking control system and observing uncertain items and external interference in the ship control system; based on a backstepping method and a dynamic surface control algorithm, a course controller of the unmanned surface vehicle is designed, and the calculation complexity brought by a virtual control law is reduced; based on the Lyapunov stability theory, the stability of the designed unmanned surface vehicle course tracking control system with state quantization and input quantization is proved, all signals in a closed-loop system are consistent and bounded in a semi-global mode, and the tracking error is arbitrarily small by adjusting parameters of a controller.

The invention discloses a ship crew working state monitoring method, and belongs to the technical field of ship control. The method comprises the following steps: acquiring environmental data of a ship and physiological data and behavior data of a target crew in the ship; performing time-frequency analysis on the environment data, the physiological data and the behavior data to obtain state time-frequency characteristics of the target crew; performing fusion time sequence modeling based on the state time-frequency characteristics to obtain a working state model of the target crew; the working state model is called to adjust early warning rules, the working state parameters are evaluated through the adjusted early warning rules, the working state monitoring result of the target crew is obtained, the early warning rules comprise a threshold rule, a trend rule and an association rule, and the working state parameters are obtained based on the physiological data and the behavior data. According to the method, by fusing time sequence modeling and dynamically adjusting the early warning rule, the early warning accuracy and practicability are improved, and a powerful guarantee is provided for safe operation of the ship.

The invention discloses a ship intelligent control system and method and a ship, and belongs to the technical field of ships. The intelligent ship control system comprises an energy efficiency management subsystem, a video management subsystem and a comprehensive management center. Wherein the comprehensive management center comprises a navigation equipment management module, a ballast calculation module, an alarm monitoring module and a network and monitoring module, and is used for receiving navigation data information, ballast water quantity control information, monitoring information of a ship main engine, a generator, a power supply, gas and fuel oil, network transmission information and video monitoring information during navigation of a ship; the information is analyzed and stored, and a control instruction is generated to intelligently control the ship; and the comprehensive management center carries out information distribution so as to carry out ship energy efficiency control and video monitoring control. According to the technical scheme, respective control and coordinated control of multiple functions of the ship can be realized, the control is more intelligent, the control reasonability is improved, and the navigation safety of the ship is improved.