CN119356340A - A method, device and system for controlling ship navigation - Google Patents
A method, device and system for controlling ship navigation Download PDFInfo
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- CN119356340A CN119356340A CN202411492696.4A CN202411492696A CN119356340A CN 119356340 A CN119356340 A CN 119356340A CN 202411492696 A CN202411492696 A CN 202411492696A CN 119356340 A CN119356340 A CN 119356340A
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/40—Control within particular dimensions
- G05D1/43—Control of position or course in two dimensions
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- G—PHYSICS
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Abstract
本发明公开了一种船体航行控制方法、装置及系统，属于船体航行控制技术领域，方法包括获取船体的结构数据和动力数据，以及船体航行环境中的气象数据和水文数据；将获取到的所有数据输入到训练好的船体运动控制模型中，得到船体的航行控制参数；根据航行控制参数对船体进行航行控制；本发明除了考虑船体自身结构对运动的影响外，还将环境因素纳入考虑范围，加入了气象条件和水文条件对船体运动的影响，使得对船体的控制更加精准，降低船体航行过程的航迹误差；通过可视化数字孪生平台的引入，采用预测加补偿的方式最大限度的确保了船舶在实际航行过程中能够按规划航迹准确航行。
The present invention discloses a ship navigation control method, device and system, which belong to the technical field of ship navigation control. The method comprises acquiring structural data and power data of the ship, as well as meteorological data and hydrological data in the ship navigation environment; inputting all acquired data into a trained ship motion control model to obtain the ship navigation control parameters; and performing navigation control on the ship according to the navigation control parameters. In addition to considering the influence of the ship's own structure on the motion, the present invention also takes environmental factors into consideration, and adds the influence of meteorological conditions and hydrological conditions on the ship motion, so that the control of the ship is more precise and the track error of the ship navigation process is reduced. By introducing a visual digital twin platform, a prediction plus compensation method is adopted to ensure to the maximum extent that the ship can accurately navigate according to the planned track during the actual navigation process.
Description
Technical Field
The invention relates to a ship navigation control method, device and system, and belongs to the technical field of ship navigation control.
Background
The traditional ship aims at carrying people and objects, and is usually controlled to navigate by a shipman, but along with the increasing of demands, the application scene is also continuously abundant, the ship is not limited to carrying people and objects, the ship also comprises the applications of measurement, exploration, remote rescue, material delivery and national defense, the navigation water area is not necessarily familiar with the water area, the problems of unknown water area, extreme meteorological conditions, long-time cruising and the like are solved, the ship is not suitable for the shipman to drive the ship under the condition, and unmanned navigation of the ship is generated under the background.
Unmanned aerial control of vessels indicates direction for new areas of marine applications. The key of unmanned aerial control is that the unmanned aerial control can automatically carry out path planning, and the ship can accurately navigate according to the planned track. However, the automatic planning of the route can be carried out at present, the simple route can be better executed, once complex routes and severe weather conditions are involved, the actual routes of the ship can generate larger deviation from the planned routes, the reason is that in the process of executing the planned routes, the general various state information of the ship is collected in real time, and the real-time correction is carried out according to the deviation between the current collected information and the planned routes, but the real-time response capability of the ship is poor due to the influence of inertia in the navigation process, so that even if the deviation from the planned routes is found, the deviation correction is carried out, the deviation correction is difficult to be completed immediately, other deviations can be brought in the correction process, and the larger deviation is finally generated before the planned routes and the actual routes.
Disclosure of Invention
The invention aims to provide a ship navigation control method, device and system, which solve the problem of large track error in the prior art.
In order to achieve the above purpose, the invention is realized by adopting the following technical scheme:
In a first aspect, the present invention provides a hull navigation control method, comprising:
acquiring structural data and dynamic data of a ship body, and meteorological data and hydrological data in a ship body navigation environment;
Inputting all the acquired data into a trained ship body motion control model to obtain navigation control parameters of the ship body;
Performing navigation control on the ship body according to the navigation control parameters;
The ship motion control model is a deep learning model constructed by taking structural data and dynamic data of a ship, meteorological data and hydrological data in a ship navigation environment as independent variables and taking navigation control parameters of the ship as dependent variables.
Further, the structural data comprises a hull structural form, a hull length, a hull width and linear characteristics, the power data comprises power control data, rudder angle control data and hull weight, the meteorological data comprises ambient wind speed, ambient wind direction and ambient temperature, and the hydrological data comprises sea state data, water depth, water flow rate and water flow direction;
The navigation control parameters comprise a host rotation speed and a rudder angle value.
Further, the hull motion control model is trained by:
And acquiring the independent variable in the history time as a training parameter, converting the training parameter into a multidimensional array, then taking the multidimensional array as the input of the ship motion control model, and training the ship motion control model by taking the difference between the actual track and the planned track of the ship as a punishment function.
Further, when the independent variable is updated, the updated independent variable is used as a new training parameter, and the ship motion control model is retrained.
Further, the hull motion control model is of a full-connection structure and is provided with a plurality of full-connection layers, each full-connection layer is provided with a plurality of nodes, the number of output nodes is 2, and the 2 output nodes respectively correspond to the rotation speed and rudder angle value of the output host.
In a second aspect, the present invention provides a hull navigation control apparatus comprising:
The data acquisition module is configured to acquire structural data and power data of the ship body, and weather data and hydrological data in a ship navigation environment;
the navigation control parameter calculation module is configured to input all acquired data into a trained ship motion control model to obtain navigation control parameters of the ship;
the navigation control module is configured to carry out navigation control on the ship body according to the navigation control parameters;
the ship motion control model is a deep learning model constructed by taking structural data and dynamic data of a ship, meteorological data and hydrological data in a ship navigation environment as independent variables and taking navigation control parameters of the ship as dependent variables.
In a third aspect, the present invention provides a vessel voyage control system comprising a visual digital twin platform, a data storage management unit and a vessel voyage control unit for performing the method of any of the first aspects;
the three-dimensional twin model of the ship body is built on the visual digital twin platform, a three-dimensional water area twin scene and a three-dimensional space twin scene are built, a motion control interface of the ship body is built, the three-dimensional twin model of the ship body is arranged in the three-dimensional water area twin scene, the three-dimensional water area twin scene is internally provided with the hydrological data to simulate the hydrological characteristics in the ship body navigation environment, and the three-dimensional space twin scene is internally provided with the meteorological data to simulate the meteorological characteristics in the ship body navigation environment;
The motion control interface comprises a first control interface influenced by the structural data, a second control interface influenced by the power data, a third control interface influenced by the meteorological data and a fourth control interface influenced by the hydrological data;
The data storage management unit is respectively connected with the visual digital twin platform and the ship navigation control unit and is used for storing structural data and power data of the ship, and meteorological data and hydrological data in a ship navigation environment;
And carrying out visual twin hull navigation control on a three-dimensional twin model of the hull in the three-dimensional water area twin scene through the first control interface, the second control interface, the third control interface and the fourth control interface, wherein the navigation control parameters required in the process are obtained through the hull navigation control unit, and carrying out navigation control on the hull in the real scene according to the result of the visual twin hull navigation control.
Further, the system also comprises an external data acquisition device which is in communication connection with the visual digital twin platform, and the visual digital twin platform can directly acquire data from the external data acquisition device to construct a three-dimensional twin scene.
Further, the three-dimensional twin model of the hull is constructed using structural data and dynamic data of the hull.
Compared with the prior art, the invention has the following beneficial effects:
according to the ship navigation control method, device and system provided by the invention, besides the influence of the ship structure on the motion, the environmental factors are taken into consideration, and the influence of meteorological conditions and hydrological conditions on the ship motion is added, so that the ship is controlled more accurately, and the track error in the ship navigation process is reduced;
building a digital twin visual platform, building a three-dimensional scene, placing a twin hull three-dimensional model, building a motion control interface of the ship, and realizing the whole process visual process of ship navigation in the three-dimensional scene;
training a ship body motion control model, and continuously accumulating actual navigation data in the subsequent use process, performing iterative optimization on the model all the time, and continuously optimizing the accuracy of the model;
The prediction flight path is realized by firstly simulating (visualizing the navigation control of the twin hull) in the three-dimensional twin scene, and then the flight path error generated in the navigation control process of the visualized twin hull is compensated in the real scene, so that the prediction and compensation mode ensures that the ship can accurately navigate according to the planned flight path in the actual navigation process to the maximum extent.
Drawings
FIG. 1 is a flow chart of a hull navigation control method provided by an embodiment of the present invention;
FIG. 2 is a schematic diagram of a hull navigational control system according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a hull motion control model according to an embodiment of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings, and the following examples are only for more clearly illustrating the technical aspects of the present invention, and are not to be construed as limiting the scope of the present invention.
Example 1.
As shown in fig. 1, the present invention provides a hull navigation control method, including:
acquiring structural data and dynamic data of a ship body, and meteorological data and hydrological data in a ship body navigation environment;
Inputting all the acquired data into a trained ship body motion control model to obtain navigation control parameters of the ship body;
performing navigation control on the ship body according to the navigation control parameters;
the ship motion control model is a deep learning model constructed by taking structural data and dynamic data of a ship, meteorological data and hydrological data in a ship navigation environment as independent variables and taking navigation control parameters of the ship as dependent variables.
The invention considers the influence of the structure of the hull on the motion, takes the environmental factors into consideration, adds the influence of meteorological conditions and hydrological conditions on the motion of the hull, ensures that the control on the hull is more accurate, and reduces the track error in the sailing process of the hull.
Example 2.
The invention provides a ship navigation control method, which comprises the following steps:
S1, acquiring structural data and power data of a ship body, and meteorological data and hydrological data in a ship body navigation environment;
s2, inputting all acquired data into a trained ship body motion control model to obtain navigation control parameters of the ship body;
And S3, performing navigation control on the ship body according to the navigation control parameters.
The ship motion control model is constructed by taking structural data and power data of a ship and weather data and hydrological data in a ship navigation environment as independent variables (input) and taking navigation control parameters of the ship as dependent variables (output), wherein the structural data comprises a ship structural form, a ship length, a ship width and linear characteristics, the power data comprises power control data (navigation speed, heading), rudder angle control data (rudder direction) and ship weight, the weather data comprises an ambient wind speed, an ambient wind direction and an ambient temperature, the hydrological data comprises sea state data (wave height), water depth, a water flow speed (flow speed in FIG. 3) and a water flow direction (flow direction in FIG. 3), and the navigation control parameters comprise a host rotation speed and a rudder angle value.
As shown in fig. 3, the hull motion control model is a deep learning model, is a fully connected structure, converts multiple sets of input parameters of acquired historical moments into a 14 x1 multi-dimensional array structure as the input of the deep learning model, the model is provided with 3 fully connected layers, and the nodes of each layer of full-connection layer are set to be 20, the final output node is 2, the main machine rotating speed and rudder angle value are respectively, the overall structure of the model is 14 multiplied by 20 multiplied by 2, and the difference between the actual track and the planned track of the ship body is used as a penalty function to train the model. The trained deep learning model can generate host rotation speed and rudder angle values as control according to the input parameters such as hull structure, hull length, hull width, hull weight, heading, speed, heading, wind direction, wind speed, temperature, wave height, water depth, flow direction, flow speed and the like, namely the trained deep learning model is used as a hull motion control model.
If the model is to be applied to other hulls, the built deep learning model is modified in a transfer learning mode based on the hull motion control model which is already trained, and the model can be obtained with higher precision through simple training on the basis of the hull motion control model which is already trained, so that the model is suitable for hull motion control models of other ships.
And for the ship motion control model after training, the optimization iterative training is continuously carried out on the ship motion control model along with the increase of acquired ship navigation data in the later period, so that the accuracy of the ship motion control model is gradually improved until the optimization iterative training can not continuously improve the control accuracy of the model.
Example 3.
The invention provides a ship navigation control system, which comprises a visual digital twin platform, a data storage management unit and a ship navigation control unit, wherein the ship navigation control unit is used for executing the method provided in the embodiment 1/2.
The visualized digital twin platform adopts Django (an advanced Python Web frame, which can rapidly develop safe and maintainable websites) as a frame, and adopts three.js (a 3D engine running in a browser) as a rendering engine, so as to improve the fidelity of the visualized model and realize the motion control of the ship model on the digital twin platform.
The method comprises the steps of constructing a three-dimensional twin model of a ship body on a visual digital twin platform, constructing a three-dimensional water area twin scene and a three-dimensional space twin scene, constructing a motion control interface of the ship body, arranging the three-dimensional twin model of the ship body in the three-dimensional water area twin scene, arranging hydrologic data (specifically including detailed hydrologic data listed in embodiment 2) in the three-dimensional water area twin scene to simulate hydrologic characteristics in a ship body navigation environment, arranging meteorological data (specifically including detailed meteorological data listed in embodiment 2) in the three-dimensional space twin scene to simulate meteorological characteristics in the ship body navigation environment, wherein two data paths are provided, one data path is related data information stored in a database (data storage management unit), and the other data path is directly connected with an external data acquisition device.
The factors influencing the ship navigation can influence the ship motion besides the self power factors, and based on the reasons, the motion control interface comprises a first control interface influenced by structural data, a second control interface influenced by power data, a third control interface influenced by meteorological data and a fourth control interface influenced by hydrological data, so that the ship motion control based on multi-factor combined action control is finally realized, and the visual navigation of the twin-hull under a set scene is realized.
The data storage management unit is respectively connected with the visual digital twin platform and the ship navigation control unit and is used for storing structural data and power data of the ship, and meteorological data and hydrological data in the ship navigation environment.
And carrying out visual twin hull navigation control on a three-dimensional twin model of the hull in a three-dimensional water area twin scene through the first control interface, the second control interface, the third control interface and the fourth control interface, wherein navigation control parameters required in the process are obtained through the hull navigation control unit, carrying out navigation control on the hull in the real scene according to the result of the visual twin hull navigation control, and compensating for a flight path error generated in the visual twin hull navigation control process.
Based on the built visual digital twin platform and a ship motion control model in a ship navigation control unit, the functions of automatic track planning, multi-ship formation navigation, dynamic navigation data deduction, navigation process rewinding and the like can be realized.
The automatic track planning is realized by primarily designing the shortest track and the speed which can pass through the obstacle according to the target position and the found obstacle, controlling the motion of the three-dimensional twin model of the ship body on the visual digital twin platform according to the set track and the speed through the ship body motion control model, continuously correcting the track on the basis, and finally forming the planning track with smooth transition.
The multi-ship formation sailing is to set relative position relations among formation ships on the basis of a planned track, a main ship sails according to the planned track, other ships generate a sailing track and control parameters in the sailing process through corresponding ship body motion control models, the generated track data and the control parameters are stored, and relevant data at any moment and at any position can be loaded at any time according to requirements for multi-disc analysis.
And (3) carrying out automatic track planning on the visual digital twin platform, wherein in the track planning process, besides planning a navigation route, the weather information and the hydrologic information in the digital twin scene are combined, and the host rotation speed, rudder angle value and the like of the ship are planned based on a motion control model of the ship body, so that the ship can navigate according to the planned route, the planned navigation speed and the like.
And carrying out multi-ship formation navigation on a visual digital twin platform, taking weather information, hydrologic information and the like into consideration, and taking the mutual influence among ships in the formation into consideration, comprehensively setting navigation parameters of each ship based on the formation positions of different ships, so as to ensure accurate navigation of the ships according to planned tracks and ensure that the overall formation is consistent with a preset scheme.
And (3) carrying out multi-disc on the sailing process, comprehensively comparing the actual track and the planned track of the ship, evaluating the sailing precision, analyzing an error result, taking the error between the planned track position and the actual track position as a punishment function, carrying out optimization iterative training on the ship body motion control model of the ship, and further improving the accuracy of the ship body motion control model.
Compared with the prior art, the invention has the advantages that:
The process visualization is realized by constructing a digital twin visualization platform, establishing a three-dimensional scene, putting in a twin hull three-dimensional model, constructing a motion control interface of the ship, and realizing the whole process visualization process of the three-dimensional scene;
The model is complicated, namely, the built ship motion model considers basic conventional ship power factors and structural factors, and also brings meteorological condition factors and hydrologic factors of a sailing water area into consideration of ship motion, and the motion control model of the ship is more vivid although the complexity of the model is improved;
The control model is iterated, namely a deep learning model pair is constructed and is iterated and trained, a more accurate ship body motion control model can be obtained through the iteration of the deep learning, and in the subsequent use process, the ship body motion control model can be iterated and optimized along with the continuous accumulation of actual navigation data, and the accuracy of the ship body motion control model can be optimized continuously;
The navigation process can be traced, namely, the ship navigates according to the planned track, relevant data in the actual navigation process are stored in a database, the navigation process can be duplicated in the later stage, the navigation precision is analyzed, and the search reasons are analyzed.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (9)
1. A hull navigation control method, comprising:
acquiring structural data and dynamic data of a ship body, and meteorological data and hydrological data in a ship body navigation environment;
Inputting all the acquired data into a trained ship body motion control model to obtain navigation control parameters of the ship body;
Performing navigation control on the ship body according to the navigation control parameters;
The ship motion control model is a deep learning model constructed by taking structural data and dynamic data of a ship, meteorological data and hydrological data in a ship navigation environment as independent variables and taking navigation control parameters of the ship as dependent variables.
2. The hull voyage control method of claim 1, wherein said structural data includes hull structural form, hull length, hull width and alignment characteristics, said power data includes power control data, rudder angle control data and hull weight, said meteorological data includes ambient wind speed, ambient wind direction and ambient temperature, and said hydrologic data includes sea state data, water depth, water flow rate and water flow direction;
The navigation control parameters comprise a host rotation speed and a rudder angle value.
3. The hull voyage control method according to claim 1, characterized in that said hull motion control model is trained by:
And acquiring the independent variable in the history time as a training parameter, converting the training parameter into a multidimensional array, then taking the multidimensional array as the input of the ship motion control model, and training the ship motion control model by taking the difference between the actual track and the planned track of the ship as a punishment function.
4. A hull voyage control method according to claim 3, wherein when said independent variable is updated, said updated independent variable is used as a new training parameter to retrain said hull motion control model.
5. The hull navigation control method according to claim 1, wherein the hull motion control model is of a full-connection structure and is provided with a plurality of full-connection layers, each full-connection layer is provided with a plurality of nodes, the number of output nodes is 2, and the 2 output nodes respectively correspond to the output host rotation speed and rudder angle value.
6. A hull navigation control device, comprising:
The data acquisition module is configured to acquire structural data and power data of the ship body, and weather data and hydrological data in a ship navigation environment;
the navigation control parameter calculation module is configured to input all acquired data into a trained ship motion control model to obtain navigation control parameters of the ship;
the navigation control module is configured to carry out navigation control on the ship body according to the navigation control parameters;
the ship motion control model is a deep learning model constructed by taking structural data and dynamic data of a ship, meteorological data and hydrological data in a ship navigation environment as independent variables and taking navigation control parameters of the ship as dependent variables.
7. A hull voyage control system comprising a visual digital twin platform, a data storage management unit and a hull voyage control unit for performing the method of any of claims 1 to 5;
the three-dimensional twin model of the ship body is built on the visual digital twin platform, a three-dimensional water area twin scene and a three-dimensional space twin scene are built, a motion control interface of the ship body is built, the three-dimensional twin model of the ship body is arranged in the three-dimensional water area twin scene, the three-dimensional water area twin scene is internally provided with the hydrological data to simulate the hydrological characteristics in the ship body navigation environment, and the three-dimensional space twin scene is internally provided with the meteorological data to simulate the meteorological characteristics in the ship body navigation environment;
The motion control interface comprises a first control interface influenced by the structural data, a second control interface influenced by the power data, a third control interface influenced by the meteorological data and a fourth control interface influenced by the hydrological data;
The data storage management unit is respectively connected with the visual digital twin platform and the ship navigation control unit and is used for storing structural data and power data of the ship, and meteorological data and hydrological data in a ship navigation environment;
And carrying out visual twin hull navigation control on a three-dimensional twin model of the hull in the three-dimensional water area twin scene through a first control interface, a second control interface, a third control interface and a fourth control interface, wherein navigation control parameters required in the process are obtained through the hull navigation control unit, carrying out navigation control on the hull in the real scene according to the result of the visual twin hull navigation control, and compensating for flight path errors generated in the visual twin hull navigation control process.
8. The hull voyage control system of claim 7, further comprising an external data acquisition device in communication with said visual digital twin platform, said visual digital twin platform capable of directly acquiring data from said external data acquisition device for construction of a three-dimensional twin scene.
9. The hull voyage control system of claim 7, wherein said three-dimensional twinning model of the hull is constructed using structural data and power data of the hull.
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