An intelligent correction method and system based on shipborne navigation meteorological parameters

Abstract

The embodiment of the application 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 of a ship in a navigation process and real-time fuel consumption information detected by a shipborne monitoring unit arranged on the ship; calculating a stall correction parameter of the ship according to real-time wind speed parameters and real-time wave height parameters in the meteorological sensing parameters, and updating a recommended route of the ship in the next stage according to real-time fuel consumption information of the ship and the stall correction parameter. In the embodiment of the application, the intelligent correction method based on shipborne navigation meteorological parameters can acquire meteorological sensing parameters (such as wind speed and wave height) and fuel consumption information of the ship in the navigation process in real time through the shipborne monitoring unit, and can calculate the stall correction parameter of the ship. Based on the real-time data, the recommended route in the next stage can be dynamically updated and optimized, so that the ship can make the best navigation decision according to actual meteorological conditions and energy consumption.

Description

Technical Field

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

[0002] Currently, weather navigation technology utilizes advanced computer models and algorithms to optimize ship navigation based on weather conditions. This technology analyzes meteorological data, vessel specifications, and performance characteristics to determine the most efficient and safest routes, taking into account factors such as fuel consumption, sailing time, vessel stability, and hazardous weather conditions. Weather navigation technology is particularly useful for long-distance voyages, improving the success rate, safety, and cost-effectiveness of voyages. Currently, several companies internationally offer weather navigation services, and some common weather navigation software is available.

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

[0004] In the process of meteorological navigation, commonly used route selection methods include 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 complex and the optimal solution is inaccurate, so it has not been widely used. Isochrone method is a simple and easy route selection method, often used to select the optimal initial route. Dynamic programming method is a recursive algorithm based on the Bellman optimization principle. It has a large amount of calculation, but it is widely used with the high level of development of computer technology. 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 that realizes route planning in a global and universal calculation method through multiple parameters and influencing factors, and its development is still immature.

[0005] Compared to road network navigation, ship route planning algorithms are less mature and still have significant room for development. Typically, weather navigation algorithms and services rely on simple estimations and lack advanced features such as vessel stall and fuel estimation. Therefore, designing a solution that enables more accurate navigation has become a pressing technical challenge for those skilled in the art. Summary of the Invention

[0006] In response to 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] A first aspect of an 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 based on the ship's width, ship's draft, ship's length between perpendiculars, and ship's air resistance coefficient in the ship navigation parameters; wherein the ship navigation parameters also include the ship's starting point, the ship's destination, the ship's main engine output power, the ship's drive efficiency, and the main engine's fuel consumption rate;

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

[0010]

[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 main engine fuel consumption rate;

[0012] Acquiring sea condition forecast data for a target navigation area, and establishing a plurality of meteorological grid areas according to a preset grid size based on the target navigation area, wherein each meteorological grid area corresponds to a piece of meteorological forecast data; and determining the stall information of the ship in the corresponding meteorological grid area based on the meteorological forecast data, a hydrostatic resistance parameter of the ship, and an effective power of the ship;

[0013] Determining an initial recommended route for the corresponding ship based on the ship's starting point and destination, the main engine's unit fuel consumption, weather forecast data for each meteorological grid area in the target navigation area, ship stall information within the corresponding meteorological grid area, and a navigation pathfinding algorithm in the ship's navigation parameters;

[0014] Acquiring meteorological sensor parameters and real-time fuel consumption information of a ship during navigation detected by a shipboard monitoring unit installed on the ship, wherein the shipboard monitoring unit includes a wind speed and direction meter, a shipboard wave radar, and an oil flow meter; the meteorological sensor parameters include real-time wind speed parameters and real-time wave height parameters;

[0015] The stall correction parameter of the ship is calculated based on 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 based on 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 includes:

[0018] Determining 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 based on 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's effective power, the ship's hydrostatic resistance parameter, the ship's total resistance, and the stall calculation formula. The stall calculation formula is:

[0022]

[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 further includes water flow data;

[0025] Determining the corresponding total resistance of the ship based on 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 manner, in the first aspect of the embodiment of the present invention, the shipborne monitoring unit further includes a speed log; and the calculating the ship's operating unit fuel consumption and stall correction parameter based on the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters includes:

[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 sensing parameter and a preset wave height-resistance mapping relationship;

[0030] determining a real-time total resistance of the ship under the current sea conditions based on the real-time wind resistance data, the real-time wave resistance data, and the still water resistance parameter of the ship, and determining an experienced stall of the ship under the current sea conditions based on the still water resistance parameter of the ship and the real-time total resistance of the ship;

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

[0032] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the shipborne 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 provided on the ship, the method further includes:

[0034] Determine the real-time fuel consumption rate of the main engine based on 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 based on 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 manner, in the first aspect of the embodiment of the present invention, determining the initial recommended ship route for the corresponding ship based on the ship's starting point and destination, the engine's 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 pathfinding algorithm, in the ship's navigation parameters, includes:

[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 nodes to be explored and a closed list to store nodes that have been explored;

[0039] Starting from the starting node, add it to the open list and calculate the navigation cost and heuristic function value based on 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. Repeat 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] A first acquisition module is configured to acquire ship navigation parameters and determine the still water resistance parameters of the corresponding ship based on the ship's width, ship's draft, ship's length between perpendiculars, and ship's air resistance coefficient, among the ship's navigation parameters; wherein the ship's navigation parameters also include the ship's starting point, ship's destination, ship's main engine output power, ship's drive efficiency, and main engine 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]

[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 engine is the fuel consumption per unit time of the ship's main engine, and SFOC is the main engine fuel consumption rate;

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

[0048] A route determination module is configured to determine an initial recommended route for a corresponding ship based on the ship's starting point and destination, the main engine's unit fuel consumption, the weather forecast data for each meteorological grid area in the target navigation area, the ship's stall information in the corresponding meteorological grid area, and a navigation pathfinding algorithm.

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

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

[0051] As an optional implementation manner, in the second aspect of the embodiment of the present invention, determining the initial recommended ship route for the corresponding ship based on the ship's starting point and destination, the 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 pathfinding algorithm, includes:

[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 nodes to be explored and a closed list to store nodes that have been explored;

[0053] Starting from the starting node, add it to the open list and calculate the navigation cost and heuristic function value based on 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. Repeat 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] A 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 calling the executable program code stored in the memory to execute an intelligent correction method based on shipborne 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] In this embodiment of the present invention, the intelligent correction method based on shipboard navigation meteorological parameters uses a shipboard monitoring unit to obtain real-time meteorological sensor parameters (such as wind speed and wave height) and fuel consumption information during navigation, and calculates the ship's stall correction parameters. Based on this real-time data, the recommended route for the next phase can be dynamically updated and optimized, ensuring that the ship can make optimal navigation decisions based on 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 following briefly introduces the drawings required for use in the embodiments. 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 paying any creative work.

[0061] Figure 1 This 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 1 is a flow chart of ship stall information calculation disclosed in an embodiment of the present invention;

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

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

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

[0066] Figure 6 1 is a schematic structural 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 diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

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

[0070] Compared to road network navigation, the maturity of ship route planning algorithms is still relatively low, and there is still considerable room for development. Typically, meteorological navigation algorithms and services are mostly simple estimates, lacking advanced functions such as ship stall and fuel estimation. Based on this, embodiments of the present invention disclose an intelligent correction method, system, electronic device, and storage medium based on shipborne navigation meteorological parameters. This method uses a shipborne monitoring unit to obtain real-time meteorological sensor parameters (such as wind speed and wave height) and fuel consumption information of the ship during navigation, and can calculate the ship's stall correction parameters. Based on this real-time data, the recommended route for the next phase 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] Example 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 a still water resistance parameter of the corresponding ship based on the ship's width, ship's draft, ship's length between perpendiculars, and ship's air resistance coefficient in the ship navigation parameters; wherein the ship navigation parameters also include the ship's starting point, the ship's destination, the ship's main engine output power, the ship's drive efficiency, and the main engine's 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]

[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 main engine fuel consumption rate;

[0077] S103: Acquiring sea condition forecast data for a target navigation area, and establishing a plurality of meteorological grid areas according to a preset grid size based on the target navigation area, wherein each meteorological grid area corresponds to a piece of meteorological forecast data; and determining the stall information of the ship in the corresponding meteorological grid area based on the meteorological forecast data, the hydrostatic resistance parameter of the ship, and the effective power of the ship;

[0078] S104: determining an initial recommended route for the corresponding ship based on the ship's starting point and destination, the engine's unit fuel consumption, weather forecast data for each meteorological grid area in the target navigation area, ship stall information within the corresponding meteorological grid area, and a navigation pathfinding algorithm, among the ship's navigation parameters;

[0079] S105: Acquiring meteorological sensor 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 sensor parameters include real-time wind speed parameters and real-time wave height parameters;

[0080] S106: Calculating a 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 updating the recommended route for the ship in the next phase according to the real-time fuel consumption information of the ship and the stall correction parameter.

[0081] By acquiring ship navigation parameters such as ship width, draft, length between perpendiculars, and air resistance coefficient, the method of this embodiment of the present invention can accurately determine the ship's still water resistance parameters. This helps to more accurately assess the ship's performance under different conditions, providing a basis for subsequent route planning and stall correction.

[0082] Using the main engine transmission efficiency and fuel consumption rate, combined with a pre-set efficiency calculation formula, the ship's effective power and specific fuel consumption can be calculated. This helps shipowners or operators better understand the ship's energy consumption and take measures to optimize the ship's fuel efficiency. By obtaining sea condition forecast data for the target navigation area and dividing the area into multiple meteorological grid areas, each corresponding to a meteorological forecast data set, this enables a more precise assessment of the impact of different meteorological conditions on the ship's navigation, including stall situations. This helps plan routes in advance, avoid adverse weather conditions, and reduce navigation risks.

[0083] The solution 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 pathfinding algorithm to intelligently plan an initial recommended route. This not only improves navigation efficiency but also ensures that the ship minimizes energy consumption and stalls 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 determining of the ship stall information in the corresponding meteorological grid area based on the weather forecast data, the hydrostatic resistance parameter of the ship, and the effective power of the ship includes:

[0086] S1021: Determine 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: Determine the corresponding total resistance of the ship based on the obtained wind resistance data, wave resistance data, and still water resistance parameters of the ship;

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

[0090]

[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] By incorporating wind direction, wind speed, and wave height forecast data, the solution in this embodiment of the present invention can more comprehensively consider the impact of meteorological factors on ship navigation. This refined use of meteorological data enables more accurate predictions of ship stalls, helping shipping companies better plan routes and adjust ship speeds, thereby improving transportation efficiency while ensuring safety.

[0093] The method of determining wind resistance data and wave resistance data based on the wind-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 changing meteorological conditions on ship resistance in real time, allowing ships to adjust their navigation strategies according to actual conditions and reduce unnecessary energy consumption. By combining wind resistance data, wave resistance data and the ship's hydrostatic resistance parameters to calculate the total resistance of the ship, and further combining it 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 in 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 the ship under different meteorological conditions in advance, so that they can 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, during 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 perpendiculars, 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's effective power and ship stall:

[0095]

[0096]

[0097] Among them, R total is the total resistance of the ship, R wind is wind resistance, R wave is the 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 a ship's route is determined, it will not be frequently maneuvered, and the ship will be at the most economical speed, that is, the ship's main engine speed is at the most efficient state. The effective power of a ship and the main engine fuel consumption have the following relationship: ,

[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 based on 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 incorporating water flow data, this technology can more comprehensively account for the resistance a ship faces during navigation. Wind resistance, wave resistance, and water resistance are the primary components of a ship's navigational resistance. By factoring these factors together, the total resistance can be more accurately calculated, leading to more precise predictions of a ship's navigational performance and fuel consumption.

[0104] More preferably, the shipborne monitoring unit further includes a speed log; and the calculating of the ship's operating unit fuel consumption and stall correction parameter based on the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters includes:

[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 sensing parameter and a preset wave height-resistance mapping relationship;

[0107] determining a real-time total resistance of the ship under the current sea conditions based on the real-time wind resistance data, the real-time wave resistance data, and the still water resistance parameter of the ship, and determining an experienced stall of the ship under the current sea conditions based on the still water resistance parameter of the ship and the real-time total resistance of the ship;

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

[0109] This embodiment of the present invention utilizes a speed log to monitor a vessel's speed in real time. This technology compares the speed with the vessel's empirical stall calculated from meteorological sensor parameters (real-time wind speed and wave height) and resistance mapping, thereby generating stall correction parameters. This real-time monitoring and dynamic adjustment method enables vessels to rapidly respond to changing sea conditions, optimize navigation strategies, and improve navigation efficiency and safety.

[0110] By combining meteorological sensor parameters (real-time wind speed and wave height) with resistance mapping to calculate real-time wind and wave resistance data, and then determining the vessel's real-time total resistance, this method more accurately reflects the vessel's stall situation in current sea conditions. Compared to static weather forecast data, real-time sensor data can more promptly reflect changes in sea conditions, thereby improving the accuracy of stall prediction.

[0111] More preferably, the shipborne monitoring unit further includes a shaft power meter, which 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 provided on the ship, the method further includes:

[0113] Determine the real-time fuel consumption rate of the main engine based on 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 based on 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] By incorporating a shaft power meter, this embodiment of the present invention can monitor the main engine's output power in real time and, combined with real-time fuel consumption information, calculate the main engine's real-time fuel consumption rate. This helps shipping companies accurately understand the main engine's energy consumption and take appropriate measures to optimize its fuel efficiency. Furthermore, by calculating the ratio of the ship's real-time effective power to the main engine's real-time output power, the ship's real-time drive efficiency can be determined, providing an important basis for evaluating and optimizing ship performance.

[0117] Traditional ship performance assessments often rely on static data and empirical formulas, which fail to accurately reflect a ship's actual voyage conditions. However, this technology, by monitoring the main engine's output power and fuel consumption in real time, and calculating real-time fuel consumption rate and drive efficiency, can more accurately reflect a ship's energy consumption and performance, improving data accuracy and reliability. By acquiring real-time meteorological sensor parameters, fuel consumption information, and main engine performance data, shipping companies can dynamically adjust their navigation strategies based on this data, such as adjusting speed, rerouting, or implementing energy-saving measures, to optimize navigation efficiency and reduce operating costs. This dynamic adjustment capability helps shipping companies maintain their competitive advantage in a highly competitive market.

[0118] By monitoring the main engine's output power and fuel consumption in real time, this technology can also help shipping companies promptly identify potential main engine failures or performance degradation. By comparing and analyzing historical and real-time data, it can predict the main engine's maintenance needs, allowing proactive measures to prevent failures and improve the main engine's reliability and service life.

[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, and other factors, the calculation of actual ship fuel consumption and stall is very complex and differs somewhat from empirical results. The ship's effective power and fuel consumption rate calculated using the above relationship can be further corrected, and this correction depends on the ship's actual measured data. The entire monitoring and analysis system consists of data measurement instruments, data transmission equipment, and data processing and analysis equipment. The speed meter measures the ship's speed, the oil flow meter measures the ship's main engine fuel consumption, the shaft power meter measures the ship's main engine output power, the ship's wave radar measures wave parameters, the anemometer measures wind speed and direction, GPS and AIS assist in determining the ship's position and status, and the ship's onboard analysis terminal processes and analyzes the obtained data.

[0120] When a ship is sailing at the engine's economic speed in a wide waterway with relatively calm winds and waves, and the ship's hydrostatic resistance is known, the ship's propulsion efficiency η and the engine's specific fuel consumption (SFOC) can be corrected based on the measured ship speed, engine fuel consumption, and engine output power. Fuel consumption changes caused by crew operations and other human factors are not included in the correction.

[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, length between perpendiculars, air resistance coefficient, ship total resistance coefficient, main engine transmission efficiency, main engine fuel consumption rate, etc. The correction method is relatively complex. The main steps are:

[0122] Based on the wind speed measured by the wind speed and direction meter and the wave height measured by the ship's wave radar, combined with the ship's empirical wind resistance and wave resistance data, the total resistance of the ship under the current sea conditions is obtained according to Formula 1. The ship's empirical stall speed under the current sea conditions is calculated according to Formula 3 based on the total resistance under the current sea conditions, the known ship's still water speed, still water resistance, and the effective power of the main engine. The stall correction parameter is obtained by comparing the ship's empirical stall speed with the ship's speed measured by the speedometer. More preferably, as Figure 3-Figure 5 As shown, the initial recommended ship route of the corresponding ship is determined based on the ship's starting point and 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:

[0123] 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 nodes to be explored and a closed list to store nodes that have been explored;

[0124] S1042: Starting from the starting node, add it to the open list, and calculate the navigation cost and heuristic function value based on 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 a pre-configured heuristic function;

[0125] 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. Repeat the above process until the target node is found or the open list is empty.

[0126] S1044: Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

[0127] In practical implementation, various 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 modifying parameters in weather navigation algorithms. The A* algorithm is quite flexible and can be applied in a variety of scenarios. It combines the advantages of the Dijkstra algorithm and the Best First Search algorithm, allowing it to search for the lowest-cost path with minimal computational cost. The A* algorithm adds a heuristic function to the Dijkstra algorithm, making it faster for single-target navigation and taking into account movement costs under varying sea conditions.

[0128] The A* algorithm based on an orthogonal grid commonly uses four or eight search directions, but it is also possible to construct an A* pathfinding algorithm using more search directions. More search directions provide higher route resolution and reduce large-angle turns during a route. A grid of longitude and latitude coordinates is used to divide the global ocean into grid points to distinguish between navigable and non-navigable areas, and the A* algorithm heuristic function is written based on spherical great-circle distance. In embodiments of the present invention, a four- or eight-way search approach can be used.

[0129] The specific implementation steps of the A* algorithm are:

[0130] First, define nodes and edges. Nodes represent key points on a route, such as the starting point, destination, and weather grid intersections. Each node should include its location (latitude and longitude), the cost to reach it (e.g., fuel consumption), a heuristic function value (e.g., the estimated distance to the destination), and a pointer to the parent node (for backtracking). Edges are line segments or curves connecting two nodes, representing possible navigation paths. Each edge should include the cost from the starting node to the ending node (e.g., fuel consumption, time, etc.).

[0131] Second, initialization: Create an Open List to store nodes to be explored. Create a Closed List to store nodes that have already been explored. Add the starting 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 spherical great circle distance).

[0132] 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 start 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 next possible 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 start 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.

[0133] Fourth, path generation: Once the target node is found, the final path is generated by backtracking the parent node pointers from the target node to the starting node. These nodes are connected in sequence to form the final recommended route.

[0134] Fifth, 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 a sphere.

[0135] Sixth, weather conditions are considered. In practice, weather conditions (such as wind speed, wind direction, and wave height) can be included as part of the edge cost. Based on weather forecast data, the edge cost is dynamically adjusted to reflect the navigation difficulty and fuel consumption under different weather conditions.

[0136] In practice, a priority queue (e.g., a min-heap) can be used to implement the open list to speed up the node selection process. Various optimization techniques, such as A* algorithm pruning and dynamic adjustment of the heuristic function, can be used to improve the performance and accuracy of the algorithm.

[0137] In this embodiment of the present invention, the intelligent correction method based on shipboard navigation meteorological parameters uses a shipboard monitoring unit to obtain real-time meteorological sensor parameters (such as wind speed and wave height) and fuel consumption information during navigation, and calculates the ship's stall correction parameters. Based on this real-time data, the recommended route for the next phase can be dynamically updated and optimized, ensuring that the ship can make optimal navigation decisions based on actual meteorological conditions and energy consumption.

[0138] Example 2

[0139] See also Figure 6 , Figure 6 This 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:

[0140] A first acquisition module is configured to acquire ship navigation parameters and determine the still water resistance parameters of the corresponding ship based on the ship's width, ship's draft, ship's length between perpendiculars, and ship's air resistance coefficient, among the ship's navigation parameters; wherein the ship's navigation parameters also include the ship's starting point, ship's destination, ship's main engine output power, ship's drive efficiency, and main engine fuel consumption rate;

[0141] 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:

[0142]

[0143] 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;

[0144] The second acquisition module is configured to acquire sea condition forecast data for a target navigation area, establish multiple meteorological grid areas according to a preset grid size based on the target navigation area, wherein each meteorological grid area corresponds to a piece of meteorological forecast data; and determine the ship stall information within the corresponding meteorological grid area based on the meteorological forecast data and the effective power of the ship;

[0145] A route determination module is configured to determine an initial recommended route for a corresponding ship based on the ship's starting point and destination, the main engine's unit fuel consumption, the weather forecast data for each meteorological grid area in the target navigation area, the ship's stall information in the corresponding meteorological grid area, and a navigation pathfinding algorithm.

[0146] Real-time acquisition module: used to obtain meteorological sensor parameters and real-time fuel consumption information of the ship during navigation detected by the ship-borne monitoring unit installed on the ship, the ship-borne monitoring unit includes an anemometer, a ship-borne wave radar and an oil flow meter; the meteorological sensor parameters include real-time wind speed parameters and real-time wave height parameters;

[0147] Route update module: used to calculate the ship's stall correction parameter based on the real-time wind speed parameter and real-time wave height parameter in the meteorological sensor parameters, and update the ship's recommended route for the next stage based on the ship's real-time fuel consumption information and the stall correction parameter.

[0148] More preferably, the determining of the initial recommended ship route for the corresponding ship based on the ship's starting point and 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 pathfinding algorithm includes:

[0149] 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 nodes to be explored and a closed list to store nodes that have been explored;

[0150] Starting from the starting node, add it to the open list and calculate the navigation cost and heuristic function value based on 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;

[0151] 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. Repeat the above process until the target node is found or the open list is empty.

[0152] Find the target node, trace back from the target node to the starting node, and generate the final recommended route.

[0153] In this embodiment of the present invention, the intelligent correction method based on shipboard navigation meteorological parameters uses a shipboard monitoring unit to obtain real-time meteorological sensor parameters (such as wind speed and wave height) and fuel consumption information during navigation, and calculates the ship's stall correction parameters. Based on this real-time data, the recommended route for the next phase can be dynamically updated and optimized, ensuring that the ship can make optimal navigation decisions based on actual meteorological conditions and energy consumption.

[0154] Example 3

[0155] See also Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device can be a computer, a server, etc. Of course, in certain circumstances, it can 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:

[0156] A memory 510 storing executable program code;

[0157] a processor 520 coupled to the memory 510;

[0158] The processor 520 calls the executable program code stored in the memory 510 to execute part or all of the steps of the intelligent correction method based on shipborne navigation meteorological parameters in the first embodiment.

[0159] 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 some or all steps of an intelligent correction method based on shipborne navigation meteorological parameters in embodiment 1.

[0160] An 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 caused to execute part or all of the steps of the intelligent correction method based on shipborne navigation meteorological parameters in embodiment one.

[0161] 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. When the computer program product runs on a computer, the computer executes some or all of the steps in an intelligent correction method based on shipborne navigation meteorological parameters in embodiment one.

[0162] 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 order of execution 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.

[0163] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of this embodiment.

[0164] In addition, the functional units in the embodiments of the present invention may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The integrated unit may be implemented in the form of hardware or software functional units.

[0165] If the integrated unit is implemented as 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, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests for causing a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the method described in various embodiments of the present invention.

[0166] In the embodiments provided herein, it should be understood that "B corresponding to A" means that B is associated with A and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B based solely on A; B can also be determined based on A and / or other information.

[0167] Those skilled in the art will appreciate that some or all of the steps in the various methods of the embodiments may be performed by instructing related hardware through a program. The program may be stored in a computer-readable storage medium, including 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 programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0168] 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 herein 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 limiting 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 based on the ship's width, ship's draft, ship's length between perpendiculars, and ship's air resistance coefficient in the ship navigation parameters; wherein the ship navigation parameters also include the ship's starting point, the ship's destination, the ship's main engine output power, the ship's drive efficiency, and the main engine's fuel consumption rate; The corresponding ship effective power and main engine unit fuel consumption are calculated based on the main engine transmission efficiency and main engine fuel consumption rate and a preset efficiency calculation formula; the efficiency calculation formula includes: 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; Acquiring sea condition forecast data for a target navigation area, and establishing a plurality of meteorological grid areas according to a preset grid size based on the target navigation area, wherein each meteorological grid area corresponds to a piece of meteorological forecast data; and determining ship stall information within the corresponding meteorological grid area based on the meteorological forecast data, a hydrostatic resistance parameter of the ship, and an effective power of the ship; the meteorological forecast data including 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 includes: Determining 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 based on 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's effective power, the ship's hydrostatic resistance parameter, the ship's total resistance, and the stall calculation formula. The stall calculation formula is: 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; Determining an initial recommended route for the corresponding ship based on the ship's starting point and destination, the main engine's unit fuel consumption, weather forecast data for each meteorological grid area in the target navigation area, ship stall information within the corresponding meteorological grid area, and a navigation pathfinding algorithm in the ship's navigation parameters; Acquiring meteorological sensor parameters and real-time fuel consumption information of a ship during navigation detected by a shipboard monitoring unit installed on the ship, wherein the shipboard monitoring unit includes a wind speed and direction meter, a shipboard wave radar, and an oil flow meter; the meteorological sensor parameters include real-time wind speed parameters and real-time wave height parameters; The stall correction parameter of the ship is calculated based on 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 based on 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 also includes water flow data; Determining the corresponding total resistance of the ship based on 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.

3. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 1, characterized in that: The ship-borne monitoring unit further includes a speed log; and the calculation of the ship's unit fuel consumption and stall correction parameter based on the real-time wind speed parameter and the real-time wave height parameter in the meteorological sensing parameters includes: 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 sensing parameter and a preset wave height-resistance mapping relationship; determining a real-time total resistance of the ship under the current sea conditions based on the real-time wind resistance data, the real-time wave resistance data, and the still water resistance parameter of the ship, and determining an experienced stall of the ship under the current sea conditions based on the still water resistance parameter of the ship and the real-time total resistance of the ship; The stall correction parameter is obtained by comparing the real-time ship speed measured by the speed log with the ship's experienced stall speed under the current sea conditions.

4. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 3, characterized in that: The shipborne monitoring unit further comprises 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 provided on the ship, the method further includes: Determine the real-time fuel consumption rate of the main engine based on 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 based on 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.

5. The intelligent correction method based on shipborne navigation meteorological parameters according to claim 3, characterized in that: The determining of the initial recommended route of the corresponding ship based on the ship's starting point and 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 includes: 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 nodes to be explored and a closed list to store nodes that have been explored; Starting from the starting node, add it to the open list and calculate the navigation cost and heuristic function value based on 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. Repeat 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.

6. An intelligent correction system based on shipborne navigation meteorological parameters, characterized in that: include: A first acquisition module is configured to acquire ship navigation parameters and determine the still water resistance parameters of the corresponding ship based on the ship's width, ship's draft, ship's length between perpendiculars, and ship's air resistance coefficient, among the ship's navigation parameters; wherein the ship's navigation parameters also include the ship's starting point, ship's destination, ship's main engine output power, ship's drive efficiency, and main engine fuel consumption rate; The first calculation module is used to calculate the corresponding ship's 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: 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; The second acquisition module is configured to acquire sea condition forecast data for a target navigation area, establish multiple meteorological grid areas according to a preset grid size based on the target navigation area, wherein each meteorological grid area corresponds to a piece of meteorological forecast data; and determine the ship stall information within the corresponding meteorological grid area based on the meteorological forecast data and the effective power of the ship; A route determination module is configured to determine an initial recommended route for a corresponding ship based on the ship's starting point and destination, the main engine's unit fuel consumption, weather forecast data for each weather grid area in the target navigation area, ship stall information within the corresponding weather grid area, and a navigation pathfinding algorithm, among the ship's navigation parameters; 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 includes: Determining 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 based on 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's effective power, the ship's hydrostatic resistance parameter, the ship's total resistance, and the stall calculation formula. The stall calculation formula is: 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; Real-time acquisition module: used to obtain meteorological sensor parameters and real-time fuel consumption information of the ship during navigation detected by the ship-borne monitoring unit installed on the ship, the ship-borne monitoring unit includes an anemometer, a ship-borne wave radar and an oil flow meter; the meteorological sensor parameters include real-time wind speed parameters and real-time wave height parameters; Route update module: used to calculate the ship's stall correction parameter based on the real-time wind speed parameter and real-time wave height parameter in the meteorological sensor parameters, and update the ship's recommended route for the next stage based on the ship's real-time fuel consumption information and the stall correction parameter.

7. The intelligent correction system based on shipborne navigation meteorological parameters according to claim 6, characterized in that: The determining of the initial recommended route of the corresponding ship based on the ship's starting point and 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 includes: 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 nodes to be explored and a closed list to store nodes that have been explored; Starting from the starting node, add it to the open list and calculate the navigation cost and heuristic function value based on 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. Repeat 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.

8. 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 5.

9. 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 according to any one of claims 1 to 5.

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