Intelligent correction method and system based on shipborne navigation meteorological parameters

Abstract

The embodiment of the invention relates to the technical field of ship navigation, and discloses an intelligent correction method based on shipborne navigation meteorological parameters, which comprises the following steps: acquiring meteorological sensing parameters and real-time oil consumption information of a ship in the sailing process detected by a shipborne monitoring unit arranged on the ship; and calculating to obtain a stall correction parameter of the ship according to a real-time wind speed parameter and a real-time wave height parameter in the meteorological sensing parameters, and updating a ship recommended route in the next stage according to the real-time oil consumption information of the ship and the stall correction parameter. According to the intelligent correction method based on the shipborne navigation meteorological parameters, the meteorological sensing parameters (such as the wind speed and the wave height) and the oil consumption information of the ship in the sailing process are obtained in real time through the shipborne monitoring unit, and the stall correction parameters of the ship can be calculated. Based on the real-time data, the recommended route of the next stage can be dynamically updated and optimized, and it is ensured that the ship can make an optimal navigation decision according to actual meteorological conditions and energy consumption conditions.

Description

Technical Field

[0001] The present invention relates to the field of ship navigation technology, and in particular to an intelligent correction method and system based on shipborne navigation meteorological parameters. Background Art

[0002] At present, meteorological navigation technology uses advanced computer models and algorithms to optimize ship navigation according to weather conditions. The technology analyzes meteorological data, ship specifications and performance characteristics to determine the most efficient and safest route, and takes into account factors such as fuel consumption, sailing time, ship stability and hazardous weather. Meteorological navigation technology is particularly suitable for long-distance voyages, which can improve the success rate, safety and cost-effectiveness of voyages. At present, there are many companies in the world that provide meteorological navigation services, and some common meteorological navigation software is available. China began to develop meteorological navigation in the early 1980s and established a marine meteorological navigation system in 1985, which has achieved huge economic benefits.

[0003] The basic problem of weather navigation is path planning, which can be solved using both exact and heuristic algorithms. Exact algorithms for path planning include Dijkstra's algorithm, A* algorithm, optimized queue algorithm, Bellman-Ford algorithm, and Floyd-Warshall algorithm. Heuristic algorithms include tabu search algorithm, simulated annealing algorithm, variable domain search algorithm, particle swarm algorithm, and ant colony algorithm. Compared with exact algorithms, heuristic algorithms can solve problems of larger scale and higher complexity.

[0004] In the process of meteorological navigation, the commonly used methods for selecting routes are variational method, isochrone method, dynamic programming method, network model and intelligent algorithm. Variational method is a method for solving the shortest sailing time route for ships, but its solution is complicated and the optimal solution is inaccurate, so it has not been widely used. Isochrone method is a simple and easy route selection method, which is often used to select the optimal initial route. Dynamic programming method is a recursive algorithm based on Bellman optimization principle. It has a large amount of calculation, but it is widely used under the high level of computer technology development. Network model is a shortest path planning method, which is often used for initial route selection in complex meteorological environments. Intelligent algorithm is a newer intelligent algorithm, which realizes global and general calculation method of route planning through multiple parameters and influencing factors, and its development is not yet mature.

[0005] Compared with road network navigation, the maturity of ship route planning algorithms is still relatively low and there is still a lot of room for development. Usually, weather navigation algorithms and services are mostly simple estimates, lacking advanced functions such as ship stall and fuel estimation. Therefore, designing a solution that can perform more accurate navigation has become a technical problem that technicians in this field need to solve urgently. Summary of the invention

[0006] In view of the above-mentioned defects, an embodiment of the present invention discloses an intelligent correction method based on shipborne navigation meteorological parameters, which can more realistically predict ship fuel consumption and provide more environmentally friendly navigation services.

[0007] The first aspect of the embodiment of the present invention discloses an intelligent correction method based on shipborne navigation meteorological parameters, comprising:

[0008] Obtaining ship navigation parameters, and determining the still water resistance parameters of the corresponding ship according to the ship width, ship draft, ship vertical length and ship air resistance coefficient in the ship navigation parameters; wherein the ship navigation parameters also include the ship starting point, ship destination, ship main engine output power, ship drive efficiency and main engine fuel consumption rate;

[0009] The corresponding ship effective power and main engine unit fuel consumption are calculated according to the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes:

[0010] P effective =η·P engine F engine =SFOC·P engine

[0011] Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the fuel consumption rate of the main engine;

[0012] Acquire sea condition forecast data of a target navigation area, and establish multiple meteorological grid areas according to the target navigation area according to a preset grid size, wherein each meteorological grid area corresponds to a meteorological forecast data; and determine the stall information of the ship in the corresponding meteorological grid area according to the meteorological forecast data, the hydrostatic resistance parameter of the ship, and the effective power of the ship;

[0013] Determine an initial ship recommended route for the corresponding ship according to the ship's starting point and ship's destination, the main engine's unit fuel consumption, the weather forecast data of each weather grid area in the target navigation area, the ship's stall information in the corresponding weather grid area, and the navigation path-finding algorithm in the ship's navigation parameters;

[0014] Acquire meteorological sensing parameters and real-time fuel consumption information of a ship during navigation detected by a ship-borne monitoring unit arranged on the ship, wherein the ship-borne monitoring unit comprises a wind speed and direction meter, a ship-borne wave radar and an oil flow meter; the meteorological sensing parameters comprise real-time wind speed parameters and real-time wave height parameters;

[0015] The stall correction parameter of the ship is calculated according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters, and the recommended route of the ship in the next stage is updated according to the real-time fuel consumption information of the ship and the stall correction parameter.

[0016] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the weather forecast data includes wind direction forecast data, wind speed forecast data and wave height forecast data;

[0017] The determining of the ship stall information in the corresponding meteorological grid area according to the meteorological forecast data, the hydrostatic resistance parameter of the ship and the effective power of the ship comprises:

[0018] Determine corresponding wind resistance data according to the wind direction forecast data, wind speed forecast data and a preset wind force-resistance mapping relationship;

[0019] Determine corresponding wave resistance data according to the wave height forecast data and a preset wave height-resistance mapping relationship;

[0020] Determine the corresponding total resistance of the ship according to the obtained wind resistance data, wave resistance data and still water resistance parameters of the ship;

[0021] The ship stall information in the corresponding meteorological grid area is determined according to the ship effective power, the ship's hydrostatic resistance parameter, the ship's total resistance and the stall calculation formula, and the stall calculation formula is:

[0022] V loss =V calm -V total =P effective (1 / R still -1 / R total )

[0023] Among them, R total is the total resistance of the ship, R still is the hydrostatic resistance parameter, V total is the total speed of the ship, P effective is the effective power of the ship, V still is the ship's still water speed, V loss The ship stalls.

[0024] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the weather forecast data also includes water flow data;

[0025] Determining the corresponding total resistance of the ship according to the obtained wind resistance data, wave resistance data and still water resistance parameters of the ship includes:

[0026] The corresponding total resistance of the ship is determined based on the obtained wind resistance data, wave resistance data, water resistance data and the still water resistance parameters of the ship.

[0027] As an optional implementation, in the first aspect of the embodiment of the present invention, the ship-borne monitoring unit further includes a speed log; the operation unit fuel consumption and the stall correction parameter of the ship are calculated according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensor parameters, including:

[0028] Determine corresponding real-time wind resistance data according to the real-time wind speed parameter in the meteorological sensing parameter and a preset wind force-resistance mapping relationship;

[0029] Determine corresponding real-time wave resistance data according to the real-time wave height parameter in the meteorological sensor parameter and a preset wave height-resistance mapping relationship;

[0030] Determine the real-time total resistance of the ship under the current sea condition according to the real-time wind resistance data, the real-time wave resistance data and the still water resistance parameter of the ship, and determine the experienced stall of the ship under the current sea condition according to the still water resistance parameter of the ship and the real-time total resistance of the ship;

[0031] The stall correction parameters are obtained by comparing the real-time ship speed measured by the speed log with the ship's experienced stall speed under current sea conditions.

[0032] As an optional implementation, in the first aspect of the embodiment of the present invention, the shipboard monitoring unit further includes a shaft power meter, and the shaft power meter is used to monitor the real-time output power of the main engine;

[0033] After acquiring the meteorological sensor parameters and real-time fuel consumption information of the ship during navigation detected by the ship-borne monitoring unit arranged on the ship, the method further includes:

[0034] Determine the real-time fuel consumption rate of the main engine according to the real-time output power of the main engine and the real-time fuel consumption information measured by the shaft power meter;

[0035] The real-time driving efficiency of the ship is determined according to the real-time effective power of the ship and the real-time output power of the main engine measured by the shaft power meter;

[0036] The main engine fuel consumption rate and the ship driving efficiency are updated according to the main engine real-time fuel consumption rate and the ship real-time driving efficiency.

[0037] As an optional implementation, in the first aspect of the embodiment of the present invention, the initial ship recommended route of the corresponding ship is determined according to the ship starting point and the ship destination, the unit fuel consumption of the main engine, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area, and the navigation path finding algorithm in the ship navigation parameters, including:

[0038] Taking the ship starting point in the ship navigation parameters as the starting node, taking the ship destination in the ship navigation parameters as the target node, and creating an open list to store the nodes to be explored and a closed list to store the nodes that have been explored;

[0039] Starting from the starting node, add it to the open list, and calculate the navigation cost and the heuristic function value according to the neighboring nodes of the starting node; the navigation cost includes the host unit fuel consumption, weather forecast data and ship stall data; the heuristic function value is calculated according to the pre-configured heuristic function;

[0040] Select the node with the lowest cost estimate as the current node, remove it from the open list, and add it to the closed list, repeating the above process until the target node is found or the open list is empty;

[0041] Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

[0042] A second aspect of an embodiment of the present invention discloses an intelligent correction system based on shipborne navigation meteorological parameters, comprising:

[0043] The first acquisition module is used to acquire the ship's navigation parameters, and determine the still water resistance parameters of the corresponding ship according to the ship's width, ship's draft, ship's vertical length and ship's air resistance coefficient in the ship's navigation parameters; wherein the ship's navigation parameters also include the ship's starting point, the ship's destination, the ship's main engine output power, the ship's driving efficiency and the main engine's fuel consumption rate;

[0044] The first calculation module is used to calculate the corresponding ship effective power and main engine unit fuel consumption according to the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes:

[0045] P effective =η·P engine F engine =SFOC·P engine

[0046] Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engineis the fuel consumption per unit time of the ship's main engine, and SFOC is the fuel consumption rate of the main engine;

[0047] The second acquisition module is used to acquire the sea condition forecast data of the target navigation area, and establish a plurality of meteorological grid areas according to the preset grid size according to the target navigation area, wherein each meteorological grid area corresponds to a meteorological forecast data; and determine the ship stall information in the corresponding meteorological grid area according to the meteorological forecast data and the effective power of the ship;

[0048] The route determination module is used to determine the initial recommended route of the corresponding ship according to the ship's starting point and destination, the main engine unit fuel consumption, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area, and the navigation path finding algorithm in the ship's navigation parameters;

[0049] Real-time acquisition module: used to acquire meteorological sensing parameters and real-time fuel consumption information of the ship during navigation detected by a ship-borne monitoring unit installed on the ship, wherein the ship-borne monitoring unit includes a wind speed and direction meter, a ship-borne wave radar and an oil flow meter; the meteorological sensing parameters include real-time wind speed parameters and real-time wave height parameters;

[0050] Route update module: used to calculate the stall correction parameter of the ship according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensor parameters, and update the recommended route of the ship in the next stage according to the real-time fuel consumption information of the ship and the stall correction parameter.

[0051] As an optional implementation, in the second aspect of the embodiment of the present invention, the initial ship recommended route of the corresponding ship is determined according to the ship starting point and ship destination, the unit fuel consumption of the main engine, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area, and the navigation path finding algorithm in the ship navigation parameters, including:

[0052] Taking the ship starting point in the ship navigation parameters as the starting node, taking the ship destination in the ship navigation parameters as the target node, and creating an open list to store the nodes to be explored and a closed list to store the nodes that have been explored;

[0053] Starting from the starting node, add it to the open list, and calculate the navigation cost and the heuristic function value according to the neighboring nodes of the starting node; the navigation cost includes the host unit fuel consumption, weather forecast data and ship stall data; the heuristic function value is calculated according to the pre-configured heuristic function;

[0054] Select the node with the lowest cost estimate as the current node, remove it from the open list, and add it to the closed list, repeating the above process until the target node is found or the open list is empty;

[0055] Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

[0056] The third aspect of an embodiment of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute an intelligent correction method based on ship-borne navigation meteorological parameters disclosed in the first aspect of the embodiment of the present invention.

[0057] A fourth aspect of an embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute an intelligent correction method based on shipborne navigation meteorological parameters disclosed in the first aspect of an embodiment of the present invention.

[0058] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0059] The intelligent correction method based on ship-borne navigation meteorological parameters in the embodiment of the present invention obtains the meteorological sensor parameters (such as wind speed, wave height) and fuel consumption information of the ship in real time during navigation through the ship-borne monitoring unit, and can calculate the stall correction parameters of the ship. Based on these real-time data, the recommended route for the next stage can be dynamically updated and optimized to ensure that the ship can make the best navigation decision according to the actual meteorological conditions and energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 It is a flow chart of an intelligent correction method based on shipborne navigation meteorological parameters disclosed in an embodiment of the present invention;

[0062] Figure 2 It is a schematic diagram of a process of calculating ship stall information disclosed in an embodiment of the present invention;

[0063] Figure 3 is a schematic diagram of a flow chart of calculating a recommended route disclosed in an embodiment of the present invention;

[0064] Figure 4is a schematic diagram of a navigation pathfinding algorithm disclosed in an embodiment of the present invention;

[0065] Figure 5 It is a display schematic diagram of the airworthy area division disclosed in an embodiment of the present invention;

[0066] Figure 6 It is a structural schematic diagram of an intelligent correction system based on shipborne navigation meteorological parameters provided by an embodiment of the present invention;

[0067] Figure 7 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] It should be noted that the terms "first", "second", "third", "fourth", etc. in the specification and claims of the present invention are used to distinguish different objects rather than to describe a specific order. The terms "including" and "having" in the embodiments of the present invention and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0070] Compared with road network navigation, the maturity of ship route planning algorithms is still relatively low, and there is still a lot of room for development. Usually, meteorological navigation algorithms and services are mostly simple estimates, lacking advanced functions such as ship stall and fuel estimation. Based on this, the embodiment of the present invention discloses an intelligent correction method, system, electronic device and storage medium based on shipborne navigation meteorological parameters, which can obtain the meteorological sensor parameters (such as wind speed, wave height) and fuel consumption information of the ship in real time during navigation through the shipborne monitoring unit, and can calculate the stall correction parameters of the ship. Based on these real-time data, the recommended routes for the next stage can be dynamically updated and optimized to ensure that the ship can make the best navigation decisions based on actual meteorological conditions and energy consumption.

[0071] Embodiment 1

[0072] See also Figure 1 , Figure 1It is a flow chart of an intelligent correction method based on shipborne navigation meteorological parameters disclosed in an embodiment of the present invention. Among them, the execution subject of the method described in the embodiment of the present invention is an execution subject composed of software and / or hardware, and the execution subject can receive relevant information by wired or / and wireless means, and can send certain instructions. Of course, it can also have certain processing functions and storage functions. The execution subject can control multiple devices, such as a remote physical server or cloud server and related software, or it can be a local host or server and related software that performs related operations on a device placed somewhere. In some scenarios, multiple storage devices can also be controlled, and the storage devices can be placed in the same place or different places as the devices. For example Figure 1 As shown, the intelligent correction method based on shipborne navigation meteorological parameters includes the following steps:

[0073] S101: Obtaining ship navigation parameters, and determining the still water resistance parameters of the corresponding ship according to the ship width, ship draft, ship vertical length and ship air resistance coefficient in the ship navigation parameters; wherein the ship navigation parameters also include the ship starting point, ship destination, ship main engine output power, ship driving efficiency and main engine fuel consumption rate;

[0074] S102: Calculate the corresponding ship effective power and main engine unit fuel consumption according to the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes:

[0075] P effective =η·P engine F engine =SFOC·P engine

[0076] Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the fuel consumption rate of the main engine;

[0077] S103: Acquire sea condition forecast data of the target navigation area, and establish multiple meteorological grid areas according to the target navigation area according to a preset grid size, wherein each meteorological grid area corresponds to a meteorological forecast data; and determine the stall information of the ship in the corresponding meteorological grid area according to the meteorological forecast data, the hydrostatic resistance parameter of the ship, and the effective power of the ship;

[0078] S104: determining an initial ship recommended route for the corresponding ship according to the ship's starting point and ship's destination, the main engine's unit fuel consumption, the weather forecast data of each meteorological grid area in the target navigation area, the ship's stall information in the corresponding meteorological grid area, and the navigation path-finding algorithm in the ship's navigation parameters;

[0079] S105: Acquire meteorological sensing parameters and real-time fuel consumption information of the ship during navigation detected by a ship-borne monitoring unit arranged on the ship, wherein the ship-borne monitoring unit includes a wind speed and direction meter, a ship-borne wave radar and an oil flow meter; the meteorological sensing parameters include real-time wind speed parameters and real-time wave height parameters;

[0080] S106: Calculate the stall correction parameter of the ship according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters, and update the recommended route of the ship in the next stage according to the real-time fuel consumption information of the ship and the stall correction parameter.

[0081] The solution of the embodiment of the present invention can accurately determine the still water resistance parameters of the ship by obtaining the ship's navigation parameters, such as the ship's width, draft, length between verticals, and air resistance coefficient, etc. This helps to more accurately evaluate the performance of the ship under different conditions and provides a basis for subsequent route planning and stall correction.

[0082] By using the main engine transmission efficiency and fuel consumption rate, combined with the preset efficiency calculation formula, the effective power and specific fuel consumption of the ship can be calculated. This helps ship owners or operators better understand the energy consumption of the ship and take measures to optimize the fuel efficiency of the ship. By obtaining the sea condition forecast data of the target navigation area and dividing the area into multiple meteorological grid areas, each area corresponds to a meteorological forecast data. This enables a more accurate assessment of the impact of different meteorological conditions on the navigation of the ship, including stalling. This helps to plan routes in advance, avoid bad weather, and reduce navigation risks.

[0083] The solution of the embodiment of the present invention combines the ship's starting point, destination, main engine unit fuel consumption, weather forecast data and stall information, and uses a navigation path-finding algorithm to intelligently plan an initial recommended route. This can not only improve navigation efficiency, but also ensure that the ship reduces energy consumption and stalls as much as possible during navigation.

[0084] More preferably, the weather forecast data includes wind direction forecast data, wind speed forecast data and wave height forecast data;

[0085] like Figure 2 As shown, the ship stall information in the corresponding meteorological grid area is determined according to the meteorological forecast data, the hydrostatic resistance parameter of the ship and the effective power of the ship, including:

[0086] S1021: determining corresponding wind resistance data according to the wind direction forecast data, the wind speed forecast data and a preset wind force-resistance mapping relationship;

[0087] S1022: Determine corresponding wave resistance data according to the wave height forecast data and a preset wave height-resistance mapping relationship;

[0088] S1023: determining a corresponding total resistance of the ship according to the obtained wind resistance data, wave resistance data and still water resistance parameters of the ship;

[0089] S1024: Determine the ship stall information in the corresponding meteorological grid area according to the ship effective power, the ship's hydrostatic resistance parameter, the ship's total resistance, and a stall calculation formula, wherein the stall calculation formula is:

[0090] V loss =V calm -V total =P effective (1 / R still -1 / R total )

[0091] Among them, R total is the total resistance of the ship, R still is the hydrostatic resistance parameter, V total is the total speed of the ship, P effective is the effective power of the ship, V still is the ship's still water speed, V loss The ship stalls.

[0092] The solution of the embodiment of the present invention introduces wind direction forecast data, wind speed forecast data and wave height forecast data, and the technology can more comprehensively consider the impact of meteorological factors on ship navigation. This refined use of meteorological data makes the prediction of ship stall more accurate, which helps shipping companies to better plan routes and adjust speeds, thereby improving transportation efficiency while ensuring safety.

[0093] The method of determining wind resistance data and wave resistance data according to the wind force-resistance mapping relationship and the wave height-resistance mapping relationship mentioned in the embodiment of the present invention is a method for dynamically calculating resistance. This method can reflect the impact of changes in meteorological conditions on ship resistance in real time, so that the ship can adjust the navigation strategy according to the actual situation and reduce unnecessary energy consumption. By combining the wind resistance data, wave resistance data and the hydrostatic resistance parameters of the ship, the total resistance of the ship is calculated, and then further combined with the ship's effective power and stall calculation formula, the stall information of the ship under different meteorological conditions can be obtained. This comprehensive evaluation method can more comprehensively reflect the performance of the ship under different environments and provide strong support for the navigation safety and efficiency of the ship. Accurate ship stall prediction helps shipping companies understand the navigation performance of ships under different meteorological conditions in advance, so as to take corresponding measures to avoid potential safety risks. For example, in severe weather conditions, companies can adjust routes or reduce speed to ensure the safety of ships and cargo.

[0094] Specifically, in actual navigation, the ship's speed and fuel consumption are related to many factors, such as: ship's still water speed, ship width, ship draft, length between verticals, air resistance coefficient, ship's total resistance coefficient, main engine transmission efficiency, main engine fuel consumption rate, etc. The following relationship exists between ship resistance, ship effective power and ship stall:

[0095] R total =R wind +R wave +R still R total ·V total =P effective =R still ·V still

[0096] V loss =V calm -V total =P effective (1 / R still -1 / R total )

[0097] Among them, R total is the total resistance of the ship, R wind is wind resistance, R wave is wave resistance, R still is the hydrostatic resistance, V total is the total speed of the ship, P effective is the effective power of the ship, V still is the ship's still water speed, V loss The ship stalls.

[0098] Normally, after the ship's route is determined, it will not be frequently maneuvered, and the ship is at the most economical speed, that is, the ship's main engine speed is at the most efficient state. The effective power of the ship and the main engine fuel consumption have the following relationship: P effective =η·P engine , F engine =SFOC·P engine

[0099] Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the main engine fuel consumption rate.

[0100] More preferably, the weather forecast data also includes water flow data;

[0101] Determining the corresponding total resistance of the ship according to the obtained wind resistance data, wave resistance data and still water resistance parameters of the ship includes:

[0102] The corresponding total resistance of the ship is determined based on the obtained wind resistance data, wave resistance data, water resistance data and the still water resistance parameters of the ship.

[0103] By introducing water flow data, the present invention can more comprehensively consider the resistance faced by ships during navigation. Wind resistance, wave resistance and water resistance are the main components of ship navigation resistance. Taking them all into consideration can more accurately calculate the total resistance of the ship, thereby more accurately predicting the navigation performance and fuel consumption of the ship.

[0104] More preferably, the ship-borne monitoring unit further includes a speed log; the operation unit fuel consumption and stall correction parameter of the ship are calculated according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters, including:

[0105] Determine corresponding real-time wind resistance data according to the real-time wind speed parameter in the meteorological sensing parameter and a preset wind force-resistance mapping relationship;

[0106] Determine corresponding real-time wave resistance data according to the real-time wave height parameter in the meteorological sensor parameter and a preset wave height-resistance mapping relationship;

[0107] Determine the real-time total resistance of the ship under the current sea condition according to the real-time wind resistance data, the real-time wave resistance data and the still water resistance parameter of the ship, and determine the experienced stall of the ship under the current sea condition according to the still water resistance parameter of the ship and the real-time total resistance of the ship;

[0108] The stall correction parameters are obtained by comparing the real-time ship speed measured by the speed log with the ship's experienced stall speed under current sea conditions.

[0109] The embodiment of the present invention introduces a speedometer, which can monitor the ship's sailing speed in real time and compare it with the ship's empirical stall calculated based on meteorological sensor parameters (real-time wind speed, real-time wave height) and resistance mapping relationship, thereby obtaining stall correction parameters. This real-time monitoring and dynamic adjustment method enables the ship to quickly respond to changes in sea conditions, optimize navigation strategies, and improve navigation efficiency and safety.

[0110] The real-time wind resistance data and real-time wave resistance data are calculated by combining the meteorological sensor parameters (real-time wind speed, real-time wave height) with the resistance mapping relationship, and then the real-time total resistance of the ship is determined. This method can more accurately reflect the stall situation of the ship under the current sea conditions. Compared with static meteorological forecast data, real-time sensor data can reflect changes in sea conditions more timely, thereby improving the accuracy of stall prediction.

[0111] More preferably, the ship-borne monitoring unit further comprises a shaft power meter, and the shaft power meter is used to monitor the real-time output power of the main engine;

[0112] After acquiring the meteorological sensor parameters and real-time fuel consumption information of the ship during navigation detected by the ship-borne monitoring unit arranged on the ship, the method further includes:

[0113] Determine the real-time fuel consumption rate of the main engine according to the real-time output power of the main engine and the real-time fuel consumption information measured by the shaft power meter;

[0114] The real-time driving efficiency of the ship is determined according to the real-time effective power of the ship and the real-time output power of the main engine measured by the shaft power meter;

[0115] The main engine fuel consumption rate and the ship driving efficiency are updated according to the main engine real-time fuel consumption rate and the ship real-time driving efficiency.

[0116] The embodiment of the present invention introduces a shaft power meter, which can monitor the output power of the main engine in real time and calculate the real-time fuel consumption rate of the main engine in combination with the real-time fuel consumption information. This helps shipping companies to accurately understand the energy consumption of the main engine and take corresponding measures to optimize the fuel efficiency of the main engine. At the same time, by calculating the ratio of the real-time effective power of the ship to the real-time output power of the main engine, the real-time driving efficiency of the ship can be obtained, which provides an important basis for evaluating and optimizing the performance of the ship.

[0117] Traditional ship performance evaluation often relies on static data and empirical formulas, which are difficult to accurately reflect the actual situation of the ship during navigation. This technology can more accurately reflect the energy consumption and performance of the ship by real-time monitoring of the main engine's output power and fuel consumption information, as well as calculating the real-time fuel consumption rate and driving efficiency, thereby improving the accuracy and reliability of the data. After obtaining real-time meteorological sensor parameters, fuel consumption information and main engine performance data, shipping companies can dynamically adjust navigation strategies based on these data, such as adjusting speed, changing routes or taking energy-saving measures, in order to optimize navigation efficiency and reduce operating costs. This dynamic adjustment capability helps shipping companies maintain their competitive advantage in a highly competitive market environment.

[0118] By monitoring the output power and fuel consumption of the main engine in real time, the technology can also help shipping companies to promptly detect potential failures or performance degradation of the main engine. By comparing and analyzing historical data and real-time data, the maintenance needs of the main engine can be predicted, so that measures can be taken in advance to prevent failures and improve the reliability and service life of the main engine.

[0119] Specifically, due to differences in loading conditions, the impact of the marine environment, the complexity of the power and propulsion systems, fuel quality and efficiency, nonlinear relationships, data availability and accuracy, etc., the actual calculation of ship fuel consumption and stall is very complex and has certain differences from empirical results. The effective power and fuel consumption rate of the ship calculated using the previous relationship can be further corrected, and the correction depends on the actual measured data of the ship. The entire monitoring and analysis system consists of data measuring instruments, data transmission equipment, and data processing and analysis equipment. The speed meter measures the ship's speed, the oil flow meter measures the fuel consumption of the ship's main engine, the shaft power meter measures the output power of the ship's main engine, the ship-borne wave radar measures the wave parameters, the wind speed and direction meter measures the wind speed and direction, GPS and AIS assist in determining the ship's position and status, and the ship-borne analysis terminal processes and analyzes the obtained data.

[0120] When a ship is sailing at the economic speed of the main engine in a wide waterway with relatively calm wind and waves, and the ship's hydrostatic resistance is known, the ship's driving efficiency η and the main engine fuel consumption rate SFOC can be corrected by measuring the ship's speed, the ship's main engine fuel consumption, and the ship's main engine output power. The fuel consumption changes caused by crew operations and other human factors are not within the correction range.

[0121] Compared with fuel consumption correction, the ship's stall calculation involves more indirect parameters, including the ship's still water speed, ship width, ship draft, vertical length, air resistance coefficient, ship total resistance coefficient, main engine transmission efficiency, main engine fuel consumption rate, etc. The correction method is relatively complicated. The main steps are:

[0122] a. Based on the wind speed measured by the wind speed and direction instrument, the wave height measured by the ship-borne wave radar, and the ship's empirical wind resistance and wave resistance data, the total resistance of the ship in the current sea conditions is obtained according to Formula 1.

[0123] b. The empirical stall speed of the ship under the current sea conditions is calculated according to Formula 3 based on the total resistance under the current sea conditions, the known still water speed of the ship, the still water resistance, and the effective power of the main engine.

[0124] c. The stall correction parameters are obtained by comparing the ship's empirical stall speed with the ship's speed measured by the speedometer.

[0125] More preferably, Figure 3-Figure 5 As shown, the initial ship recommended route of the corresponding ship is determined according to the ship starting point and the ship destination, the unit fuel consumption of the main engine, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area, and the navigation path finding algorithm, including:

[0126] S1041: taking the ship starting point in the ship navigation parameters as the starting node, taking the ship destination in the ship navigation parameters as the target node, and creating an open list to store the nodes to be explored and a closed list to store the explored nodes;

[0127] S1042: Starting from the starting node, add it to the open list, and calculate the navigation cost and the heuristic function value according to the neighboring nodes of the starting node; the navigation cost includes the unit fuel consumption of the host, the weather forecast data and the ship stall data; the heuristic function value is calculated according to the pre-configured heuristic function;

[0128] S1043: Select the node with the lowest cost estimate as the current node, remove it from the open list, and add it to the closed list, repeating the above process until the target node is found or the open list is empty;

[0129] S1044: Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

[0130] In specific implementation, a variety of algorithms can be used as navigation pathfinding algorithms. Here, the A* algorithm is used as an example to illustrate the role of pathfinding algorithms in the correction of meteorological navigation algorithm parameters. The A* algorithm is quite flexible and can be used in various scenarios. It combines the advantages of the Dijkstra algorithm and the Best First Search algorithm, and can search for the lowest cost path with a smaller computational cost. The A* algorithm adds a heuristic function to the Dijkstra algorithm, which is faster for a single target and can consider the movement cost under different sea conditions.

[0131] The A* algorithm based on orthogonal grids often has four or eight directions, and more search directions can also be used to construct the A* pathfinding algorithm. More search directions provide higher route direction resolution and reduce large-angle turns in the route. The longitude and latitude coordinate grid is used to divide the global sea area into grid points to distinguish between navigable areas and non-navigable areas, and the A* algorithm heuristic function is written based on the spherical great circle distance. In the embodiment of the present invention, a four-way or eight-way search method can be used.

[0132] The specific implementation steps of the A* algorithm are:

[0133] First, define nodes and edges. Nodes: represent key points on the route, such as the starting point, the destination point, the intersection of the weather grid, etc. Each node should contain its location information (latitude and longitude), the cost to reach the node (such as fuel consumption), the heuristic function value (such as the estimated distance to the destination point), and a pointer to the parent node (for backtracking). Edges: Line segments or curve segments connecting two nodes, representing possible navigation paths. Each edge should contain the cost from the starting node to the end node (such as fuel consumption, time, etc.).

[0134] Second, initialization, create an open list (Open List) to store the nodes to be explored. Create a closed list (Closed List) to store the nodes that have been explored. Add the start node to the open list and set its cost to 0. The heuristic function value is the estimated distance to the target node (which can be calculated using the spherical great circle distance).

[0135] Third, the search process, loop: until the open list is empty or the target node is found. Select the node with the lowest cost plus the heuristic function value (f=g+h, where g is the actual cost from the starting node to the current node, and h is the estimated cost from the current node to the target node) from the open list as the current node. Remove the current node from the open list and add it to the closed list. For each neighbor node of the current node (i.e., the possible next route point): if the neighbor node is in the closed list, skip it. If the neighbor node is not in the open list, add it to the open list and set its parent node to the current node. Calculate the actual cost from the starting node to the neighbor node (g'=g+cost), where cost is the cost from the current node to the neighbor node. If the neighbor node is already in the open list, but the new path cost is lower, update its cost, heuristic function value, and parent node.

[0136] Fourth, path generation, once the target node is found, the final path is generated by backtracking the parent node pointer from the target node to the starting node. These nodes are connected in sequence to form the final recommended route.

[0137] Fifth, heuristic function, the heuristic function h(n) is used to estimate the cost of the minimum cost path from the current node n to the target node. In ship route planning, the spherical great circle distance can be used as a heuristic function because it provides an estimate of the shortest distance between two points on the sphere.

[0138] Sixth, weather conditions are considered. In actual implementation, weather conditions (such as wind speed, wind direction, wave height, etc.) can be used as part of the edge cost. According to weather forecast data, the edge cost is dynamically adjusted to reflect the navigation difficulty and fuel consumption under different weather conditions.

[0139] When implementing the algorithm, a priority queue (such as a minimum heap) can be used to implement the open list to speed up the node selection process. Various optimization techniques can be used, such as pruning of the A* algorithm, dynamically adjusting the heuristic function, etc., to improve the performance and accuracy of the algorithm.

[0140] The intelligent correction method based on ship-borne navigation meteorological parameters in the embodiment of the present invention obtains the meteorological sensor parameters (such as wind speed, wave height) and fuel consumption information of the ship in real time during navigation through the ship-borne monitoring unit, and can calculate the stall correction parameters of the ship. Based on these real-time data, the recommended route for the next stage can be dynamically updated and optimized to ensure that the ship can make the best navigation decision according to the actual meteorological conditions and energy consumption.

[0141] Embodiment 2

[0142] See also Figure 6 , Figure 6 FIG. 1 is a schematic diagram of the structure of an intelligent correction system based on shipborne navigation meteorological parameters disclosed in an embodiment of the present invention. Figure 6 As shown, the intelligent correction system based on shipborne navigation meteorological parameters may include:

[0143] The first acquisition module is used to acquire the ship's navigation parameters, and determine the still water resistance parameters of the corresponding ship according to the ship's width, ship's draft, ship's vertical length and ship's air resistance coefficient in the ship's navigation parameters; wherein the ship's navigation parameters also include the ship's starting point, the ship's destination, the ship's main engine output power, the ship's driving efficiency and the main engine's fuel consumption rate;

[0144] The first calculation module is used to calculate the corresponding ship effective power and main engine unit fuel consumption according to the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes:

[0145] P effective =η·P engine F engine =SFOC·P engine

[0146] Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the fuel consumption rate of the main engine;

[0147] The second acquisition module is used to acquire the sea condition forecast data of the target navigation area, and establish a plurality of meteorological grid areas according to the preset grid size according to the target navigation area, wherein each meteorological grid area corresponds to a meteorological forecast data; and determine the ship stall information in the corresponding meteorological grid area according to the meteorological forecast data and the effective power of the ship;

[0148] The route determination module is used to determine the initial recommended route of the corresponding ship according to the ship's starting point and destination, the main engine unit fuel consumption, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area, and the navigation path finding algorithm in the ship's navigation parameters;

[0149] Real-time acquisition module: used to acquire meteorological sensing parameters and real-time fuel consumption information of the ship during navigation detected by a ship-borne monitoring unit installed on the ship, wherein the ship-borne monitoring unit includes a wind speed and direction meter, a ship-borne wave radar and an oil flow meter; the meteorological sensing parameters include real-time wind speed parameters and real-time wave height parameters;

[0150] Route update module: used to calculate the stall correction parameter of the ship according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensor parameters, and update the recommended route of the ship in the next stage according to the real-time fuel consumption information of the ship and the stall correction parameter.

[0151] More preferably, the determining of the initial recommended ship route of the corresponding ship according to the ship starting point and the ship destination, the unit fuel consumption of the main engine, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area and the navigation path finding algorithm in the ship navigation parameters includes:

[0152] Taking the ship starting point in the ship navigation parameters as the starting node, taking the ship destination in the ship navigation parameters as the target node, and creating an open list to store the nodes to be explored and a closed list to store the nodes that have been explored;

[0153] Starting from the starting node, add it to the open list, and calculate the navigation cost and the heuristic function value according to the neighboring nodes of the starting node; the navigation cost includes the host unit fuel consumption, weather forecast data and ship stall data; the heuristic function value is calculated according to the pre-configured heuristic function;

[0154] Select the node with the lowest cost estimate as the current node, remove it from the open list, and add it to the closed list, repeating the above process until the target node is found or the open list is empty;

[0155] Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

[0156] The intelligent correction method based on ship-borne navigation meteorological parameters in the embodiment of the present invention obtains the meteorological sensor parameters (such as wind speed, wave height) and fuel consumption information of the ship in real time during navigation through the ship-borne monitoring unit, and can calculate the stall correction parameters of the ship. Based on these real-time data, the recommended route for the next stage can be dynamically updated and optimized to ensure that the ship can make the best navigation decision according to the actual meteorological conditions and energy consumption.

[0157] Embodiment 3

[0158] See also Figure 7 , Figure 7 Schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device may be a computer, a server, etc. Of course, in certain circumstances, it may also be a smart device such as a mobile phone, a tablet computer, a monitoring terminal, and an image acquisition device with processing functions. Figure 7 As shown, the electronic device may include:

[0159] A memory 510 storing executable program codes;

[0160] a processor 520 coupled to the memory 510;

[0161] The processor 520 calls the executable program code stored in the memory 510 to execute part or all of the steps in the intelligent correction method based on shipborne navigation meteorological parameters in the first embodiment.

[0162] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute part or all of the steps in an intelligent correction method based on shipborne navigation meteorological parameters in embodiment one.

[0163] The embodiment of the present invention further discloses a computer program product, wherein when the computer program product is run on a computer, the computer is enabled to execute part or all of the steps in the intelligent correction method based on shipborne navigation meteorological parameters in the first embodiment.

[0164] An embodiment of the present invention also discloses an application publishing platform, wherein the application publishing platform is used to publish a computer program product, wherein when the computer program product runs on a computer, the computer executes part or all of the steps in an intelligent correction method based on shipborne navigation meteorological parameters in embodiment one.

[0165] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0166] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0167] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0168] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several requests for a computer device (which can be a personal computer, a server or a network device, etc., specifically a processor in a computer device) to perform some or all of the steps of the method described in each embodiment of the present invention.

[0169] In the embodiments provided by the present invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0170] A person of ordinary skill in the art can understand that some or all of the steps in the various methods of the embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0171] The above is a detailed introduction to an intelligent correction method, system, electronic device and storage medium based on shipborne navigation meteorological parameters disclosed in an embodiment of the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An intelligent correction method based on shipborne navigation meteorological parameters, characterized in that: include: Obtaining ship navigation parameters, and determining the still water resistance parameters of the corresponding ship according to the ship width, ship draft, ship vertical length and ship air resistance coefficient in the ship navigation parameters; wherein the ship navigation parameters also include the ship starting point, ship destination, ship main engine output power, ship drive efficiency and main engine fuel consumption rate; The corresponding ship effective power and main engine unit fuel consumption are calculated according to the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes: P effective =η·P engine F engine =SFOC·P engine Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the fuel consumption rate of the main engine; Acquire sea condition forecast data of a target navigation area, and establish multiple meteorological grid areas according to the target navigation area according to a preset grid size, wherein each meteorological grid area corresponds to a meteorological forecast data; and determine the stall information of the ship in the corresponding meteorological grid area according to the meteorological forecast data, the hydrostatic resistance parameter of the ship, and the effective power of the ship; Determine an initial ship recommended route for the corresponding ship according to the ship's starting point and ship's destination, the main engine's unit fuel consumption, the weather forecast data of each weather grid area in the target navigation area, the ship's stall information in the corresponding weather grid area, and the navigation path-finding algorithm in the ship's navigation parameters; Acquire meteorological sensing parameters and real-time fuel consumption information of a ship during navigation detected by a ship-borne monitoring unit arranged on the ship, wherein the ship-borne monitoring unit comprises a wind speed and direction meter, a ship-borne wave radar and an oil flow meter; the meteorological sensing parameters comprise real-time wind speed parameters and real-time wave height parameters; The stall correction parameter of the ship is calculated according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters, and the recommended route of the ship in the next stage is updated according to the real-time fuel consumption information of the ship and the stall correction parameter.

2. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 1, characterized in that: The weather forecast data includes wind direction forecast data, wind speed forecast data and wave height forecast data; The determining of the ship stall information in the corresponding meteorological grid area according to the meteorological forecast data, the hydrostatic resistance parameter of the ship and the effective power of the ship comprises: Determine corresponding wind resistance data according to the wind direction forecast data, wind speed forecast data and a preset wind force-resistance mapping relationship; Determine corresponding wave resistance data according to the wave height forecast data and a preset wave height-resistance mapping relationship; Determine the corresponding total resistance of the ship according to the obtained wind resistance data, wave resistance data and still water resistance parameters of the ship; The ship stall information in the corresponding meteorological grid area is determined according to the ship effective power, the ship's hydrostatic resistance parameter, the ship's total resistance and the stall calculation formula, and the stall calculation formula is: V loss =V calm -V total =P effective (1 / R still -1 / R total ) Among them, R total is the total resistance of the ship, R still is the hydrostatic resistance parameter, V total is the total speed of the ship, P effective is the effective power of the ship, V still is the ship's still water speed, V loss The ship stalls.

3. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 2, characterized in that: The weather forecast data also includes water flow data; Determining the corresponding total resistance of the ship according to the obtained wind resistance data, wave resistance data and still water resistance parameters of the ship includes: The corresponding total resistance of the ship is determined based on the obtained wind resistance data, wave resistance data, water resistance data and the still water resistance parameters of the ship.

4. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 2, characterized in that: The ship-borne monitoring unit also includes a speedometer; the operation unit fuel consumption and stall correction parameters of the ship are calculated according to the real-time wind speed parameters and real-time wave height parameters in the meteorological sensor parameters, including: Determine corresponding real-time wind resistance data according to the real-time wind speed parameter in the meteorological sensing parameter and a preset wind force-resistance mapping relationship; Determine corresponding real-time wave resistance data according to the real-time wave height parameter in the meteorological sensor parameter and a preset wave height-resistance mapping relationship; Determine the real-time total resistance of the ship under the current sea condition according to the real-time wind resistance data, the real-time wave resistance data and the still water resistance parameter of the ship, and determine the experienced stall of the ship under the current sea condition according to the still water resistance parameter of the ship and the real-time total resistance of the ship; The stall correction parameters are obtained by comparing the real-time ship speed measured by the speed log with the ship's experienced stall speed under current sea conditions.

5. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 4, characterized in that: The ship-borne monitoring unit also includes a shaft power meter, which is used to monitor the real-time output power of the main engine; After acquiring the meteorological sensor parameters and real-time fuel consumption information of the ship during navigation detected by the ship-borne monitoring unit arranged on the ship, the method further includes: Determine the real-time fuel consumption rate of the main engine according to the real-time output power of the main engine and the real-time fuel consumption information measured by the shaft power meter; The real-time driving efficiency of the ship is determined according to the real-time effective power of the ship and the real-time output power of the main engine measured by the shaft power meter; The main engine fuel consumption rate and the ship driving efficiency are updated according to the main engine real-time fuel consumption rate and the ship real-time driving efficiency.

6. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 4, characterized in that: The initial recommended ship route of the corresponding ship is determined according to the ship's starting point and ship's destination, the main engine's unit fuel consumption, the weather forecast data of each meteorological grid area in the target navigation area, the ship's stall information in the corresponding meteorological grid area, and the navigation path finding algorithm, including: Taking the ship starting point in the ship navigation parameters as the starting node, taking the ship destination in the ship navigation parameters as the target node, and creating an open list to store the nodes to be explored and a closed list to store the nodes that have been explored; Starting from the starting node, add it to the open list, and calculate the navigation cost and the heuristic function value according to the neighboring nodes of the starting node; the navigation cost includes the host unit fuel consumption, weather forecast data and ship stall data; the heuristic function value is calculated according to the pre-configured heuristic function; Select the node with the lowest cost estimate as the current node, remove it from the open list, and add it to the closed list, repeating the above process until the target node is found or the open list is empty; Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

7. An intelligent correction system based on shipborne navigation meteorological parameters, characterized in that: include: The first acquisition module is used to acquire the ship's navigation parameters, and determine the still water resistance parameters of the corresponding ship according to the ship's width, ship's draft, ship's vertical length and ship's air resistance coefficient in the ship's navigation parameters; wherein the ship's navigation parameters also include the ship's starting point, the ship's destination, the ship's main engine output power, the ship's driving efficiency and the main engine's fuel consumption rate; The first calculation module is used to calculate the corresponding ship effective power and main engine unit fuel consumption according to the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes: P effective =η·P engine F engine =SFOC·P engine Among them, P effective is the effective power of the ship, η is the ship driving efficiency, P engine is the output power of the ship’s main engine, F engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the fuel consumption rate of the main engine; The second acquisition module is used to acquire the sea condition forecast data of the target navigation area, and establish a plurality of meteorological grid areas according to the preset grid size according to the target navigation area, wherein each meteorological grid area corresponds to a meteorological forecast data; and determine the ship stall information in the corresponding meteorological grid area according to the meteorological forecast data and the effective power of the ship; The route determination module is used to determine the initial recommended route of the corresponding ship according to the ship's starting point and destination, the main engine unit fuel consumption, the weather forecast data of each meteorological grid area in the target navigation area, the ship stall information in the corresponding meteorological grid area, and the navigation path finding algorithm in the ship's navigation parameters; Real-time acquisition module: used to acquire meteorological sensing parameters and real-time fuel consumption information of the ship during navigation detected by a ship-borne monitoring unit installed on the ship, wherein the ship-borne monitoring unit includes a wind speed and direction meter, a ship-borne wave radar and an oil flow meter; the meteorological sensing parameters include real-time wind speed parameters and real-time wave height parameters; Route update module: used to calculate the stall correction parameter of the ship according to the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensor parameters, and update the recommended route of the ship in the next stage according to the real-time fuel consumption information of the ship and the stall correction parameter.

8. The intelligent correction system based on shipborne navigation meteorological parameters as claimed in claim 7, characterized in that: The initial recommended ship route of the corresponding ship is determined according to the ship's starting point and ship's destination, the main engine's unit fuel consumption, the weather forecast data of each meteorological grid area in the target navigation area, the ship's stall information in the corresponding meteorological grid area, and the navigation path finding algorithm, including: Taking the ship starting point in the ship navigation parameters as the starting node, taking the ship destination in the ship navigation parameters as the target node, and creating an open list to store the nodes to be explored and a closed list to store the nodes that have been explored; Starting from the starting node, add it to the open list, and calculate the navigation cost and the heuristic function value according to the neighboring nodes of the starting node; the navigation cost includes the host unit fuel consumption, weather forecast data and ship stall data; the heuristic function value is calculated according to the pre-configured heuristic function; Select the node with the lowest cost estimate as the current node, remove it from the open list, and add it to the closed list, repeating the above process until the target node is found or the open list is empty; Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

9. An electronic device, characterized in that: include: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent correction method based on shipborne navigation meteorological parameters as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the intelligent correction method based on shipborne navigation meteorological parameters as described in any one of claims 1 to 6.

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