Inspection method and system for unmanned ship

Abstract

The invention discloses an unmanned ship inspection method and system, and relates to the technical field of inspection methods, and the method comprises the steps: determining marine meteorological detection nodes based on an inspection route and marine meteorological data detected by an unmanned ship; a plurality of marine meteorological characteristics are determined according to detection of a plurality of marine meteorological detection nodes, and the marine meteorological types of the inspection area are determined according to the marine meteorological characteristics, the inspection area enclosed by the inspection route and the marine meteorological data of the target area, so that the accuracy of the marine meteorological types of the inspection area is ensured. Therefore, the emergency inspection mode of the unmanned ship is determined according to the influence event corresponding to the marine meteorological type, the model of the unmanned ship and the mode mapping relation; in the emergency inspection mode of the unmanned ship, the emergency route of the unmanned ship is determined according to the speed of the unmanned ship and the relative distance between the unmanned ship and the target area, the normal inspection condition and the emergency inspection condition of the unmanned ship are compatible, and the inspection safety of the unmanned ship is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of inspection methods, and in particular to an inspection method and system for an unmanned ship. Background Art

[0002] With the development of science and technology, unmanned ships are used as unmanned equipment to sail in the ocean. They patrol the ocean and carry out marine missions, including marine sewage discharge and underwater detection. In existing technologies, unmanned ships patrol the ocean, usually from the current position to the target area, but during the movement of the position, they cannot accurately obtain the marine meteorological information of the patrol area. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides an inspection method and system for an unmanned vessel to solve the problems mentioned in the background art.

[0004] In one aspect, the present invention provides an inspection method for an unmanned vessel, comprising:

[0005] Determine the inspection route based on the current location of the unmanned vessel and the ocean area of ​​the target area;

[0006] Determine the marine meteorological detection nodes based on the inspection route and the marine meteorological data detected by the unmanned vessel;

[0007] Determine multiple marine meteorological characteristics based on the detection of multiple marine meteorological detection nodes, and determine the marine meteorological type of the inspection area based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area;

[0008] Determine the emergency inspection mode of the unmanned vessel based on the mapping relationship between the impact events corresponding to the marine meteorological types, the model of the unmanned vessel, and the mode;

[0009] In the emergency inspection mode of the unmanned boat, the emergency route of the unmanned boat is determined according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area.

[0010] On the other hand, the present invention provides an unmanned vessel inspection system, which is applied to the above-mentioned unmanned vessel inspection method, and the unmanned vessel inspection system includes:

[0011] The inspection route module is used to determine the inspection route based on the current position of the unmanned vessel and the ocean area of ​​the target area;

[0012] The marine meteorological detection node module is used to determine the marine meteorological detection nodes based on the inspection route and the marine meteorological data detected by the unmanned vessel;

[0013] The marine meteorological type module is used to determine multiple marine meteorological characteristics based on the detection of multiple marine meteorological detection nodes, and determine the marine meteorological type of the inspection area based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area;

[0014] The emergency inspection module is used to determine the emergency inspection mode of the unmanned vessel based on the mapping relationship between the impact event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode;

[0015] The emergency route module is used to determine the emergency route of the unmanned boat according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area in the emergency inspection mode of the unmanned boat.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The present invention can determine an inspection route according to the current position of the unmanned ship and the ocean area of ​​the target area; determine an ocean meteorological detection node based on the inspection route and the ocean meteorological data detected by the unmanned ship; determine multiple ocean meteorological characteristics based on the detection of multiple ocean meteorological detection nodes, and determine the ocean meteorological type of the inspection area based on multiple ocean meteorological characteristics, the inspection area enclosed by the inspection route, and the ocean meteorological data of the target area. It is compatible with the overall consideration of multiple ocean meteorological characteristics, the inspection area enclosed by the inspection route, and the ocean meteorological data of the target area, realizes the ocean meteorological detection service of the unmanned ship during the inspection process, and ensures the accuracy of the ocean meteorological type of the inspection area.

[0018] Therefore, the emergency inspection mode of the unmanned ship is determined based on the mapping relationship between the impact events corresponding to the marine meteorological information, the model of the unmanned ship, and the mode; in the emergency inspection mode of the unmanned ship, the emergency route of the unmanned ship is determined according to the speed of the unmanned ship and the relative distance between the unmanned ship and the target area, which is compatible with the normal inspection conditions and emergency inspection conditions of the unmanned ship, thereby ensuring the inspection safety of the unmanned ship. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 1 is a flow chart of an inspection method for an unmanned vessel in an embodiment of the present invention;

[0020] Figure 2 1 is a flow chart of step S11 in the inspection method of the unmanned vessel in an embodiment of the present invention;

[0021] Figure 3 1 is a flow chart of step S12 in the inspection method of the unmanned vessel in an embodiment of the present invention;

[0022] Figure 4 1 is a flow chart of step S13 in the inspection method of the unmanned vessel in an embodiment of the present invention;

[0023] Figure 5 1 is a flow chart of step S14 in the inspection method of the unmanned vessel in an embodiment of the present invention;

[0024] Figure 6 1 is a flow chart of step S15 in the inspection method of the unmanned vessel in an embodiment of the present invention;

[0025] Figure 7 Schematic diagram of the structure of the inspection system of the unmanned boat in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0027] Example 1:

[0028] See also Figures 1 to 6 This embodiment provides an unmanned vessel inspection method, which can be applied to unmanned vessel-based inspection scenarios. The inspection method includes:

[0029] Step S11: determining an inspection route based on the current position of the unmanned vessel and the ocean area of ​​the target area;

[0030] Step S12: determining a marine meteorological detection node based on the inspection route and the marine meteorological data detected by the unmanned vessel;

[0031] Step S13: determining a plurality of marine meteorological characteristics based on the detection of the plurality of marine meteorological detection nodes, and determining the marine meteorological type of the inspection area based on the plurality of marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area;

[0032] Step S14: determining the emergency inspection mode of the unmanned vessel according to the mapping relationship between the influencing event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode;

[0033] Step S15: In the emergency inspection mode of the unmanned boat, the emergency route of the unmanned boat is determined according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area.

[0034] refer to Figure 2 In step S11, the inspection route is determined according to the current position of the unmanned ship and the ocean area of ​​the target area. The specific steps are as follows:

[0035] S111: collecting inspection signals from the unmanned vessel, determining a target area based on the inspection signals from the unmanned vessel, and determining a marine area of ​​the target area based on the island morphology and the surrounding range of the target area;

[0036] S112: Determine a preliminary route based on the current position of the unmanned vessel and the target area, determine a marine inspection area based on the preliminary route and the marine area of ​​the target area, and determine the inspection route based on the area of ​​the marine inspection area, the distribution map of the marine inspection area, and the model of the unmanned vessel.

[0037] At this time, the inspection signal of the unmanned ship is collected, the inspection signal of the unmanned ship is introduced, the task instructions in the inspection signal are parsed, and the specific inspection target area is determined; at this time, the task instructions sent by the control center may contain the geographic coordinates, boundary descriptions (such as polygons), or specific landmark information of the target area; the control system on the unmanned ship parses the instructions and marks the target area in its built-in map or GIS (geographic information system); the unmanned ship uses GIS technology to convert the received geographic coordinates or boundary descriptions into visible areas on the map.

[0038] Optionally, assume that the unmanned vessel is performing an inspection mission, the goal of which is to inspect a remote island in the Pacific Ocean and its surrounding waters; the unmanned vessel establishes a connection with the control center via satellite communication, transmitting its position (latitude and longitude are 150°W, 20°N), heading to the northeast, speed of 10 knots, sufficient battery power in real time, and receives an inspection mission instruction, specifying the geographic coordinates and boundary description of the target island; the control system on the unmanned vessel parses the mission instruction and marks the boundary of the target island on the built-in GIS map. The island is elliptical, about 20 kilometers long and about 10 kilometers wide.

[0039] Considering the shape of the island and the characteristics of the surrounding sea area, determine a larger area including the target island and its surrounding sea area as the marine area; at this time, the shape, size, and complexity of the coastline of the island will affect the demarcation of the marine area; for example, an irregularly shaped island may require a larger surrounding sea area to ensure a comprehensive inspection; consider factors such as the water depth, seabed topography, tides, and distribution of marine life in the surrounding sea area, which may affect the navigation safety and inspection effect of the unmanned ship; based on the island shape and the characteristics of the surrounding sea area, use GIS technology to delineate a reasonable marine area, which should include all important marine environmental features of the target island and its surrounding area; optionally, the unmanned ship uses GIS software and marine environmental data (such as water depth maps, seabed topography maps, tidal models, etc.), combined with island morphology analysis, to automatically or manually delineate the marine area.

[0040] The unmanned vessel uses GIS software and marine environmental data to analyze the shape of the island and the characteristics of the surrounding waters. Taking into account the irregular shape of the island and the complex terrain of the surrounding waters (such as reefs and shoals), the unmanned vessel automatically demarcates an area within 50 kilometers of the island and its surroundings as a marine zone. This area ensures that the unmanned vessel can fully inspect the marine environment of the island and its surroundings while avoiding known navigation hazards.

[0041] Furthermore, a preliminary navigation route is planned from the current position of the unmanned ship to the target area. At the same time, the unmanned ship obtains the current accurate latitude and longitude coordinates through its built-in GPS or other positioning system; the target area may be a polygonal area defined by a series of geographic coordinates, or a circular area defined by a center point and its radius; the unmanned ship uses a route planning algorithm to take into account the ocean environment (such as wind direction, tides), navigation safety (such as avoiding reefs and shoals), and the navigation capabilities of the unmanned ship (such as maximum speed and endurance) to generate one or more preliminary navigation routes from the current position to the target area; at the same time, the unmanned ship may use special route planning software, input the current position, target area coordinates, and necessary ocean environment data, and the software automatically calculates the preliminary route.

[0042] Optionally, assume that the unmanned vessel is performing an inspection mission, the goal of which is to inspect a fishing ground and its surrounding waters in the Atlantic Ocean; the unmanned vessel is currently located 100 nautical miles southwest of the fishing ground, and the current position and the geographic coordinates of the target fishing ground are input into the route planning software. The software takes into account the influence of wind direction and tides and generates a preliminary navigation route from the current position to the northeast through the center of the fishing ground.

[0043] Determine a larger area that includes the preliminary route and its surrounding sea areas as the marine inspection area; at this time, expand a buffer zone of a certain width outward with the preliminary route as the center. The size of the buffer zone may be determined according to the detailed requirements of the inspection mission, the detection range of the unmanned vessel, and the characteristics of the marine environment; ensure that the expanded buffer zone completely covers the marine part of the target area and all important marine features that the preliminary route may pass through (such as straits, fishing grounds, coral reefs, etc.); at the same time, the unmanned vessel uses GIS technology to draw a buffer zone on the map based on the preliminary route and check whether it completely covers the marine part of the target area.

[0044] Optionally, a 20 nautical mile buffer zone may be extended outwards from the initial route to ensure that all significant features of the fishery and its surrounding waters are covered. This buffer zone includes the main fishing areas of the fishery and any surrounding marine protected areas.

[0045] Optimize inspection routes to ensure that unmanned vessels can efficiently and safely cover the entire marine inspection area. At this time, consider the size, complexity of the marine inspection area, and the distribution of internal ocean features, which may affect the navigation time and inspection efficiency of the unmanned vessel. The model of the unmanned vessel determines its navigation performance (such as maximum speed, endurance, and detection range), equipment configuration (such as water quality monitors, underwater detectors), and possible special functions (such as autonomous obstacle avoidance and remote control). Based on the characteristics of the marine inspection area and the model of the unmanned vessel, use route optimization algorithms or manual adjustments to determine one or more optimal inspection routes. The route should minimize navigation time, improve inspection efficiency, and ensure the safety of the unmanned vessel. At the same time, the unmanned vessel may use advanced route optimization software, input the map of the marine inspection area, the navigation performance and equipment configuration information of the unmanned vessel, and the software will automatically calculate the optimal inspection route. Alternatively, experienced operators can manually plan the inspection route based on the ocean map and the performance characteristics of the unmanned vessel.

[0046] The unmanned vessel is equipped with high-precision water quality monitors and underwater detectors, and has a long cruising range and autonomous obstacle avoidance capabilities. Taking into account the large area and complex shape of the marine inspection area, which contains multiple important fishery resource areas, the operator uses route optimization software, inputs a map of the marine inspection area, the unmanned vessel's navigation performance and equipment configuration information; the software automatically calculates an optimal inspection route, which starts from the southwest corner of the fishing ground, sails north along the edge of the fishing ground, and finally passes through the central area of ​​the fishing ground, ensuring a comprehensive inspection of the entire fishing ground and its surrounding waters, while minimizing navigation time and improving inspection efficiency. Through this process, the unmanned vessel can accurately determine the preliminary route, marine inspection area and final inspection route of its inspection mission, providing a solid foundation for the subsequent execution of inspection missions.

[0047] refer to Figure 3 In step S12, the marine meteorological detection node is determined based on the inspection route and the marine meteorological data detected by the unmanned vessel. The specific steps are as follows:

[0048] S121: The unmanned vessel conducts a sea inspection along the inspection route. The ocean meteorological detector dynamically detects and collects ocean meteorological data as the unmanned vessel conducts the sea inspection, and marks the corresponding ocean location on the ocean meteorological data.

[0049] S122: Determine a corresponding ocean meteorological area based on the detection mark and the inspection route of the unmanned vessel, and determine an ocean meteorological detection node based on the ocean meteorological area and the ocean meteorological data, wherein the plurality of ocean meteorological detection nodes are respectively within the inspection route, and a regional difference between two adjacent ocean meteorological areas is less than a preset regional difference threshold;

[0050] In an embodiment, the unmanned vessel sails on the sea according to a preset inspection route to perform marine meteorological detection tasks; at the same time, the route may be pre-planned based on the characteristics of the marine environment, navigation safety considerations and inspection objectives; the unmanned vessel ensures stable navigation along the inspection route through a built-in navigation system and automatic driving technology; at the same time, the unmanned vessel also monitors its own navigation status in real time, such as speed, heading, position, etc., to ensure navigation safety.

[0051] Use marine meteorological detectors to obtain marine meteorological data in real time; at this time, the marine meteorological detectors may include anemometers, wind vanes, thermometers, hygrometers, wave height meters, etc., which are used to measure different meteorological parameters; as the unmanned ship sails, the marine meteorological detectors will continuously collect meteorological data of the surrounding ocean, and the data will change with time and location; the marine meteorological detectors will store the collected data in the data system of the unmanned ship in real time for subsequent analysis and use.

[0052] The collected marine meteorological data is associated with specific offshore locations to form a complete meteorological data set. At this time, the unmanned ship obtains the current latitude and longitude information through GPS or other positioning systems as the geographic location mark of the meteorological data. Each meteorological data point is accompanied by a timestamp and location information to indicate when and where the data was collected. As time goes by, the unmanned ship will continue to collect and mark meteorological data, eventually forming a data set containing time, location and meteorological parameters.

[0053] Therefore, the corresponding marine meteorological area is determined according to the detection mark and the inspection route of the unmanned ship, and the marine meteorological detection node is determined based on the marine meteorological area and marine meteorological data. Multiple marine meteorological detection nodes are respectively located in the inspection route. The regional difference between the two adjacent marine meteorological areas is less than the preset regional difference threshold. Multiple marine meteorological detection nodes are introduced to ensure the accuracy of multiple marine meteorological detection nodes.

[0054] At this time, the sea area covered by the inspection route is divided into several marine meteorological areas with similar meteorological characteristics; at the same time, all meteorological data collected by the unmanned ship during the inspection process and its corresponding detection marks (location information) are analyzed; according to the similarity of meteorological data (such as the proximity of parameters such as wind speed, wind direction, and temperature), data points in adjacent or similar positions are classified into the same meteorological feature group; based on the distribution of meteorological feature groups, the sea area covered by the entire inspection route is divided into several marine meteorological areas; the meteorological data in each area should be relatively consistent.

[0055] One or more representative points are selected in each marine meteorological area as marine meteorological detection nodes for long-term or regular monitoring of meteorological changes in the area. At this time, the detection nodes should be located at locations that are representative of the meteorological data in the area, such as the average value, extreme value or point with obvious change trend of the meteorological data. Ensure that the selected nodes can accurately reflect the overall meteorological characteristics of the area, while considering the stability and reliability of the data. Within the inspection route, the detection nodes should be reasonably arranged according to the distribution and size of the marine meteorological area to ensure comprehensive coverage of the entire inspection sea area.

[0056] Ensure that the divided marine meteorological areas have a certain degree of continuity and gradualness in meteorological characteristics to avoid abrupt jumps in meteorological data between regions; at this time, calculate the mean value difference or standard deviation difference between two adjacent areas in key meteorological parameters (such as wind speed, wind direction, temperature, etc.); preset a reasonable regional difference threshold based on the fluctuation range of meteorological data, the accuracy requirements of inspection tasks and the monitoring capabilities of unmanned ships; if the difference between two adjacent areas exceeds the preset threshold, it may be necessary to re-divide the area or adjust the position of the detection node to ensure that the meteorological data between regions have reasonable continuity and gradualness.

[0057] Specifically, assume that the unmanned ship collects the following meteorological data and its detection marks during the inspection process: Data point 1: {longitude 120°, latitude 30°, time 2023-05-01 10:00, wind speed 10m / s, wind direction northeast, sea water temperature 20℃}; Data point 2: {longitude 121°, latitude 30°, time 2023-05-01 11:00, wind speed 12m / s, wind direction east, sea water temperature 21℃}; Data point 3: {longitude 122°, latitude 30°, time 2023-05-01 12:00, wind speed 10m / s, wind direction northeast, sea water temperature 20.5℃}; Data point 4: {longitude 123°, latitude 31°, time 2023-05-01 13:00, wind speed 8m / s, wind direction north, sea water temperature 19℃}.

[0058] Based on this data point, the inspection sea area is divided into two marine meteorological regions; Region 1 includes data points 1, 2, and 3, whose wind speed, wind direction, and seawater temperature are relatively close; Region 2 includes data point 4 and subsequent possible data points, and its meteorological characteristics are different from those of Region 1.

[0059] Select a detection node in each area; for example, select data point 2 (longitude 121°, latitude 30°) as the detection node in area 1 because it is located in the center of the area and the meteorological data is representative; select data point 4 as the detection node in area 2; calculate the difference in wind speed, wind direction, and seawater temperature between two adjacent areas (area 1 and area 2); assume that the preset regional difference thresholds are that the wind speed difference does not exceed 5m / s, the wind direction difference does not exceed 45°, and the seawater temperature difference does not exceed 2°C; through calculation, it is found that the differences in wind speed, wind direction, and seawater temperature between area 1 and area 2 are all less than the preset thresholds, so the divided areas are reasonable. This actual example shows how to divide marine meteorological areas and determine detection nodes based on meteorological data collected by unmanned vessels and their detection marks, while ensuring that the meteorological data differences between adjacent areas are within a reasonable range.

[0060] Specifically, assume the following meteorological data points and their scores (based on the weight and score calculation method): Data point 1: (longitude 120°, latitude 30°, score 0.6); Data point 2: (longitude 121°, latitude 30°, score 0.75); Data point 3: (longitude 122°, latitude 30°, score 0.65); Data point 4: (longitude 123°, latitude 31°, score 0.4).

[0061] Based on the score, the data point is divided into two marine meteorological regions:

[0062] Region A: contains data points 1 and 3 (with similar scores); Region B: contains data points 2 and 4 (although data point 4 has a lower score, it is divided into another region because it is farther away);

[0063] Select a detection node in each region:

[0064] Detection node for area A: data point 2 (although located at the boundary of the area, it has the highest score and is located on the inspection route); detection node for area B: data point 4 (the only data point in the area and is located on the inspection route); finally, check whether the score difference between the two adjacent areas is less than a preset threshold (for example, 0.3); in this example, the score difference between area A and area B is 0.75-0.4=0.35, which is slightly higher than the preset threshold, which may require reconsidering the area division or adjusting the weight distribution; however, in this simplified example, it is assumed that the difference is acceptable because data point 4 is located farther away and may represent different meteorological conditions.

[0065] refer to Figure 4In step S13, multiple marine meteorological characteristics are determined based on the detection of multiple marine meteorological detection nodes, and the marine meteorological type of the inspection area is determined based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area. The specific steps are as follows:

[0066] S131: Determine a node detection table based on multiple ocean meteorological detection nodes and the inspection direction of the unmanned vessel, and trigger autonomous detection of multiple ocean meteorological detection nodes along the node detection table to determine multiple ocean meteorological characteristics;

[0067] S132: The unmanned vessel captures an image of the surrounding environment at the location corresponding to the marine meteorological detection node, and determines a marine meteorological combination based on a matching of multiple marine meteorological features and the corresponding surrounding environment images;

[0068] S133: Determine a first marine meteorological coefficient based on multiple marine meteorological combinations and the inspection area enclosed by the inspection route, determine a second marine meteorological coefficient based on multiple marine meteorological combinations and marine meteorological data of the target area, and determine the marine meteorological type of the inspection area based on the first marine meteorological coefficient, the second marine meteorological coefficient and the type mapping relationship.

[0069] In an embodiment of the present application, the information of all marine meteorological detection nodes is integrated, including the node's location (longitude, latitude), detection parameters (such as wind speed, wind direction, sea water temperature, wave height, etc.), the type and accuracy of the detection equipment, etc.; the inspection direction of the unmanned ship is analyzed to determine the relative position relationship between its navigation path and each detection node, which helps to rationally plan the inspection route of the unmanned ship and ensure that each node can be effectively covered; based on the detection node information and inspection direction analysis, a node detection table is formulated; the table should contain key information such as the detection order, estimated arrival time, detection parameter list, and detection frequency of each node. At the same time, GIS (geographic information system) software or similar tools are used to mark the location of all detection nodes on the map; the optimal inspection route is planned based on the navigation speed and endurance of the unmanned ship; a detailed node detection table is formulated, including the specific detection tasks and time arrangements for each node.

[0070] The unmanned ship sails along the predetermined inspection route and uses GPS or other navigation systems to accurately locate the position of each detection node; when the unmanned ship arrives near a detection node, it automatically triggers the corresponding meteorological data collection task based on the information in the node detection table. This is achieved through preset programs or instructions to ensure that each node can be inspected according to the predetermined parameters and frequency; the meteorological detection equipment on the unmanned ship starts working, collects the required meteorological data, and stores the data in real time in the ship's data storage system; at the same time, during the voyage, the unmanned ship tracks its position in real time through the GPS positioning system; when the unmanned ship approaches a detection node, the ship's control system automatically identifies and triggers the corresponding detection task; the meteorological data is collected and stored in the unmanned ship's built-in storage device, or transmitted to the onshore data center in real time via the network.

[0071] The collected meteorological data needs to be analyzed and processed to extract key meteorological features, which may include the average, maximum, and minimum wind speeds, the frequency distribution of wind directions, and the changing trends of seawater temperature. Further identification and classification are performed based on the extracted meteorological features. For example, based on the wind speed and direction data, it is possible to determine whether there are extreme weather phenomena such as storms or typhoons. Based on the changing trends of seawater temperature, the temperature conditions of the sea area in the next few days are predicted. At the same time, the collected meteorological data are processed and analyzed. Based on the analysis results, different meteorological features are identified and classified to provide basic data support for subsequent marine meteorological warnings and forecasts.

[0072] Furthermore, the unmanned ship takes images of the surrounding environment at the position corresponding to the marine meteorological detection node, and determines the marine meteorological combination based on the matching of multiple marine meteorological features and the corresponding surrounding environment images, and takes into account the overall matching of multiple marine meteorological features and the corresponding surrounding environment images to ensure the accuracy of the marine meteorological combination.

[0073] At this time, when the unmanned vessel arrives at each preset marine meteorological detection node, it uses GPS or other navigation systems to accurately locate itself and ensure that images are captured at the correct location. The high-definition camera or other imaging equipment carried by the unmanned vessel automatically starts at the designated location to capture images of the surrounding marine environment. The image should be able to clearly reflect key information such as the wave conditions on the sea surface, the cloud cover, color, and visibility in the sky. The captured images are stored in real time in the unmanned vessel's built-in storage device or transmitted to the onshore data center via the network in real time for subsequent analysis and processing. At the same time, the unmanned vessel slows down and sails steadily when approaching the detection node to ensure the quality of image acquisition. The camera or other imaging equipment automatically starts according to the preset program or instruction and captures multiple images within the specified time period to ensure that environmental changes in different time periods are captured. The image data is securely stored or transmitted for subsequent matching and analysis with meteorological characteristics.

[0074] The meteorological data collected in the previous step (such as wind speed, wind direction, sea temperature, etc.) are integrated with the captured environmental images to form a complete data set; key meteorological features are extracted from the meteorological data, such as the average and maximum wind speed, the stability of wind direction, and the changing trend of sea temperature; at the same time, the captured environmental images are analyzed to extract visual features such as the wave conditions, cloud cover, and color of the sea surface; the extracted meteorological features are matched and analyzed with the image features to determine the current marine meteorological combination, which may require the use of machine learning algorithms or expert systems for intelligent matching and judgment; the determined marine meteorological combination results are output and recorded for subsequent analysis and reporting. At the same time, the meteorological data and image data are processed and analyzed; based on the analysis results, the current marine meteorological combination is manually or automatically determined, such as "light wind + clear sky", "strong wind + cloudy", etc.; the determined marine meteorological combination results are saved in the database for subsequent query and reference.

[0075] Specifically, assume that the unmanned vessel is performing a marine meteorological inspection mission and has arrived at the preset detection node N. At node N, the unmanned vessel automatically starts the camera according to the predetermined program to capture images of the surrounding marine environment. At the same time, the meteorological data of this node has been collected in the previous steps, including a wind speed of 10m / s, a northwest wind direction, and a seawater temperature of 20°C.

[0076] Furthermore, the unmanned boat integrates the meteorological data with the captured environmental image; extracts key meteorological features from the meteorological data, such as the average wind speed of 10m / s (belonging to the light wind category), the stable northwest wind direction, and the moderate sea temperature; at the same time, analyzes the captured environmental image and finds that the sea waves are relatively calm and the sky is clear and cloudless; based on the matching analysis of the meteorological features and the image features, the unmanned boat determines that the current marine meteorological combination is "light wind + clear sky", and the result is recorded and saved in the database for subsequent analysis and reporting; from this example, it can be seen that step S132 can more accurately determine the current marine meteorological combination by combining meteorological data and image data, providing important data support for subsequent marine meteorological warnings and forecasts.

[0077] Therefore, the first marine meteorological coefficient is determined according to multiple marine meteorological combinations and the inspection area enclosed by the inspection route, the second marine meteorological coefficient is determined according to multiple marine meteorological combinations and the marine meteorological data of the target area, and the marine meteorological type of the inspection area is determined according to the first marine meteorological coefficient, the second marine meteorological coefficient and the type mapping relationship. The overall consideration of multiple marine meteorological characteristics, the inspection area enclosed by the inspection route and the marine meteorological data of the target area is compatible, so as to realize the marine meteorological detection service of the unmanned ship during the inspection process and ensure the accuracy of the marine meteorological types in the inspection area.

[0078] At this time, based on the inspection route of the unmanned boat and the preset detection nodes, one or more inspection areas are delineated. This area is usually a polygonal area enclosed by the inspection route. Marine meteorological data of all detection nodes in each inspection area are collected, including wind speed, wind direction, sea temperature, wave height and other parameters. All meteorological data in the inspection area are statistically analyzed to calculate a comprehensive meteorological coefficient, namely the first marine meteorological coefficient. The first marine meteorological coefficient is a weighted average, maximum value, minimum value or other statistical quantity of multiple meteorological parameters, depending on meteorological needs and analysis purposes. At the same time, GIS software or similar tools are used to delineate inspection areas according to the inspection route. The meteorological data of all nodes in each inspection area are collected and organized. The first marine meteorological coefficient is calculated using statistical methods or mathematical models.

[0079] Optionally, assume that the unmanned ship is performing a marine meteorological inspection mission and has completed step S132 to determine multiple marine meteorological combinations; now, it is necessary to determine the marine meteorological type of the inspection area based on the meteorological combination; the unmanned ship navigates according to the predetermined inspection route and demarcates two inspection areas: area A and area B; in area A, the unmanned ship detects two meteorological combinations of "light wind + clear sky" and "light breeze + cloudy"; in area B, two meteorological combinations of "strong wind + cloudy" and "strong wind + high waves" are detected; statistical analysis is performed on the meteorological combination data, and the first marine meteorological coefficient of area A is calculated to be "low wind and calm seas", and the first marine meteorological coefficient of area B is "high wind and large waves".

[0080] For the second ocean meteorological coefficient, one or more specific target areas are determined, which may be important waterways, fishing areas, locations of offshore facilities, etc.; historical meteorological data or real-time meteorological data in the target area are obtained, which may come from fixed ocean meteorological observation stations, buoys, satellite remote sensing, etc.; based on the meteorological data of the target area, a comprehensive meteorological coefficient, namely the second ocean meteorological coefficient, is calculated. The calculation method of this coefficient is similar to that of the first ocean meteorological coefficient, but it may focus more on the meteorological characteristics and concerns unique to the target area; at the same time, the scope and location of the target area are determined; the meteorological data of the target area are obtained and organized; and statistical methods or mathematical models are applied to calculate the second ocean meteorological coefficient.

[0081] Optionally, the target area is determined to be Channel C, which is an important sea transportation channel; historical meteorological data of Channel C is obtained, and it is found that the area is often affected by strong winds and high waves; based on the data, the second ocean meteorological coefficient of Channel C is calculated to be "high winds and high waves".

[0082] Based on meteorological knowledge and experience, a mapping relationship between marine meteorological types and meteorological coefficients is established. This mapping relationship may be based on statistical analysis of historical data, judgment of an expert system, or prediction of a machine learning model. The calculated first marine meteorological coefficient and the second marine meteorological coefficient are compared with the type mapping relationship to determine the most likely marine meteorological type in the inspection area. This type may be wind waves, swells, sea fog, low temperatures, etc. The determined marine meteorological type is output and recorded, and an inspection report or warning information is generated for subsequent analysis and response. At the same time, a predefined type mapping relationship or intelligent algorithm is used to determine the meteorological type; the determined marine meteorological type is recorded and output; and an inspection report or warning information is generated and provided to relevant departments or personnel.

[0083] Optionally, a predefined category mapping relationship is used for comparison, and it is found that the first ocean meteorological coefficient "low wind and calm" in area A corresponds to the meteorological category "calm sea conditions"; similarly, the first ocean meteorological coefficient "high wind and strong waves" in area B and the second ocean meteorological coefficient "high wind and strong waves" in channel C both correspond to the meteorological category "severe sea conditions"; therefore, the ocean meteorological category of area A is determined to be "calm sea conditions", and the ocean meteorological categories of area B and channel C are determined to be "severe sea conditions".

[0084] The results are recorded and an inspection report is generated; the report indicates that during the inspection, the sea conditions in area A are calm and suitable for navigation; while the sea conditions in area B and channel C are severe, requiring cautious navigation or the adoption of countermeasures.

[0085] refer to Figure 5 In step S14, the emergency inspection mode of the unmanned vessel is determined according to the mapping relationship between the influencing event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode. The specific steps are as follows:

[0086] S141: Determine an impact event corresponding to a marine meteorological type based on the location of the marine meteorological detection node, the marine meteorological type, and the impact matching table, and determine a corresponding marine meteorological impact area based on the impact events corresponding to multiple marine meteorological types and the inspection area;

[0087] S142: If the unmanned vessel is within the marine meteorological influence area, the emergency inspection distance is determined according to the current position of the unmanned vessel and the marine meteorological influence area, and the emergency inspection mode of the unmanned vessel is determined according to the emergency inspection distance, the model of the unmanned vessel, and the mode mapping relationship.

[0088] In this embodiment, the impact event corresponding to the marine meteorological type is determined based on the location of the marine meteorological detection node, the marine meteorological type and the impact matching table, and the corresponding marine meteorological impact area is determined according to the impact events and inspection areas corresponding to multiple marine meteorological types. The overall consideration of the impact events and inspection areas corresponding to multiple marine meteorological types is compatible to ensure the accuracy of the corresponding marine meteorological impact area.

[0089] At this time, real-time or recent marine meteorological data are collected from the marine meteorological detection nodes. The data include but are not limited to wind speed, wind direction, wave height, sea water temperature, visibility, etc.; based on the collected data, a preset algorithm or rule set is used to identify the current marine meteorological type, which may be predefined, such as "strong wind", "heavy rain", "sea fog", etc.

[0090] Furthermore, an impact matching table can be pre-constructed, which lists the correspondence between various marine meteorological types and the impact events they may trigger. This impact matching table is compiled based on historical data and expert experience. The identified marine meteorological type is compared with the impact matching table to determine the impact events that may be triggered by the meteorological type. The impact events may include navigation difficulties, increased risk of ship capsizing, reduced visibility, and obstructed fishing operations. Optionally, assume that at a certain marine meteorological detection node, the collected data shows that the current wind speed is 20m / s, the wave height is 3m, and the visibility is 1km. According to a preset algorithm, the current marine meteorological type is identified as "strong winds + low visibility." After consulting the impact matching table, it is determined that the impact events that may be triggered by this meteorological combination are "navigation difficulties, increased risk of ship capsizing, and reduced visibility affecting navigation safety."

[0091] The impact events corresponding to the multiple identified marine meteorological types are integrated to form a comprehensive list of impact events. At this time, the geographical characteristics of the inspection area are taken into consideration, such as the shape of the coastline, water depth, seabed topography, channel distribution, etc., which will affect the actual impact range of the meteorological event. Combining the impact event list and the geographical characteristics of the inspection area, a geographic information system (GIS) or similar spatial analysis tool is used to determine the marine meteorological impact area, which is the geographical range where the meteorological event may have an actual impact. The determined impact area is output in the form of a map, marking the specific affected areas and the possible degree of impact.

[0092] Furthermore, if the unmanned ship is within the marine meteorological influence area, the emergency inspection distance is determined based on the current position of the unmanned ship and the marine meteorological influence area, and the emergency inspection mode of the unmanned ship is determined based on the emergency inspection distance, the model of the unmanned ship and the mode mapping relationship, which is compatible with the overall consideration of the emergency inspection distance, the model of the unmanned ship and the mode mapping relationship to ensure the accuracy of the emergency inspection mode of the unmanned ship.

[0093] At this time, the current position coordinates of the unmanned boat are accurately obtained through the GPS system or other positioning technology of the unmanned boat; the marine meteorological impact area determined in step S141 is reviewed to understand the boundary, shape, size and possible impact degree of the area; based on the current position of the unmanned boat and the boundary of the marine meteorological impact area, the shortest distance from the unmanned boat to the boundary of the impact area is calculated. This distance is regarded as the emergency inspection distance, which represents the minimum distance that the unmanned boat can approach the impact area for inspection without being seriously disturbed by meteorological conditions while maintaining safety; at the same time, a certain safety margin is added on the basis of the calculated emergency inspection distance to cope with sudden changes in meteorological conditions or uncertainties in the operation of the unmanned boat.

[0094] Specifically, assume that the unmanned vessel is currently located at coordinates (120.000, 30.000), and the marine meteorological impact area is a circular area with a radius of 5 nautical miles and a center of (120.050, 30.020); through calculation, the shortest distance from the unmanned vessel to the boundary of the impact area is 2 nautical miles (without considering the safety margin); for safety reasons, a safety margin of 1 nautical mile is added, so the final emergency inspection distance is 3 nautical miles.

[0095] Furthermore, a mapping relationship table can be constructed in advance, which lists the correspondence between different emergency inspection distances, unmanned boat models and recommended inspection modes. The table is compiled based on the performance parameters of the unmanned boat, historical operating experience and expert advice; confirm the model of the unmanned boat currently performing the inspection task, and understand its performance parameters, such as speed, endurance, wind resistance, etc.; compare the emergency inspection distance and the unmanned boat model with the mode mapping relationship table, and select the most appropriate inspection mode, which may include the setting of parameters such as inspection speed, route planning, and data collection frequency; according to the selected inspection mode, adjust the relevant parameters of the unmanned boat to ensure that it can perform the emergency inspection task in the best condition.

[0096] Specifically, assuming that the model of the unmanned boat is "high-speed wind-resistant", its maximum speed is 40 knots and its endurance is 24 hours; after consulting the mode mapping relationship table, it is found that when the emergency inspection distance is 3 nautical miles and the unmanned boat model is "high-speed wind-resistant", the recommended inspection mode is "medium-speed safety inspection", which requires the unmanned boat to sail at a speed of 20 knots, maintain a safe route planning, and increase the data collection frequency to obtain more detailed meteorological information; therefore, the speed and route planning parameters of the unmanned boat are adjusted to ensure that it can perform emergency inspection tasks in the "medium-speed safety inspection" mode.

[0097] refer to Figure 6In step S15, in the emergency inspection mode of the unmanned boat, the emergency route of the unmanned boat is determined according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area. The specific steps are:

[0098] S151: The unmanned vessel performs an inspection based on the emergency inspection mode, determines the relative distance between the unmanned vessel and the target area based on the distance detection between the unmanned vessel and the target area, and marks the portion of the distance corresponding to the emergency inspection mode in the relative distance;

[0099] S152: Determine an emergency route for the unmanned vessel based on the partial distance corresponding to the emergency inspection mode, the speed of the unmanned vessel, and the emergency inspection mode of the unmanned vessel, and mark corresponding emergency measures in the emergency route of the unmanned vessel;

[0100] S153: Collect the inspected routes of the unmanned ship relative to the inspection area, and determine the uninspected area based on the inspected routes, the emergency routes of the unmanned ship, and the inspection area. Determine the uninspected range based on the route detection of the uninspected area, and use the uninspected range as the priority inspection range for the next maritime inspection of the unmanned ship.

[0101] In this embodiment, the unmanned boat performs inspections based on the emergency inspection mode, determines the relative distance between the unmanned boat and the target area based on the distance detection between the unmanned boat and the target area, and marks the part of the distance corresponding to the emergency inspection mode in the relative distance, introducing the relative distance between the unmanned boat and the target area.

[0102] At this time, the unmanned ship starts the corresponding emergency inspection mode according to the preset emergency inspection instructions or automatically detected marine meteorological conditions. This mode may include adjusting the navigation speed, changing the route, increasing the data collection frequency, etc. to adapt to the current sea conditions and inspection needs.

[0103] The unmanned ship uses its own sensor system (such as radar, sonar, GPS, etc.) to detect the relative distance between the unmanned ship and the target area (which may be an ocean meteorological impact area, a dangerous goods area, or other areas that require special attention) in real time. The relative distance between the unmanned ship and the target area is the straight-line distance between the current position of the unmanned ship and the boundary or center point of the target area, or it may be a dynamic distance calculated based on the navigation path of the unmanned ship and the shape of the target area.

[0104] According to the requirements of the emergency inspection mode, the unmanned boat will mark a specific distance in the relative distance. This distance may be an area where the unmanned boat needs to maintain a safe distance, or it may be an area where inspections need to be strengthened or specific measures need to be taken. The marking method may be to record this distance through the internal system of the unmanned boat, or to show the location and range of this distance to the operator through a display interface.

[0105] Specifically, assume that the unmanned ship is carrying out an emergency inspection mission in the typhoon-affected area; the unmanned ship has started the "remote safety inspection" mode according to the location and intensity of the typhoon, reducing the sailing speed and increasing the frequency of data collection; the unmanned ship starts the "remote safety inspection" mode and adjusts the sailing speed and route to ensure that while maintaining a safe distance, it can effectively monitor the impact range of the typhoon; the unmanned ship uses GPS and radar systems to detect the relative distance between itself and the center of the typhoon-affected area in real time; it is assumed that the current unmanned ship is about 20 nautical miles away from the center of the typhoon-affected area.

[0106] According to the requirements of the "remote safety inspection" mode, the unmanned vessel marks a specific distance in the relative distance, that is, an area 10-15 nautical miles from the center of the typhoon-affected area. This area is considered to be an area with a stronger typhoon impact. The unmanned vessel needs to maintain a safe distance and strengthen data collection and analysis to promptly detect and report any potential dangerous situations; the unmanned vessel records this marked distance through the internal system and displays the location and range of this distance to the operator in a striking manner on the display interface; through such steps, the unmanned vessel can flexibly adjust its own inspection strategy according to the relative distance from the target area during the emergency inspection process, ensuring that it can effectively monitor the target area while maintaining its own safety.

[0107] Furthermore, the emergency route of the unmanned ship is determined based on the partial distance corresponding to the emergency inspection mode, the speed of the unmanned ship, and the emergency inspection mode of the unmanned ship, and the corresponding emergency measures are marked in the emergency route of the unmanned ship, which is compatible with the overall consideration of the partial distance corresponding to the emergency inspection mode, the speed of the unmanned ship, and the emergency inspection mode of the unmanned ship to ensure the accuracy of the emergency route of the unmanned ship.

[0108] At this time, based on the relative distance between the unmanned boat and the target area determined in S151, and the specific requirements of the emergency inspection mode, the distance segment that the unmanned boat needs to pay special attention to when performing emergency inspections is clarified. This distance segment may be the range where the unmanned boat needs to maintain a safe distance, or it may be an area that requires enhanced monitoring or the adoption of specific emergency measures.

[0109] The speed of the unmanned vessel is an important factor in determining the emergency route. In the emergency inspection mode, the speed of the unmanned vessel may be adjusted according to the sea conditions, the characteristics of the target area, and the need for emergency measures. For example, when approaching a dangerous area, the unmanned vessel may slow down to ensure safety; and when away from the dangerous area, the unmanned vessel may speed up to improve inspection efficiency.

[0110] Based on the information from steps one and two, the unmanned vessel will calculate an emergency route that meets safety requirements and efficiently completes the inspection task. This route may be adjusted based on the current position of the unmanned vessel, the location of the target area, the relative distance, the speed of the unmanned vessel, and the specific requirements of the emergency inspection mode.

[0111] After determining the emergency route, the unmanned vessel will mark the corresponding emergency measures according to the different locations on the route and the risks that may be encountered. The measures may include adjusting the sailing speed, changing the route, initiating risk avoidance procedures, strengthening data collection and analysis, etc. The marking method may be to record the measures through the internal system of the unmanned vessel, or to show the location and execution requirements of the measures to the operator through the display interface.

[0112] Therefore, the inspected routes of the unmanned ship relative to the inspection area are collected, and the uninspected areas are determined based on the inspected routes, the emergency routes of the unmanned ship and the inspection areas. The uninspected range is determined based on the route detection of the uninspected areas, and the uninspected range is used as the priority inspection range for the next maritime inspection of the unmanned ship. It is compatible with the normal inspection conditions and emergency inspection conditions of the unmanned ship, and ensures the inspection safety of the unmanned ship.

[0113] At this time, the inspection route of the unmanned boat relative to the inspection area is collected. At the same time, the unmanned boat will use its built-in navigation system and sensors to record and collect the routes it has covered during this inspection. The route data usually includes the unmanned boat's navigation track, speed, direction, and data collection points at different locations. This data will be used for subsequent analysis to determine which areas have been inspected and which areas have not yet been covered.

[0114] After collecting the inspected routes, the unmanned vessel will compare and analyze the data with the preset inspection areas and emergency routes. Through comparison, the unmanned vessel can identify which areas have been covered and which areas have not been inspected due to various reasons (such as weather, sea conditions, unmanned vessel performance limitations, etc.). The uninspected areas will be regarded as uninspected areas.

[0115] After determining the uninspected area, the unmanned vessel will further analyze the specific location and scope of the area. This usually involves more detailed route planning and inspection of the uninspected area to determine its exact boundaries and scope. The purpose of this step is to more accurately understand which areas need to be covered first in the next inspection.

[0116] After determining the uninspected area, the unmanned ship will update the information into its inspection plan and use it as the priority inspection area for the next maritime inspection. This means that in the next inspection mission, the unmanned ship will give priority to covering the uninspected area to ensure comprehensive coverage and monitoring of the entire inspection area.

[0117] Specifically, suppose an unmanned vessel is conducting a regular inspection mission in a certain sea area, which contains multiple important marine facilities and waterways. During this inspection, the unmanned vessel uses its built-in navigation system and sensors to record the route it has covered. The route includes the trajectory of the unmanned vessel along the waterway and the detailed inspections conducted near various marine facilities.

[0118] After the inspection is completed, the unmanned vessel compares and analyzes the inspected route with the preset inspection area; through comparison, the unmanned vessel finds that due to the influence of weather and sea conditions, some remote sea areas and some areas near marine facilities are not covered, and these areas are marked as uninspected areas; to further determine the scope of the uninspected areas, the unmanned vessel conducts more detailed route planning and inspection of the areas; through this step, the unmanned vessel can more accurately understand the boundaries and scope of the uninspected areas, and provide more accurate guidance for the next inspection.

[0119] After determining the uninspected area, the unmanned vessel will update this information into its inspection plan and use it as the priority inspection area for the next maritime inspection. This means that in the next inspection mission, the unmanned vessel will give priority to covering the uninspected area to ensure comprehensive coverage and monitoring of the entire inspection area. In this way, unmanned vessels can continuously improve their inspection efficiency and quality, providing stronger support for marine safety and environmental protection.

[0120] For example, in this embodiment, regional importance: 50% (5 points for high-risk areas, 3 points for medium-risk areas, and 1 point for low-risk areas); regional urgency: 30% (5 points for recent anomalies, 3 points for historical anomalies, and 1 point for no anomalies); inspection difficulty: 20% (5 points for remote or complex terrain, and 1 point for easy access).

[0121] Newly discovered risk area D: 5 points for importance, 5 points for urgency, 5 points for difficulty, total score of 15 points, set as high priority; remote sea area C: 3 points for importance, 1 point for urgency, 5 points for difficulty, total score of 9 points, set as medium priority.

[0122] Collect the next inspection priority range table, the next inspection priority range table is shown in Table 1:

[0123] Table 1: The priority range of the next inspection

[0124]

[0125] Example 2:

[0126] This embodiment provides an inspection system for an unmanned ship, which can implement the inspection method described in Example 1, such as Figure 7 As shown, the inspection system of the unmanned ship includes:

[0127] The inspection route module 21 is used to determine the inspection route according to the current position of the unmanned vessel and the ocean area of ​​the target area;

[0128] The marine meteorological detection node module 22 is used to determine the marine meteorological detection node based on the inspection route and the marine meteorological data detected by the unmanned vessel;

[0129] The marine meteorological type module 23 is used to determine multiple marine meteorological characteristics based on the detection of multiple marine meteorological detection nodes, and determine the marine meteorological type of the inspection area based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area;

[0130] The emergency inspection module 24 is used to determine the emergency inspection mode of the unmanned vessel according to the mapping relationship between the impact event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode;

[0131] The emergency route module 25 is used to determine the emergency route of the unmanned vessel according to the speed of the unmanned vessel and the relative distance between the unmanned vessel and the target area in the emergency inspection mode of the unmanned vessel.

[0132] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of the technical features, it should be considered to be within the scope of this specification.

Claims

1. A method for inspecting an unmanned vessel, characterized in that: include: Determine the inspection route based on the current location of the unmanned vessel and the ocean area of ​​the target area; Determine the marine meteorological detection nodes based on the inspection route and the marine meteorological data detected by the unmanned vessel; Determine multiple marine meteorological characteristics based on the detection of multiple marine meteorological detection nodes, and determine the marine meteorological type of the inspection area based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area; Determine the emergency inspection mode of the unmanned vessel based on the mapping relationship between the impact events corresponding to the marine meteorological types, the model of the unmanned vessel, and the mode; In the emergency inspection mode of the unmanned boat, the emergency route of the unmanned boat is determined according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area.

2. The inspection method according to claim 1, characterized in that: The inspection route is determined based on the current position of the unmanned vessel and the ocean area of ​​the target area, including: Collect the patrol signals of the unmanned vessel, determine the target area based on the patrol signals of the unmanned vessel, and determine the ocean area of ​​the target area based on the island shape of the target area and the surrounding range of the target area; A preliminary route is determined based on the current position of the unmanned ship and the target area, and a marine inspection area is determined based on the preliminary route and the marine area of ​​the target area, and the inspection route is determined based on the area of ​​the marine inspection area, the distribution map of the marine inspection area and the model of the unmanned ship.

3. The inspection method according to claim 1, characterized in that: The determining of the marine meteorological detection node based on the inspection route and the marine meteorological data detected by the unmanned vessel includes: The unmanned vessel conducts sea inspections along the inspection route. The marine meteorological detector dynamically detects and collects marine meteorological data as the unmanned vessel conducts sea inspections, and marks the corresponding marine locations on the marine meteorological data. The corresponding marine meteorological area is determined according to the detection mark and the inspection route of the unmanned ship, and the marine meteorological detection node is determined based on the marine meteorological area and the marine meteorological data. Multiple marine meteorological detection nodes are respectively located in the inspection route, and the regional difference between two adjacent marine meteorological areas is less than the preset regional difference threshold.

4. The inspection method according to claim 1, characterized in that: The method of determining a plurality of marine meteorological characteristics based on the detection of a plurality of marine meteorological detection nodes, and determining the marine meteorological type of the inspection area based on the plurality of marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area, includes: Determine a node detection table based on multiple marine meteorological detection nodes and the inspection direction of the unmanned vessel, and trigger autonomous detection of multiple marine meteorological detection nodes along the node detection table to determine multiple marine meteorological characteristics; The unmanned vessel takes images of the surrounding environment at the position corresponding to the marine meteorological detection node, and determines the marine meteorological combination based on the matching of multiple marine meteorological features and the corresponding surrounding environment images.

5. The inspection method according to claim 4, characterized in that: Determine multiple marine meteorological characteristics based on the detection of multiple marine meteorological detection nodes, and determine the marine meteorological type of the inspection area based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area, and also include: The first marine meteorological coefficient is determined based on multiple marine meteorological combinations and the inspection area enclosed by the inspection route, the second marine meteorological coefficient is determined based on multiple marine meteorological combinations and the marine meteorological data of the target area, and the marine meteorological type of the inspection area is determined based on the first marine meteorological coefficient, the second marine meteorological coefficient and the type mapping relationship.

6. The inspection method according to claim 1, characterized in that: The method of determining the emergency inspection mode of the unmanned vessel according to the mapping relationship between the impact event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode includes: The impact event corresponding to the marine meteorological type is determined based on the location of the marine meteorological detection node, the marine meteorological type and the impact matching table, and the corresponding marine meteorological impact area is determined based on the impact events corresponding to multiple marine meteorological types and the inspection area.

7. The inspection method according to claim 6, characterized in that: The method of determining the emergency inspection mode of the unmanned vessel according to the mapping relationship between the impact event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode also includes: If the unmanned vessel is within the marine meteorological influence area, the emergency inspection distance is determined according to the current position of the unmanned vessel and the marine meteorological influence area, and the emergency inspection mode of the unmanned vessel is determined according to the mapping relationship between the emergency inspection distance, the model of the unmanned vessel and the mode.

8. The inspection method according to claim 1, characterized in that: In the emergency inspection mode of the unmanned boat, determining the emergency route of the unmanned boat according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area includes: The unmanned boat conducts inspections based on the emergency inspection mode, determines the relative distance between the unmanned boat and the target area based on the distance detection between the unmanned boat and the target area, and marks the part of the distance corresponding to the emergency inspection mode in the relative distance; The emergency route of the unmanned boat is determined according to the partial distance corresponding to the emergency inspection mode, the speed of the unmanned boat, and the emergency inspection mode of the unmanned boat, and corresponding emergency measures are marked in the emergency route of the unmanned boat.

9. The inspection method according to claim 8, characterized in that: In the emergency inspection mode of the unmanned boat, the emergency route of the unmanned boat is determined according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area, further comprising: Collect the inspected routes of the unmanned ship relative to the inspection area, and determine the uninspected areas based on the inspected routes, the emergency routes of the unmanned ship and the inspection area. Determine the uninspected range based on the route detection of the uninspected area, and use the uninspected range as the priority inspection range for the next maritime inspection of the unmanned ship.

10. An unmanned boat inspection system, characterized in that: The unmanned ship inspection system is applied to the unmanned ship inspection method according to any one of claims 1 to 9, and the unmanned ship inspection system includes: The inspection route module is used to determine the inspection route based on the current position of the unmanned vessel and the ocean area of ​​the target area; The marine meteorological detection node module is used to determine the marine meteorological detection nodes based on the inspection route and the marine meteorological data detected by the unmanned vessel; The marine meteorological type module is used to determine multiple marine meteorological characteristics based on the detection of multiple marine meteorological detection nodes, and determine the marine meteorological type of the inspection area based on the multiple marine meteorological characteristics, the inspection area enclosed by the inspection route, and the marine meteorological data of the target area; The emergency inspection module is used to determine the emergency inspection mode of the unmanned vessel based on the mapping relationship between the impact event corresponding to the marine meteorological type, the model of the unmanned vessel, and the mode; The emergency route module is used to determine the emergency route of the unmanned boat according to the speed of the unmanned boat and the relative distance between the unmanned boat and the target area in the emergency inspection mode of the unmanned boat.

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