A navigation positioning method and system for offshore wind power operation and maintenance vessels

Abstract

The present application relates to navigation positioning technical field, disclose a kind of offshore wind power operation ship navigation positioning method, to solve the problem of uneven task allocation, obstacle avoidance lag, positioning failure no reliable response in traditional technology. Including: real-time acquisition target sea area to be maintained wind turbine and operation ship position information, generate and update to be maintained sub-list;According to wind turbine location, operation priority and forbidden navigation area, generate and correct initial navigation route;Based on the ship travel data to build dynamic monitoring range and electronic fence, real-time correction exceeds the safe range of route;The positioning trust degree is calculated by multidimensional positioning trust evaluation system, identify invalid ship and screen auxiliary positioning ship, generate prediction positioning result and confidence interval.The present application also discloses a system for implementing the above method, including task allocation module, dynamic programming module, navigation monitoring module and emergency response module.The present application greatly improves the efficiency, safety and positioning continuity of offshore wind power operation.

Description

Technical Field

[0001] This invention relates to the field of navigation and positioning technology, specifically to a navigation and positioning method and system for offshore wind power maintenance vessels. Background Technology

[0002] With the rapid development of the offshore wind power industry, the number and distribution of target wind turbines awaiting maintenance in the target sea area are becoming increasingly complex, which puts forward higher requirements for the navigation and positioning efficiency, safety and reliability of offshore wind power maintenance vessels.

[0003] Currently, there are several shortcomings in the operation and maintenance of offshore wind power: First, task allocation relies heavily on static planning models, making it difficult to adjust in a timely manner according to dynamic changes such as the addition or removal of wind turbines to be maintained, the failure or availability of offshore wind power maintenance vessels, etc. This easily leads to overlapping operations among multiple vessels, wasted resource allocation, and affects the overall efficiency of operation and maintenance. Second, in terms of navigation route planning and obstacle avoidance, existing technologies mostly generate navigation routes based on fixed geographic information, lacking the ability to adapt to dynamic changes in the marine environment, sudden dangerous areas, and the navigation trajectories of other vessels in real time. Obstacle avoidance response is lagging, making it difficult to effectively avoid risk factors such as prohibited navigation areas and severe sea areas, posing a threat to the navigation safety of offshore wind power maintenance vessels. Third, the positioning of offshore wind power maintenance vessels is easily affected by complex marine environments, electromagnetic interference, and other factors, resulting in situations such as missing positioning signals or positioning equipment failure. Existing positioning support solutions lack an effective assessment mechanism for positioning reliability. When a vessel experiences positioning failure, it is difficult to quickly build reliable emergency positioning support, which can easily lead to positioning service interruption, loss of navigation control, and seriously affect the continuity and safety of operation and maintenance.

[0004] The existence of these problems restricts the efficient operation and maintenance of offshore wind power. Therefore, there is an urgent need for a navigation and positioning method and system for offshore wind power operation and maintenance vessels that can achieve dynamic task allocation, dynamic obstacle avoidance of routes, and emergency support for positioning failure. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a navigation and positioning method and system for offshore wind power operation and maintenance vessels, solving the problems of dynamic and balanced task allocation in offshore wind power operation and maintenance, timely obstacle avoidance in dangerous areas and emergencies during navigation, and reliable positioning assurance when vessel positioning fails.

[0006] To achieve the above objectives, the technical solution of the present invention is implemented as follows:

[0007] A navigation and positioning method for offshore wind power operation and maintenance vessels includes the following steps:

[0008] Real-time collection of location information of target wind turbines and offshore wind power maintenance vessels in the target sea area, generating and updating the maintenance sub-list of each offshore wind power maintenance vessel;

[0009] Based on the location information and maintenance priority of the target wind turbines to be maintained in the sub-list of wind turbines to be maintained, the target wind turbines to be maintained are sorted, the order of the navigation route nodes is determined, the initial navigation sub-routes between each route node are generated, and the initial navigation sub-routes are corrected according to the geographical coordinate range of the prohibited navigation area to obtain the navigation routes of each offshore wind power maintenance vessel.

[0010] The system guides offshore wind power maintenance vessels to follow the navigation route and generates a dynamic monitoring range based on the vessel's navigation data. It also integrates environmental monitoring data and traffic dynamic data of the target sea area within the dynamic monitoring range to construct an electronic fence for the offshore wind power maintenance vessels. Furthermore, when the navigation route of the offshore wind power maintenance vessels exceeds the range of the electronic fence, the system updates and corrects the vessel's navigation route.

[0011] Real-time location data of each offshore wind power operation and maintenance vessel is collected to generate real-time driving trajectories. A multi-dimensional location trust assessment system is constructed. Based on the corrected navigation route, the location trust level of each offshore wind power operation and maintenance vessel is calculated. Failed vessels with missing location information are identified. Auxiliary positioning vessels are selected for the failed vessels in combination with the location trust level to generate the predicted location result and location trust interval of the failed vessels.

[0012] Furthermore, the step of generating and updating the sub-list of offshore wind power maintenance vessels to be maintained includes:

[0013] Collect location information of target wind turbines to be maintained in the target sea area, and build a list of target wind turbines including the geographical coordinates and maintenance priority of each target wind turbine; collect the real-time location of each offshore wind power maintenance vessel capable of performing maintenance tasks, and build a list of maintenance vessels.

[0014] Calculate the maintenance distance from each offshore wind power maintenance vessel in the maintenance vessel list to each target wind turbine in the target wind turbine list;

[0015] The number of offshore wind power maintenance vessels in the maintenance vessel list is used as the cluster number. Based on the maintenance distance, each target wind turbine in the target wind turbine list is clustered to divide temporary maintenance clusters, and then a corresponding offshore wind power maintenance vessel sub-list to be maintained is constructed.

[0016] The system monitors the target wind turbine list and the maintenance vessel list in real time. If the target wind turbine list or the maintenance vessel list is updated, the system will trigger a dynamic update of the maintenance sub-list and regenerate the maintenance sub-list of the current offshore wind power maintenance vessels.

[0017] Furthermore, the step of obtaining the navigation routes of each offshore wind power operation and maintenance vessel includes:

[0018] Extract the geographic coordinates and maintenance priorities of all target wind turbines to be maintained from the maintenance sublist of each offshore wind power maintenance vessel, and simultaneously retrieve the geographic coordinate range of the prohibited navigation area.

[0019] Calculate the maintenance distance between each target wind turbine in the maintenance sublist, and sort the target wind turbines according to their maintenance priority to generate a maintenance sequence.

[0020] Each wind turbine to be maintained in the maintenance sequence is used as a route node of the navigation route, and the current real-time position coordinates of the offshore wind power maintenance vessel are used as the starting route node of the navigation route.

[0021] Following the order of the operation and maintenance sequence, each route node is connected sequentially to generate an initial navigation sub-route between adjacent route nodes;

[0022] Based on the geographical coordinates of each prohibited navigation area, the safe buffer boundary of the prohibited navigation area is constructed by extending the distance corresponding to the preset safety threshold outward.

[0023] Each initial navigation sub-route is spatially superimposed and compared with the safety buffer boundary of the corresponding prohibited navigation area to identify overlapping dangerous sections, correct the initial navigation sub-route, and obtain the optimized navigation sub-route.

[0024] The optimized navigation subroutines are integrated according to the operation and maintenance sequence to form the navigation routes for each offshore wind power operation and maintenance vessel.

[0025] Furthermore, the steps of identifying overlapping dangerous segments, correcting the initial navigation sub-route, and obtaining an optimized navigation sub-route include:

[0026] If the initial navigation sub-route overlaps with the safety buffer boundary, the initial navigation sub-route in the overlapping area is marked as an overlapping danger segment. The danger start coordinate is marked at the starting point of the overlapping danger segment, and the danger end coordinate is marked at the ending point of the overlapping danger segment.

[0027] Based on the starting coordinates of the danger, the ending coordinates of the danger, and the geographical coordinate range of the prohibited navigation area, the starting transition coordinates of the danger starting coordinates and the ending transition coordinates of the danger ending coordinates are symmetrically generated outside the safety buffer boundary.

[0028] By sequentially connecting the starting coordinates of danger, the starting transition coordinates, the ending transition coordinates, and the ending coordinates of danger, a continuous detour route is formed, which is used to replace the overlapping danger segments in the initial navigation sub-route.

[0029] The non-overlapping dangerous sections of the bypass route and the initial navigation sub-route are smoothly connected to obtain the optimized navigation sub-route.

[0030] Furthermore, the step of constructing an electronic fence for offshore wind power operation and maintenance vessels includes:

[0031] Real-time driving data of offshore wind power operation and maintenance vessels are collected, including current position coordinates, speed, heading angle and turning radius. The monitoring range radius is dynamically set with the current position coordinates of the offshore wind power operation and maintenance vessel as the center and combined with the speed. At the same time, a fixed proportion of the vessel's turning radius is added as the range expansion amount to generate a dynamic monitoring range.

[0032] Real-time access to environmental monitoring data and traffic dynamic data of other vessels within the dynamic monitoring range;

[0033] Based on the environmental adaptability standards for safe navigation of offshore wind power maintenance vessels, identify severe sea areas that exceed the environmental adaptability standards, and divide the distribution range of severe sea areas based on the spatial distribution characteristics of these areas.

[0034] Trajectory analysis is performed on traffic dynamic data to generate the navigation trajectory line of each vessel, and the distribution range of other vessel routes is divided by combining the preset vessel safety avoidance threshold.

[0035] Based on the dynamic monitoring range, the distribution range of severe sea areas and the distribution range of other vessel routes are included in the boundary constraints to form the outline of the electronic fence.

[0036] Furthermore, the step of updating and correcting the navigation route of the offshore wind power operation and maintenance vessel includes:

[0037] The system compares the spatial relationship between the current navigation route and the electronic fence boundary in real time, identifies illegal road segments that exceed the safety range of the electronic fence in the navigation route, records the start coordinates, end coordinates, and length of the illegal road segments, and generates a list of illegal road segments.

[0038] The buffer length is dynamically adjusted based on the length of the illegal road segment. The starting coordinates of the illegal road segment are used as the reference, and the illegal road segment is divided according to the buffer length to determine the coordinates of each buffer segment.

[0039] Centered on each buffer coordinate, and combined with the coordinate data of the electronic fence boundary, the key coordinate points of the buffer coordinates are retrieved, and a set of safety coordinates corresponding to each buffer coordinate is constructed.

[0040] Using the starting coordinates of the illegal road section as the correction start point and the ending coordinates as the correction end point, and combining the safe coordinate set of each buffer coordinate, alternative detour routes are planned.

[0041] Based on the real-time location of offshore wind power maintenance vessels and the real-time electronic fence boundary, the alternative detour routes within the dynamic monitoring range are updated, and the priority of the alternative detour routes is generated based on the route length of the alternative detour routes.

[0042] When the real-time location of the offshore wind power maintenance vessel is less than the starting coordinates of the illegal section, the target detour route is selected according to the priority of the alternative detour routes, the illegal section of the navigation route is replaced, and the navigation route of the offshore wind power maintenance vessel is updated.

[0043] Furthermore, the step of calculating the positioning trust level of each offshore wind power operation and maintenance vessel includes:

[0044] Collect actual positioning data of each offshore wind power operation and maintenance vessel, including real-time positioning coordinates, positioning timestamps and positioning signal strength data, sort and integrate the actual positioning data according to the positioning timestamp order, and generate real-time driving trajectory;

[0045] Retrieve the corrected navigation route of the corresponding offshore wind power operation and maintenance vessel, calculate the vertical deviation distance and cumulative deviation distance between the real-time driving trajectory and the corresponding navigation route segment segment by segment, and generate the fitting degree parameter of each navigation route segment according to the ratio of the cumulative deviation distance to the distance of the navigation route segment.

[0046] Identify abrupt inflection points in the real-time driving trajectory, record the location coordinates, location timestamp, and deviation from the navigation route for each abrupt inflection point, and integrate them to form a fluctuation characteristic dataset;

[0047] The cumulative duration of positioning signal loss for each offshore wind power maintenance vessel, the longest duration of a single loss, and the total frequency of loss were statistically analyzed, and signal loss assessment parameters were generated through weighted calculation.

[0048] Using fitting degree parameters, the density of abrupt change inflection points and average deviation amplitude in the fluctuation characteristic dataset, and signal loss assessment parameters as core evaluation indicators, a multi-dimensional positioning trust evaluation system is constructed, and weight coefficients are assigned to each core evaluation indicator. After normalizing each core evaluation indicator, it is substituted into the multi-dimensional positioning trust evaluation system, and a weighted summation is performed according to the weight coefficients to obtain the positioning trust value of each offshore wind power operation and maintenance vessel.

[0049] Furthermore, the step of filtering auxiliary positioning vessels for the failed vessel based on positioning trust levels includes:

[0050] When the positioning of a certain offshore wind power operation and maintenance vessel fails, it is marked as a failed vessel, and the real-time positioning confidence value, current positioning coordinates and navigation status data of all other offshore wind power operation and maintenance vessels in the target sea area are retrieved in real time.

[0051] A preset trust threshold for auxiliary positioning vessels is set, and offshore wind power operation and maintenance vessels with a positioning trust level higher than the trust threshold are selected as candidate auxiliary vessels to form a candidate vessel list.

[0052] Using the last valid positioning coordinates of the failed vessel as the reference coordinates, calculate the actual reachable distance between each candidate auxiliary vessel and the reference coordinates, and eliminate candidate auxiliary vessels whose actual reachable distance exceeds the preset shipborne relative positioning perception threshold.

[0053] The remaining candidate auxiliary vessels are sorted from high to low according to their positioning confidence scores, and a preset number of offshore wind power operation and maintenance vessels are selected as auxiliary positioning vessels according to the sorting.

[0054] Furthermore, the step of generating the predicted positioning result and positioning information interval for the failed vessel includes:

[0055] After the auxiliary positioning vessel responds to the cooperative positioning request, it collects relative position data; retrieves the historical positioning coordinates, historical sailing speed, historical heading angle data and historical acceleration of the failed vessel within the preset monitoring period before the positioning failure, and combines them with the target sea area environmental monitoring data to predict the theoretical sailing trajectory of the failed vessel within the positioning failure period, and generates the estimated position coordinate set corresponding to each time node on the theoretical sailing trajectory.

[0056] The real-time positioning coordinates of each auxiliary positioning vessel are extracted as fixed reference points. Based on the relative position data, the preliminary positioning positions of each auxiliary positioning vessel of the failed vessel are calculated by solving the geometric relationship of triangles, thus forming a preliminary positioning set.

[0057] Calculate the spatial distance between each preliminary location and the reliable estimated location in the preliminary location set, identify the effective location, and form an effective location subset;

[0058] The confidence scores of the auxiliary positioning vessels corresponding to each effective positioning location are extracted, weight coefficients are assigned to each effective positioning location in the effective positioning subset, and fusion calculations are performed to obtain the predicted positioning coordinates of the failed vessels.

[0059] Based on the trust level of the failed vessel, the confidence interval of the failed vessel is matched by a preset trust error level mapping rule, and the geographical coordinate boundary range of the confidence interval of the failed vessel is obtained with the predicted positioning coordinates as the center.

[0060] To achieve the above objectives, the present invention also discloses a navigation and positioning system for offshore wind power operation and maintenance vessels, which is used to implement the above method, including a task allocation module, a dynamic planning module, a navigation monitoring module and an emergency response module;

[0061] The task allocation module is used to collect the location information of the target wind turbines and offshore wind power maintenance vessels in the target sea area in real time, and generate and update the maintenance sub-list of each offshore wind power maintenance vessel.

[0062] The dynamic planning module determines the order of the navigation route nodes based on the location information and maintenance priority of the target wind turbines in the maintenance sublist, generates the initial navigation sub-route between each route node, and corrects the initial navigation sub-route according to the geographical coordinate range of the prohibited navigation area to obtain the navigation route of each offshore wind power maintenance vessel.

[0063] The navigation monitoring module is used to generate a dynamic monitoring range based on the navigation data of offshore wind power maintenance vessels, access environmental monitoring data and traffic dynamic data of the target sea area within the dynamic monitoring range, construct an electronic fence for offshore wind power maintenance vessels, and update and correct the navigation route of offshore wind power maintenance vessels when their navigation route exceeds the range of the electronic fence.

[0064] The emergency response module is used to collect the actual positioning data of each offshore wind power operation and maintenance vessel in real time, generate real-time driving trajectory, construct a multi-dimensional positioning trust assessment system, calculate the positioning trust level of each offshore wind power operation and maintenance vessel based on the corrected navigation route, identify the failed vessels with missing positioning, and filter the auxiliary positioning vessels of the failed vessels in combination with the positioning trust level, so as to generate the predicted positioning result and positioning trust interval of the failed vessels.

[0065] Beneficial effects: (1) This invention achieves dynamic balanced allocation of tasks: by collecting wind turbine and vessel location information in real time, dividing maintenance clusters based on maintenance distance, and dynamically updating the list of vessels to be maintained, it effectively avoids overlapping of multi-vessel collaborative operations and waste of resource allocation, and improves the overall efficiency of maintenance. (2) This invention improves navigation safety: by combining wind turbine priority and restricted navigation areas to generate optimized navigation routes, by constructing dynamic electronic fences based on vessel driving data, by correcting routes that exceed the safe range in real time, and by actively avoiding risk factors such as restricted navigation areas, bad sea areas and other vessels. (3) This invention ensures the continuity of positioning services: by constructing a multi-dimensional positioning trust assessment system, accurately identifying vessels with positioning failures, screening vessels with high trust in auxiliary positioning, and by combining trajectory prediction and triangulation to generate predicted positioning results and confidence intervals, it avoids navigation loss of control problems caused by positioning service interruption. Attached Figure Description

[0066] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0067] Figure 1 This is a flowchart of the navigation and positioning method for offshore wind power maintenance vessels according to an embodiment of the present invention;

[0068] Figure 2This is a flowchart illustrating the process of generating navigation routes for each offshore wind power maintenance vessel in the navigation and positioning method for offshore wind power maintenance vessels as described in this embodiment of the invention.

[0069] Figure 3 This is a flowchart illustrating the construction of an electronic fence for an offshore wind power maintenance vessel in the navigation and positioning method for offshore wind power maintenance vessels according to an embodiment of the present invention.

[0070] Figure 4 This is a flowchart illustrating the process of updating and correcting the navigation route of offshore wind power maintenance vessels in the navigation and positioning method for offshore wind power maintenance vessels according to an embodiment of the present invention.

[0071] Figure 5 This is a flowchart illustrating the process of selecting auxiliary positioning vessels based on the positioning trust level of each maintenance vessel in the navigation and positioning method for offshore wind power maintenance vessels according to an embodiment of the present invention.

[0072] Figure 6 This is a schematic diagram of the navigation and positioning system for offshore wind power maintenance vessels as described in an embodiment of the present invention. Detailed Implementation

[0073] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0074] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0075] Example 1

[0076] See Figure 1 A navigation and positioning method for offshore wind power operation and maintenance vessels, comprising the following steps:

[0077] Step S1: Real-time collection of location information of target wind turbines awaiting maintenance in the target sea area and construction of a target wind turbine list. Simultaneously, collection of location information and operational status data of offshore wind power maintenance vessels with maintenance capabilities, and construction of a maintenance vessel list. Based on the relative positional relationship between the target wind turbines and the offshore wind power maintenance vessels, and combined with the locational distribution characteristics of the target wind turbines, the target wind turbine list is dynamically decomposed to generate a maintenance sub-list for each offshore wind power maintenance vessel. A dynamic update mechanism is established for the target wind turbine list, the maintenance sub-list, and the initial navigation route. When changes in status are detected, such as an increase or decrease in the number of target wind turbines awaiting maintenance, a malfunction or failure of an offshore wind power maintenance vessel, or the addition of an idle offshore wind power maintenance vessel, the reassignment process of the maintenance sub-list is automatically triggered. This ensures that multiple offshore wind power maintenance vessels operate collaboratively without overlap and without wasted resources, providing accurate task guidance for subsequent navigation and positioning.

[0078] In this embodiment, by collecting and integrating the core data of the target wind turbines and offshore wind power maintenance vessels in real time, and dynamically decomposing a dedicated sub-list based on the relative positional relationship and wind turbine distribution characteristics, and with the dynamic update mechanism triggered by state changes, the task allocation of multiple offshore wind power maintenance vessels is balanced and the initial navigation route is accurately adapted, effectively avoiding overlapping collaborative operations and resource waste, and providing an accurate and dynamically adapted task foundation for subsequent navigation and positioning.

[0079] In a specific instance, the steps for generating a sub-list of offshore wind power maintenance vessels to be maintained include:

[0080] By using BeiDou positioning reference stations deployed in wind farms, the location information of target wind turbines awaiting maintenance in the target sea area is collected; a list of target wind turbines containing the geographical coordinates and maintenance priority of each target wind turbine awaiting maintenance is constructed.

[0081] By relying on the Beidou positioning terminals carried by offshore wind power maintenance vessels, the real-time location of each offshore wind power maintenance vessel capable of performing maintenance tasks is collected in real time, and a list of maintenance vessels is constructed.

[0082] Calculate the maintenance distance from each offshore wind power maintenance vessel in the maintenance vessel list to each target wind turbine in the target wind turbine list; for example, obtain the geographical coordinates of the target wind turbines based on the BeiDou positioning reference stations deployed at the wind farm. The real-time location coordinates of the offshore wind power maintenance vessel are collected by the Beidou positioning terminal mounted on the vessel. The maintenance distance between the two is calculated using the Haversine formula based on the geodetic coordinate system. The formula is defined as follows:

[0083]

[0084]

[0085]

[0086] in, This is a dimensionless intermediate parameter used to eliminate the influence of Earth's curvature on distance calculations. For the corresponding coordinates, latitude. The longitude of the corresponding coordinates. for and The difference in latitude between two points The difference in longitude between two points; Let the central angle be the angle formed by the target wind turbine, the maintenance vessel, and the center of the Earth. Using the Earth's average radius, the calculation results are as follows. This refers to the maintenance distance between two points.

[0087] The number of offshore wind power maintenance vessels in the maintenance vessel list is used as the cluster number. Based on the maintenance distance, each target wind turbine in the target wind turbine list is clustered to divide temporary maintenance clusters, and then a sub-list of offshore wind power maintenance vessels to be maintained is constructed. For example, the cluster division of target wind turbines to be maintained can be achieved by the K-Means clustering method. This method is based on the core logic of minimizing the sum of maintenance distances within the cluster, which can quickly adapt wind turbines to the corresponding maintenance vessels according to maintenance distance, ensuring the balance and efficiency of task allocation.

[0088] Relying on the remote monitoring platform of wind farms, the system continuously captures the dynamic changes in the number of target wind turbines awaiting maintenance. Through the shipborne fault diagnosis terminal and dispatch feedback system, it monitors the status changes of offshore wind power maintenance vessels in real time. The system monitors the target wind turbine list and the maintenance vessel list in real time. If either the target wind turbine list or the maintenance vessel list is updated, it triggers a dynamic update of the sub-list awaiting maintenance. This involves adjusting, splitting, or merging the original sub-list, completing the dynamic update of the sub-list, and regenerating the current sub-list of offshore wind power maintenance vessels awaiting maintenance.

[0089] In practice, the geographical coordinates of 50 wind turbines to be maintained in the target sea area are collected by the BeiDou positioning reference station deployed in the wind farm, and priority is set according to the maintenance needs to build a list of target wind turbines; relying on the BeiDou positioning terminal carried by the maintenance vessel, the real-time position of 10 maintenance vessels is collected to build a list of maintenance vessels.

[0090] The Haversine formula is used to calculate the maintenance distance from each maintenance vessel to each target wind turbine, as follows:

[0091]

[0092]

[0093]

[0094] Using the number of 10 maintenance vessels as the cluster number, the K-Means clustering algorithm is used to cluster 50 target wind turbines, dividing them into 10 temporary maintenance clusters, and constructing a sub-list of maintenance pending operations for each maintenance vessel; when a wind turbine completes maintenance or a new wind turbine is added, the sub-list of maintenance pending operations is dynamically updated.

[0095] Step S2: Based on the location distribution and maintenance priority of each target wind turbine in the maintenance sublist of each offshore wind power maintenance vessel, and by integrating the geographical coordinate range of the prohibited navigation area in the target sea area, a multi-objective path optimization algorithm that balances operational efficiency and obstacle avoidance safety is adopted to generate navigation routes for each offshore wind power maintenance vessel. This ensures both operational efficiency and safety redundancy, guiding the maintenance vessels to traverse each target wind turbine in the sublist in an orderly manner.

[0096] In this embodiment, by combining the location distribution and maintenance priority of the target wind turbines to be maintained, and incorporating the geographical coordinate data of obstacles in the target sea area, a navigation route is formed by using multi-target path optimization. This not only ensures that the maintenance vessel can efficiently traverse the target wind turbines in a reasonable order, but also achieves active avoidance of obstacles in the sea area, taking into account both operational efficiency and navigation safety redundancy, and providing reliable route support for the orderly conduct of maintenance operations.

[0097] Please see Figure 2 In a specific instance, the steps for generating navigation routes for each offshore wind power operation and maintenance vessel include:

[0098] Extract the geographic coordinates and maintenance priorities of all target wind turbines to be maintained from the maintenance sublist of each offshore wind power maintenance vessel, and simultaneously retrieve the geographic coordinate range of underwater obstacles, prohibited navigation areas, and other prohibited navigation areas in the target sea area; and perform coordinate benchmark unification processing to ensure that the data format is consistent with the coordinate system.

[0099] Calculate the maintenance distance between each target wind turbine in the maintenance sublist, and sort the target wind turbines according to their maintenance priority to generate a maintenance sequence. That is, sort all target wind turbines in the first round according to their maintenance priority from high to low, and sort the target wind turbines in the same priority tier according to their maintenance distance.

[0100] Each wind turbine to be maintained in the maintenance sequence is used as a route node of the navigation route. The current real-time position coordinates of the offshore wind power maintenance vessel are obtained and set as the starting route node of the navigation route. According to the order of the maintenance sequence, each route node is connected in sequence to generate the initial navigation sub-route between adjacent route nodes.

[0101] Based on the geographical coordinates of each prohibited navigation area, a safety buffer boundary is constructed by extending outwards to the distance corresponding to a preset safety threshold, thus clarifying the safe avoidance range of the prohibited navigation area. The preset safety threshold refers to the minimum safe distance standard set to ensure that offshore wind power operation and maintenance vessels avoid prohibited navigation areas during navigation. This standard needs to be calculated and determined by combining the maximum turning radius, speed, braking performance, and other navigation performance parameters of the offshore wind power operation and maintenance vessels, as well as the hydrological environmental characteristics of the target sea area, such as current speed, wave height, and visibility. This is achieved through a risk assessment model that integrates risk identification, risk quantification, and risk level determination, ensuring that the safety threshold is adapted to the vessel's navigation capabilities and the actual marine environment, thereby achieving effective avoidance of prohibited navigation areas.

[0102] Each initial navigation sub-route is spatially superimposed and compared with the corresponding safety buffer boundary of the prohibited navigation area to identify overlapping dangerous sections. The initial navigation sub-route is then corrected to obtain the optimized navigation sub-route, i.e.:

[0103] If the initial navigation sub-route overlaps with the safety buffer boundary, the initial navigation sub-route in the overlapping area is marked as an overlapping danger segment. The starting coordinates of the danger are marked at the beginning of the overlapping danger segment, and the ending coordinates of the danger are marked at the end of the overlapping danger segment.

[0104] Based on the starting and ending coordinates of the danger, and the geographical coordinate range of the prohibited navigation area, symmetrical starting transition coordinates and ending transition coordinates of the danger starting coordinates are generated outside the safety buffer boundary. Distance verification ensures that the distance between the detour starting transition coordinates, the danger ending coordinates, and the safety buffer boundary is not less than a preset safety threshold. Specifically, the ending transition coordinates refer to the key coordinate points generated outside the safety buffer boundary when the initial navigation sub-route overlaps with the safety buffer boundary, based on the danger ending coordinates, the geographical range of the prohibited navigation area, and the safety buffer boundary, used to connect the end point of the overlapping danger segment and the detour segment route. First, locate the boundary segment of the prohibited navigation area where the dangerous termination coordinates are located, clarify the correspondence between the coordinates and the boundary of the prohibited navigation area, and confirm the range of the safety buffer boundary. Then, calculate the direction vector of this boundary segment, and determine the outer normal direction that is perpendicular to the segment and points away from the prohibited navigation area. Subsequently, determine the offset distance according to the preset safety threshold plus half the turning radius of the vessel. Next, convert the dangerous termination coordinates into plane rectangular coordinates, calculate the plane position of the termination transition coordinates by multiplying the outer normal direction by the offset distance, and then convert them into a latitude and longitude format consistent with the initial navigation route through coordinate inverse projection to obtain the termination transition coordinates.

[0105] By sequentially connecting the starting coordinates of danger, the starting transition coordinates, the ending transition coordinates, and the ending coordinates of danger, a continuous detour route is formed, which is used to replace the overlapping danger segments in the initial navigation sub-route.

[0106] Curve fitting tools, such as the Bézier curve algorithm, are used to smoothly connect the non-overlapping hazardous sections of the bypass route and the initial navigation sub-route, eliminating abrupt inflection points at route corners and ensuring a smooth and continuous trajectory that conforms to the ship's navigation characteristics. The steps of constructing safety buffer boundaries, overlapping comparison, hazardous coordinate marking, bypass transition coordinate planning, bypass route generation, and smooth connection are repeated to complete the processing and optimization of hazardous sections of all initial navigation sub-routes.

[0107] The optimized navigation sub-routes are integrated in the order of the complete operation and maintenance execution sequence to form the navigation route for each offshore wind power operation and maintenance vessel, and are simultaneously output to the shipborne navigation terminal.

[0108] In the specific implementation, the geographical coordinates and priorities of 5 wind turbines in the maintenance list of a certain maintenance vessel are extracted, and the geographical coordinate range of the restricted navigation area within the target sea area is retrieved simultaneously; the maintenance distance between the 5 wind turbines is calculated, and they are sorted from high to low priority. If the priorities are the same, they are sorted by the maintenance distance between the wind turbines to generate a maintenance sequence.

[0109] Starting from the current position of the maintenance vessel, five wind turbines are connected sequentially to generate an initial navigation sub-route; a safety buffer boundary is constructed by extending the restricted navigation area outward by 500m.

[0110] Through spatial overlay comparison, it was found that a section of the initial navigation sub-route overlapped with the safety buffer boundary. The starting and ending coordinates of the danger were marked. Transition coordinates were generated outside the safety buffer boundary to construct the bypass section route. The Bézier curve algorithm was used to smoothly connect the bypass section and the non-overlapping danger section to generate an optimized navigation route.

[0111] Step S3: Guide the offshore wind power operation and maintenance vessel to navigate along its navigation route. Based on the vessel's navigation data, generate a dynamic monitoring range and access real-time environmental monitoring data and traffic dynamic data for the target sea area within the dynamic monitoring range. Identify the distribution range of severe sea areas and the navigation trajectories of other vessels, construct an electronic fence for the offshore wind power operation and maintenance vessel, and clearly define its safe navigation boundary. Continuously compare the relationship between the navigation route and the electronic fence boundary. When the navigation route exceeds the safe range of the electronic fence within the monitoring range, automatically update and correct the vessel's navigation route to proactively avoid severe sea areas and navigation conflicts, ensuring the safety and dynamic adaptability of the route.

[0112] In this embodiment, a dynamic monitoring range is generated by combining the navigation data of offshore wind power maintenance vessels. The marine environment and traffic dynamic data within the range are integrated in real time to construct an electronic fence to clarify the safety boundary. By continuously comparing the route with the fence boundary and dynamically correcting deviations from the route, the active avoidance of severe sea areas and navigation conflicts is achieved, ensuring the safety of maintenance vessels' navigation and the dynamic adaptability of the route.

[0113] Please see Figure 3 In a specific example, the steps for constructing an electronic fence for an offshore wind power operation and maintenance vessel include:

[0114] Real-time navigation data of offshore wind power operation and maintenance vessels is collected, including current position coordinates, speed, heading angle, and turning radius. The monitoring range radius is dynamically set based on the vessel's current position coordinates and speed, and adjusted in real-time according to the speed. A fixed percentage of the vessel's turning radius is also added as a range expansion factor to generate a dynamic monitoring range. This ensures that the monitoring range accurately covers the potential impact area of ​​the vessel's trajectory, avoiding monitoring redundancy or insufficient coverage issues caused by a fixed radius.

[0115] By deploying marine environmental monitoring base stations within the wind farm, real-time environmental monitoring data within the dynamic monitoring range is accessed, including wind speed, wave height, current direction, and visibility. Simultaneously, real-time traffic dynamic data such as the location, speed, heading, and vessel type of other vessels within the dynamic monitoring range are collected, with a set data collection frequency to meet real-time requirements. This improves the comprehensiveness and timeliness of traffic dynamic data, providing more accurate data support for subsequent safety boundary determination.

[0116] Based on the environmental adaptability standards for safe navigation of offshore wind power operation and maintenance vessels, the environmental safety level threshold of the accessed environmental monitoring data is determined to identify severe sea areas that exceed the environmental adaptability standards, and the distribution range of severe sea areas is divided in combination with the spatial distribution characteristics of the severe sea areas.

[0117] Traffic dynamic data is analyzed to continuously record the coordinates of other vessels, generating a navigation trajectory for each vessel. This trajectory is then combined with preset vessel safety avoidance thresholds to define the distribution range of other vessels' routes. The vessel safety avoidance threshold refers to the minimum spatial distance standard that must be maintained between maintenance vessels and other vessels, based on the vessel's navigation characteristics and marine environmental conditions, to avoid navigational conflicts. This standard must cover braking distance, steering response distance, and emergency response distance, ensuring that both vessels have sufficient time to adjust their navigation status to avoid collision risks when they meet.

[0118] Based on the dynamic monitoring range, the distribution range of severe sea areas and the distribution range of other vessel routes are included in the boundary constraints to form a closed electronic fence outline.

[0119] The integrated electronic fence outline is coordinate-calibrated, and the geographic coordinates of each vertex on the outline are recorded to generate a coordinate set for the electronic fence. On the electronic chart of the shipborne navigation terminal, the area corresponding to this coordinate set is marked with a specific visual identifier. At the same time, safe navigation information is marked inside the fence, and a prohibition-entry warning is marked outside the fence, clearly defining the safe navigation boundary of offshore wind power operation and maintenance vessels. This step innovatively designs a dedicated visual identifier and hierarchical information labeling system to replace the single labeling method, enabling crew members to quickly identify safety boundaries and warning information, improving the convenience and safety of navigation operations.

[0120] Please see Figure 4 In a specific instance, the steps for updating and correcting the navigation route of an offshore wind power maintenance vessel include:

[0121] The system compares the spatial relationship between the current navigation route and the electronic fence boundary in real time, identifies illegal road segments that exceed the safety range of the electronic fence, records the start coordinates, end coordinates, and length of the illegal road segments, and generates a list of illegal road segments.

[0122] The buffer length is dynamically adjusted based on the length of the illegal road segment. Taking the starting coordinates of the illegal road segment as the reference, the buffer length is divided into several equal segments in the direction of extension of the illegal road segment. The coordinates are marked at the endpoints of each equal segment to determine the coordinates of each buffer segment. This ensures that the buffer coordinates can evenly cover the illegal road segment and provide multiple points of support for subsequent safe route planning.

[0123] Centered on each buffer coordinate, and combined with the coordinate data of the electronic fence boundary, the area around the buffer coordinate that does not exceed the safety range of the electronic fence and avoids the bad sea area and other ship routes is searched. Key coordinate points in this area are extracted and organized into a set of safe coordinates corresponding to each buffer coordinate. Each set of safe coordinates must contain at least 3 non-collinear coordinate points to ensure that a stable route planning basis can be formed.

[0124] Using the starting coordinates of the illegal road section as the correction starting point and the ending coordinates as the correction ending point, and combining the safety coordinate set of each buffer coordinate, multiple alternative detour routes are planned. Each alternative detour route avoids the distribution range of the severe sea area and the distribution range of other vessel routes, and maintains a distance from the boundary of the electronic fence that is not less than the vessel safety avoidance threshold.

[0125] Based on the real-time location of offshore wind power maintenance vessels and the real-time electronic fence boundary, the alternative detour routes within the dynamic monitoring range are updated, and the priority of the alternative detour routes is generated based on the route length of the alternative detour routes.

[0126] When the real-time position of an offshore wind power maintenance vessel is less than the starting coordinates of the illegal section of the route, a target detour route is selected based on the priority of alternative detour routes. This detour replaces the illegal section of the navigation route, and the vessel's navigation route is updated. The preset safe detour distance is the minimum warning distance between the vessel's real-time position and the starting coordinates of the illegal section, set in advance to ensure that the vessel has sufficient time to complete the detour operation and avoid entering a dangerous area after discovering a navigation route violation. This distance must cover the response time from receiving the correction command to initiating the turning operation, the navigation distance during the turning process, and the reserved operating space to deal with sudden sea conditions, ensuring that the vessel can smoothly avoid the illegal section when initiating correction within the safe distance.

[0127] After receiving the updated navigation route, the shipborne navigation terminal automatically replaces the original route and overlays the new route on the electronic chart. Simultaneously, it activates the voice prompt function to inform the crew of the reason for the route correction and the key route nodes of the new route, ensuring that the crew is aware of the route change in a timely manner and travels according to the new route.

[0128] In the specific implementation, real-time navigation data of the vessel is collected, including its current position coordinates, speed of 10 knots, heading angle of 180°, and turning radius of 50m. A monitoring range radius of 1km is set centered on the current position coordinates and combined with the speed, with an extension of 0.5 times the turning radius added to generate a dynamic monitoring range. Environmental monitoring data within the dynamic monitoring range, including wind speed of 12m / s and wave height of 2m, is accessed to identify a hazardous sea area. Traffic dynamic data from three other vessels are accessed to generate navigation trajectory lines. Combined with a 100m safety avoidance threshold, the distribution range of other vessels' routes is defined. An electronic fence is constructed, and real-time comparison reveals that a section of the optimized navigation route enters the hazardous sea area, marking it as a violation section. Buffer coordinates are determined, a safe coordinate set is constructed, and three alternative detour routes are planned, prioritized by route length. When the vessel is 200m from the starting coordinates of the violation section, the optimal detour route is selected to replace the violation section, and the navigation route is updated.

[0129] Step S4: Collect real-time positioning data of each offshore wind power operation and maintenance vessel, generate real-time driving trajectories, construct a multi-dimensional positioning trust assessment system, comprehensively analyze the degree of fit between the real-time driving trajectory and the navigation route, trajectory fluctuation characteristics, frequency of fluctuations, and positioning signal loss, calculate the positioning trust level of each offshore wind power operation and maintenance vessel based on the corrected navigation route, and establish a positioning failure emergency response mechanism. When a maintenance vessel experiences a positioning signal loss or positioning equipment failure leading to real-time positioning failure, the positioning prediction process is automatically initiated. Based on the positioning trust level of each maintenance vessel, auxiliary positioning vessels are selected. The relative positional relationship between the failed vessel and the auxiliary positioning vessels is obtained through the shipborne relative positioning sensing equipment. Combined with the historical positioning trust level data of the failed vessel, the predicted positioning result and positioning trust interval of the failed vessel are generated to ensure the continuity and reliability of the positioning service.

[0130] In this embodiment, a multi-dimensional positioning trust assessment system is constructed to quantify positioning reliability. Combined with a positioning failure emergency response mechanism and auxiliary vessel relative positioning technology, a predicted positioning result and positioning information interval are quickly generated when a single vessel fails to position. This effectively avoids navigational loss of control caused by positioning interruption, ensures the continuity and reliability of positioning services for offshore wind power operation and maintenance vessels, and provides continuous positioning support for safe navigation throughout the entire process.

[0131] In a specific instance, the steps for calculating the positioning confidence level of each offshore wind power operation and maintenance vessel include:

[0132] The actual positioning data of each offshore wind power operation and maintenance vessel is collected synchronously through Beidou positioning and GNSS assisted positioning, including real-time positioning coordinates, positioning timestamps and positioning signal strength data. The actual positioning data is sorted and integrated according to the positioning timestamp order to generate real-time driving trajectory.

[0133] The corrected navigation route for the corresponding offshore wind power maintenance vessel is retrieved, including the coordinates of each node and the course between nodes. The vertical deviation and cumulative deviation distance between the real-time trajectory and the corresponding navigation route segment are calculated segment by segment. A fitting parameter for each navigation route segment is generated based on the ratio of the cumulative deviation distance to the distance of the navigation route segment. A navigation route segment refers to a continuous, independent segment formed by breaking down the complete navigation route of the offshore wind power maintenance vessel according to specific rules. Each segment contains clearly defined start and end coordinates and the course direction, serving as the basic unit for segment-by-segment comparison of the fitting degree between the real-time trajectory and the navigation route. Based on the distribution nodes of the target wind turbines to be maintained, the boundary nodes of prohibited navigation areas, the turning nodes of the navigation channel, and the nodes of abrupt changes in marine environmental characteristics within the navigation route, combined with the total route length and the time granularity requirements of the positioning assessment, the route is divided uniformly or non-uniformly. During the division, it is ensured that the length of each route segment is adapted to the positioning data acquisition frequency, facilitating accurate analysis of the positioning fitting of each segment. Specifically, vertical deviation distance refers to the vertical straight-line distance from each positioning point on the real-time driving trajectory to its corresponding navigation route segment. This distance is always perpendicular to the actual direction of the navigation route segment and is used to accurately quantify the degree of deviation of a single positioning point from the planned route. Cumulative deviation distance refers to the total distance obtained by summing the vertical deviation distances of all real-time positioning points corresponding to the same navigation route segment. This distance is used to comprehensively reflect the overall degree of deviation of the driving trajectory from the planned route within the entire segment. For example, the fit parameter... The calculation formula is:

[0134]

[0135] in, It is the cumulative deviation distance. It is the distance of a segment of the navigation route. The value ranges from 0 to 1. The closer the value is to 1, the higher the degree of fit between the real-time driving trajectory and the navigation route segment, and the stronger the positioning accuracy. The closer the value is to 0, the lower the degree of fit and the more obvious the positioning deviation.

[0136] The sliding window algorithm identifies abrupt inflection points in the real-time driving trajectory. Specifically, when the heading angle or distance change of adjacent positioning points exceeds the preset stable range, it is marked as an abrupt inflection point. The positioning coordinates, positioning timestamp, and deviation from the navigation route of each abrupt inflection point are recorded and integrated to form a fluctuation characteristic dataset.

[0137] The cumulative duration of positioning signal loss for each offshore wind power maintenance vessel, the longest duration of a single loss, and the total frequency of loss were statistically analyzed, and signal loss assessment parameters were generated through weighted calculation.

[0138] Using the alignment parameter, the density of abrupt change inflection points and the average deviation amplitude in the fluctuation characteristic dataset, and the signal loss assessment parameter as core evaluation indicators, a multi-dimensional positioning trust evaluation system is constructed. Combining the positioning accuracy requirements of offshore wind power operation and maintenance scenarios, weight coefficients are assigned to each core evaluation indicator. For example, the trajectory alignment parameter has the highest weight, followed by the signal loss assessment parameter.

[0139] After normalizing each core evaluation indicator, it is substituted into the multi-dimensional positioning trust evaluation system, and then weighted summation is performed according to the weight coefficient to obtain the positioning trust value of each offshore wind power operation and maintenance vessel. This value is mapped to a fixed value range, and the higher the value, the stronger the positioning reliability.

[0140] Please see Figure 5 In a specific instance, the steps for selecting auxiliary positioning vessels based on the positioning trust level of each maintenance vessel include:

[0141] When the positioning of a certain offshore wind power operation and maintenance vessel fails, it is marked as a failed vessel, and the real-time positioning confidence value, current positioning coordinates and navigation status data of all other offshore wind power operation and maintenance vessels in the target sea area are retrieved.

[0142] Based on the positioning reliability requirements of offshore wind power operation and maintenance scenarios, a trust threshold for auxiliary positioning vessels is preset. The positioning trust values ​​of each offshore wind power operation and maintenance vessel are compared with the trust threshold, and offshore wind power operation and maintenance vessels with positioning trust values ​​higher than the trust threshold are selected as candidate auxiliary vessels to form a candidate vessel list.

[0143] Using the last valid positioning coordinates of the failed vessel as the reference coordinates, the straight-line distance between each candidate auxiliary vessel and this reference coordinate is calculated. The straight-line distance is then corrected based on the navigation channel and obstacle distribution to obtain the actual reachable distance. Candidate auxiliary vessels whose actual reachable distance exceeds the preset shipborne relative positioning perception threshold are eliminated. The shipborne relative positioning perception threshold refers to the maximum distance standard used to determine whether a candidate auxiliary vessel has the capability to participate in collaborative positioning in a scenario where the positioning of an offshore wind power maintenance vessel fails. It is comprehensively set based on performance parameters such as the effective detection and transmission range of the shipborne relative positioning equipment, environmental characteristics such as the navigation channel, obstacle visibility, and wind and waves in the target sea area, as well as the characteristics of the maintenance vessel, such as its speed and steering response.

[0144] The remaining candidate auxiliary vessels are sorted from highest to lowest based on their positioning confidence scores. If multiple vessels have the same positioning confidence score, they are sorted again from closest to furthest based on their actual reachability from the vessel whose positioning has failed. A priority list of auxiliary positioning vessels is generated and key information of each vessel is marked, including positioning confidence score, actual reachability, and navigation status.

[0145] According to the priority list, a preset number of top-ranked ships are selected as auxiliary positioning ships. Cooperative positioning request commands are sent to these ships through the shipboard communication system. Data such as the last valid positioning coordinates, historical navigation trajectory, positioning failure time and current navigation status of the ships whose positioning has failed are transmitted synchronously, and the auxiliary positioning ships are waited for a response.

[0146] In a specific instance, the steps for generating the predicted positioning result and positioning information interval for a failed vessel include:

[0147] After the auxiliary positioning vessel responds to the cooperative positioning request, it collects relative position data through the shipborne relative positioning sensing equipment, including the relative distance to the failed vessel, the relative heading, and the measurement timestamp. All measurement timestamps are calibrated to ensure that the data are on the same time reference, and abnormal data with errors exceeding the allowable range after calibration are removed.

[0148] The system retrieves historical positioning coordinates, historical navigation speed, historical heading angle, and historical acceleration data from a pre-defined monitoring period prior to the positioning failure of the failed vessel. This data is combined with real-time environmental monitoring data such as current speed, wind direction, and wave height in the target sea area. A Kalman filter-based trajectory prediction model is then used to predict the theoretical navigation trajectory of the failed vessel during the positioning failure period, generating a set of estimated position coordinates for each time point on the theoretical trajectory. The Kalman filter-based trajectory prediction model is a mathematical model that integrates historical navigation data of the failed vessel with marine environmental factors, using state estimation and error correction to achieve dynamic trajectory extrapolation. This model can integrate multi-source input data in real time, continuously correct prediction deviations, and output reliable estimated positions for each time point within the positioning failure period. The pre-defined monitoring period refers to a specific time interval pre-defined before the positioning failure of the offshore wind power maintenance vessel to collect the historical navigation data required for the Kalman filter-based trajectory prediction model. The model is set comprehensively based on the minimum input requirements of the Kalman filter-based trajectory prediction model for historical data, the stability of the failed vessel's daily navigation status, the frequency of changes in the target sea area environment, and the accuracy requirements of the trajectory prediction in the maintenance scenario.

[0149] The real-time positioning coordinates of each auxiliary positioning vessel are extracted as fixed reference points. The relative position data is then substituted into a triangulation algorithm. By solving the geometric relationships of the triangles, the preliminary positioning positions of each auxiliary positioning vessel corresponding to the failed vessel are calculated, forming a preliminary positioning set. For example, let the three selected auxiliary positioning vessels be A, B, and C, with their real-time Cartesian coordinates as follows: , , The relative distances between the auxiliary positioning vessels A, B, and C and the failed vessel P are respectively , , The initial location is then determined. The calculation formula is:

[0150]

[0151]

[0152]

[0153] The spatial distance between each preliminary positioning location and the reliable estimated location in the preliminary positioning set is calculated. If the distance exceeds a preset spatial deviation threshold, it is marked as an abnormal positioning and removed from the preliminary positioning set; otherwise, it is marked as a valid positioning location to form a valid positioning subset. The preset spatial deviation threshold is the maximum permissible spatial distance standard between the preliminary positioning location and the estimated location at the corresponding time node in the coordinate set, set to filter valid preliminary positioning results and remove abnormal data. By retrieving historical navigation data from failed vessels and similar offshore wind power maintenance vessels, the maximum reasonable deviation distance between the real-time trajectory and the estimated trajectory when positioning is normal is statistically analyzed as a basic reference value. This is adjusted based on the complexity of the target sea area environment and the positioning accuracy requirements for maintenance are considered to determine the final value. A dynamic calibration mechanism is also established for continuous optimization.

[0154] The confidence scores of the auxiliary positioning vessels corresponding to each valid positioning location are extracted. Weight coefficients are assigned to each valid positioning location within the valid positioning subset. The valid positioning subsets are then fused to obtain the predicted positioning coordinates of the failed vessel. For example, the predicted positioning coordinates of the failed vessel... The calculation formula is: , ,in , These are the first in the effective location subset. The x and y coordinates of each valid positioning location in a Cartesian plane. For the first Normalized weight coefficients corresponding to each valid positioning location The value is the ratio of the confidence level of the auxiliary positioning vessel at that location to the sum of the confidence levels of all valid positioning vessels. The value range is from 1 to N, where N is the actual number of valid positioning locations in the valid positioning subset; This represents the summation of the corresponding calculation results for all valid positioning positions. Ultimately, the Cartesian coordinates of the plane can be converted into predicted positioning coordinates in latitude and longitude format through inverse projection.

[0155] Based on the trust level of failed vessels, a pre-defined trust level error level mapping rule is used to match the confidence interval of the failed vessels. Using the predicted positioning coordinates as the center, the geographical coordinate boundary range of the confidence interval of the failed vessels is obtained. The trust level error level mapping rule refers to a pre-established standardized correspondence rule that directly links the positioning trust level value of the failed vessel with the positioning error level and confidence interval parameters. This rule clearly defines the standard deviation range of the positioning error and the radius coefficient of the confidence interval corresponding to different trust level intervals, ensuring the consistency and adaptability of the confidence interval matching. By retrieving historical positioning, trust level, and actual positioning error data of similar offshore wind power maintenance vessels in the target sea area and statistically analyzing the error distribution characteristics of different trust level intervals, and combining the positioning accuracy requirements of the maintenance scenario, three trust level intervals—high, medium, and low—are divided. A corresponding standard deviation range of error and a radius coefficient of the confidence interval are matched for each level. This is organized into a structured mapping table, entered into the relevant system, and a quarterly dynamic update mechanism is established to complete the setting of the trust level error level mapping rule.

[0156] In the specific implementation, the vessel's positioning data is collected to generate a real-time driving trajectory; the alignment parameter between the trajectory and the navigation route is calculated to be 0.92; two abrupt inflection points are identified, forming a fluctuation characteristic dataset; the cumulative duration of positioning signal loss for the vessel in the current month is calculated to be 10 minutes, generating a signal loss evaluation parameter of 0.05; an evaluation system is constructed, and the weighted calculation yields a positioning confidence level of 0.88. Assuming the vessel's positioning fails, it is marked as a failed vessel, and the positioning confidence level data of the other 9 vessels in the target sea area are retrieved; 6 candidate auxiliary vessels with a confidence level higher than 0.8 are selected; the actual reachable distance between the candidate auxiliary vessels and the last effective positioning coordinates of the failed vessel is calculated, and 2 vessels exceeding the 2km shipborne relative positioning perception threshold are eliminated; the top 3 vessels are selected as auxiliary positioning vessels by ranking by confidence level. The relative position data of three auxiliary positioning vessels and the failed vessel were collected. Historical data of the failed vessel in the hour before its positioning failure was retrieved. Combined with environmental monitoring data, a Kalman filter model was used to predict the theoretical navigation trajectory. A preliminary positioning set was obtained through triangulation algorithm. Valid positioning positions were screened and fused to obtain the predicted positioning coordinates. Based on the confidence degree matching confidence interval, a confidence interval with a radius of 50m was generated with the predicted positioning coordinates as the center.

[0157] Example 2

[0158] See Figure 6 This embodiment discloses a navigation and positioning system for offshore wind power operation and maintenance vessels, including a task allocation module, a dynamic planning module, a navigation monitoring module, and an emergency response module;

[0159] The task allocation module is responsible for real-time collection of location information of target wind turbines awaiting maintenance in the target sea area, as well as location information and operational status data of offshore wind power maintenance vessels with maintenance capabilities. It constructs a list of target wind turbines and a list of maintenance vessels, and generates a sub-list of maintenance vessels for each offshore wind power maintenance vessel based on relative positional relationships and location distribution characteristics, while establishing a dynamic update mechanism. Location information of target wind turbines awaiting maintenance is collected through BeiDou positioning reference stations deployed in wind farms. The real-time location of maintenance vessels is obtained using BeiDou positioning terminals mounted on the offshore wind power maintenance vessels. The maintenance distance from each maintenance vessel to each target wind turbine is calculated, and the number of maintenance vessels is used as the cluster number to create temporary maintenance clusters, thereby constructing the sub-list of maintenance vessels. In addition, the system will rely on the wind farm remote monitoring platform and shipborne fault diagnosis terminal to continuously capture the status changes of the target wind turbines and maintenance vessels, monitor the list in real time, and trigger dynamic updates of the maintenance sub-list if there are updates. The original maintenance sub-list will be adjusted, split or merged to complete the dynamic update and regenerate the maintenance sub-list of the current offshore wind power maintenance vessel, providing accurate task guidance for the subsequent navigation and positioning process.

[0160] The dynamic programming module is responsible for generating navigation routes for each offshore wind turbine maintenance vessel based on the location distribution and maintenance priority of the target wind turbines in the maintenance sublist of each offshore wind turbine maintenance vessel, integrating the geographical coordinates of the prohibited navigation area in the target sea area, and employing a multi-objective path optimization algorithm. This process balances operational efficiency and obstacle avoidance safety, guiding the maintenance vessels to systematically traverse the target wind turbines in the sublist. First, the geographical coordinates, maintenance priority, and geographical coordinates of the prohibited navigation area in the target sea area of ​​the target wind turbines are extracted and standardized. Then, the maintenance distances between the target wind turbines are calculated, and the target wind turbines are sorted according to their maintenance priorities to generate a maintenance sequence. Next, the target wind turbines in the maintenance sequence are used as route nodes, and the initial navigation sub-route is generated by sequentially connecting each route node with the current real-time position coordinates of the offshore wind turbine maintenance vessel as the starting node. Subsequently, a safety buffer boundary is constructed by extending the geographical coordinates of the prohibited navigation area outwards by a preset safety threshold. The initial navigation sub-route is then spatially superimposed and compared with the safety buffer boundary to identify overlapping dangerous sections and correct the initial navigation sub-route. Through steps such as marking dangerous coordinates, generating detour transition coordinates, constructing detour routes, and smoothing transitions, an optimized navigation sub-route is obtained. Finally, the optimized navigation sub-routes are integrated according to the operation and maintenance execution sequence to form the navigation route for each offshore wind power operation and maintenance vessel and output to the shipborne navigation terminal.

[0161] The navigation monitoring module guides offshore wind power maintenance vessels along navigation routes, collecting their current position coordinates, speed, heading angle, and turning radius in real time. Centered on the current position coordinates, it dynamically sets and adjusts the monitoring range radius based on the speed, adding a fixed proportion of the vessel's turning radius as an expansion factor to generate a dynamic monitoring range. It accesses environmental monitoring data such as wind speed, wave height, current direction, and visibility from the wind farm's marine environmental monitoring base station, simultaneously collecting real-time traffic dynamic data such as the position, speed, heading, and vessel type of other vessels to ensure data real-time performance. Based on environmental adaptation standards for safe navigation of offshore wind power maintenance vessels, it determines the environmental safety level and identifies the distribution range of severe sea areas. A time-series tracking algorithm analyzes traffic dynamic data to generate navigation trajectories for other vessels, combining this with preset vessel safety avoidance thresholds to define the distribution range of other vessel routes. Based on the dynamic monitoring range, it integrates the severe sea areas and the distribution range of other vessel routes to form a closed electronic fence outline. The geographic coordinates of the outline vertices are marked to generate a coordinate set, which is then marked on the shipborne navigation terminal's electronic chart with specific visual identifiers to clearly define the safe navigation boundary. The system continuously compares the navigation route with the electronic fence boundary, identifies and lists illegal road segments that exceed the safe range, determines buffer coordinates based on the length of the illegal road segment, searches for safe areas around the buffer coordinates, extracts key coordinate points to form a safe coordinate set, and plans multiple alternative detour routes based on the start and end coordinates of the illegal road segment, prioritizing them. When the real-time position of the offshore wind power maintenance vessel is less than the preset safe avoidance distance from the start coordinates of the illegal road segment, the system selects a target detour route to replace the illegal road segment and updates the navigation route. The shipborne navigation terminal automatically replaces the original route and activates voice prompts, enabling proactive avoidance of severe sea conditions and navigation conflicts, ensuring route safety and dynamic adaptability.

[0162] The emergency response module is responsible for collecting real-time positioning data from each offshore wind power maintenance vessel. It simultaneously acquires real-time positioning coordinates, timestamps, and signal strength data via BeiDou positioning and GNSS-assisted positioning, and integrates this data by timestamp to generate real-time driving trajectories. A multi-dimensional positioning trust assessment system is constructed. This system retrieves the navigation routes of the corresponding offshore wind power maintenance vessels, calculates the deviation distance between the real-time driving trajectory and the navigation route segment segment, and generates a fit parameter. A sliding window algorithm is used to identify abrupt inflection points in the real-time driving trajectory and form a fluctuation characteristic dataset. Data related to positioning signal loss is statistically analyzed and weighted to generate signal loss assessment parameters. Using the fit parameter, abrupt inflection point density and average deviation amplitude, and signal loss assessment parameters as core evaluation indicators, weight coefficients are assigned, and after normalization, a weighted sum is obtained to obtain the positioning trust value for each offshore wind power maintenance vessel. An emergency response mechanism for positioning failure is established. Upon positioning failure, the positioning prediction process is automatically initiated. The failed vessel is marked, and relevant data from other offshore wind power maintenance vessels within the target sea area are retrieved. Candidate auxiliary vessels are screened according to a preset trust threshold. Actual reachable distances are calculated, and vessels that do not meet the requirements are eliminated. A priority list is generated, sorted by positioning trust and distance. A preset number of auxiliary positioning vessels are selected, and a collaborative positioning request is sent. The relative position data of the auxiliary positioning vessels is received, timestamps are calibrated, and abnormal data is eliminated. Historical navigation data of the failed vessel and real-time environmental monitoring data of the target sea area are retrieved. A predicted position coordinate set is generated using a Kalman filter-based trajectory prediction model. Using the real-time positioning coordinates of the auxiliary positioning vessels as a reference, a preliminary positioning set is obtained through triangulation. Abnormal positioning exceeding a preset spatial deviation threshold is eliminated to form a valid positioning subset. Weights are assigned to the valid positioning positions based on the trust of the auxiliary positioning vessels, and the results are fused to obtain the predicted positioning coordinates of the failed vessel. Based on the trust of the failed vessel, a confidence interval is matched using a preset trust error level mapping rule. The geographical coordinate boundary of the confidence interval is obtained with the predicted positioning coordinates as the center, ensuring the continuity and reliability of the positioning service.

[0163] Working principle and its effects:

[0164] The core working principle of this invention is based on real-time data acquisition and dynamic adaptation logic. Through the full-process collaboration of intelligent task allocation, precise route planning, navigation dynamic monitoring and positioning emergency support, it solves the efficiency, safety and reliability problems in offshore wind power operation and maintenance, and realizes the intelligent upgrade of operation and maintenance operations.

[0165] Specifically, by collecting core data on the target wind turbines and offshore wind power maintenance vessels in real time, a sub-list of vessels to be maintained is generated and dynamically updated based on maintenance distance clustering, ensuring a balanced allocation of tasks across multiple vessels and avoiding overlapping operations and resource waste; by combining wind turbine maintenance priorities and information on prohibited navigation areas, navigation routes are planned and corrected to achieve dual guarantees of efficient navigation and active obstacle avoidance; dynamic monitoring ranges are generated based on vessel navigation data, and electronic fences are constructed by integrating environmental and traffic dynamic data to correct routes that exceed safe limits in real time, adapting to dynamic risks in the sea area; a positioning trust assessment system is constructed through multi-dimensional indicators to accurately quantify positioning reliability, and when vessel positioning fails, high-trust auxiliary positioning vessels are selected, and predicted positioning results and confidence intervals are generated by combining relative positioning and trajectory prediction to ensure continuous positioning services.

[0166] In summary, this invention, through dynamic and intelligent design of the entire process, not only achieves balanced and efficient allocation of operation and maintenance tasks and proactive avoidance of navigation risks, but also solves the problem of emergency support after positioning failure, comprehensively improving the efficiency, safety and stability of offshore wind power operation and maintenance, and providing strong support for the large-scale development of the offshore wind power industry.

[0167] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A navigation and positioning method for offshore wind power operation and maintenance vessels, characterized in that, Includes the following steps: Real-time collection of location information of target wind turbines and offshore wind power maintenance vessels in the target sea area, generating and updating the maintenance sub-list of each offshore wind power maintenance vessel; Based on the location information and maintenance priority of the target wind turbines to be maintained in the sub-list of wind turbines to be maintained, the target wind turbines to be maintained are sorted, the order of the navigation route nodes is determined, the initial navigation sub-routes between each route node are generated, and the initial navigation sub-routes are corrected according to the geographical coordinate range of the prohibited navigation area to obtain the navigation routes of each offshore wind power maintenance vessel. The system guides offshore wind power maintenance vessels to travel along the navigation route and generates a dynamic monitoring range based on the vessel's travel data. It also connects environmental monitoring data and traffic dynamic data of the target sea area within the dynamic monitoring range to construct an electronic fence for the offshore wind power maintenance vessels. And when the navigation route of the offshore wind power operation and maintenance vessel exceeds the range of the electronic fence, the navigation route of the offshore wind power operation and maintenance vessel is updated and corrected. Real-time collection of actual positioning data of each offshore wind power operation and maintenance vessel generates real-time driving trajectory, constructs a multi-dimensional positioning trust assessment system, calculates the positioning trust level of each offshore wind power operation and maintenance vessel based on the corrected navigation route, identifies the failed vessels with missing positioning, and filters the auxiliary positioning vessels of the failed vessels in combination with the positioning trust level to generate the predicted positioning result and positioning trust interval of the failed vessels. The steps for updating and correcting the navigation routes of offshore wind power operation and maintenance vessels include: The system compares the spatial relationship between the current navigation route and the electronic fence boundary in real time, identifies illegal road segments that exceed the safety range of the electronic fence in the navigation route, records the start coordinates, end coordinates, and length of the illegal road segments, and generates a list of illegal road segments. The buffer length is dynamically adjusted based on the length of the illegal road segment. The starting coordinates of the illegal road segment are used as the reference, and the illegal road segment is divided according to the buffer length to determine the coordinates of each buffer segment. Centered on each buffer coordinate, and combined with the coordinate data of the electronic fence boundary, the key coordinate points of the buffer coordinates are retrieved, and a set of safety coordinates corresponding to each buffer coordinate is constructed. Using the starting coordinates of the illegal road section as the correction start point and the ending coordinates as the correction end point, and combining the safe coordinate set of each buffer coordinate, alternative detour routes are planned. Based on the real-time location of offshore wind power maintenance vessels and the real-time electronic fence boundary, the alternative detour routes within the dynamic monitoring range are updated, and the priority of the alternative detour routes is generated based on the route length of the alternative detour routes. When the real-time location of the offshore wind power maintenance vessel is less than the starting coordinates of the illegal section, the target detour route is selected according to the priority of the alternative detour routes, the illegal section of the navigation route is replaced, and the navigation route of the offshore wind power maintenance vessel is updated. The steps for generating the predicted positioning results and positioning information intervals of the failed vessel include: After the auxiliary positioning vessel responds to the cooperative positioning request, it collects relative position data; retrieves the historical positioning coordinates, historical sailing speed, historical heading angle data and historical acceleration of the failed vessel within the preset monitoring period before the positioning failure, and combines them with the target sea area environmental monitoring data to predict the theoretical sailing trajectory of the failed vessel within the positioning failure period, and generates the estimated position coordinate set corresponding to each time node on the theoretical sailing trajectory. The real-time positioning coordinates of each auxiliary positioning vessel are extracted as fixed reference points. Based on the relative position data, the preliminary positioning positions of each auxiliary positioning vessel of the failed vessel are calculated by solving the geometric relationship of triangles, thus forming a preliminary positioning set. Calculate the spatial distance between each preliminary location and the reliable estimated location in the preliminary location set, identify the effective location, and form an effective location subset; The confidence scores of the auxiliary positioning vessels corresponding to each effective positioning location are extracted, weight coefficients are assigned to each effective positioning location in the effective positioning subset, and fusion calculations are performed to obtain the predicted positioning coordinates of the failed vessels. Based on the trust level of the failed vessel, the confidence interval of the failed vessel is matched by a preset trust error level mapping rule, and the geographical coordinate boundary range of the confidence interval of the failed vessel is obtained with the predicted positioning coordinates as the center.

2. The navigation and positioning method for offshore wind power operation and maintenance vessels according to claim 1, characterized in that, The steps for generating and updating the list of offshore wind power maintenance vessels to be maintained include: Collect location information of target wind turbines to be maintained in the target sea area, and build a list of target wind turbines including the geographical coordinates and maintenance priority of each target wind turbine; collect the real-time location of each offshore wind power maintenance vessel capable of performing maintenance tasks, and build a list of maintenance vessels. Calculate the maintenance distance from each offshore wind power maintenance vessel in the maintenance vessel list to each target wind turbine in the target wind turbine list; The number of offshore wind power maintenance vessels in the maintenance vessel list is used as the cluster number. Based on the maintenance distance, each target wind turbine in the target wind turbine list is clustered to divide temporary maintenance clusters, and then a corresponding offshore wind power maintenance vessel sub-list to be maintained is constructed. The system monitors the target wind turbine list and the maintenance vessel list in real time. If the target wind turbine list or the maintenance vessel list is updated, the system will trigger a dynamic update of the maintenance sub-list and regenerate the maintenance sub-list of the current offshore wind power maintenance vessels.

3. The navigation and positioning method for offshore wind power operation and maintenance vessels according to claim 1, characterized in that, The steps for obtaining the navigation routes of each offshore wind power operation and maintenance vessel include: Extract the geographic coordinates and maintenance priorities of all target wind turbines to be maintained from the maintenance sublist of each offshore wind power maintenance vessel, and simultaneously retrieve the geographic coordinate range of the prohibited navigation area. Calculate the maintenance distance between each target wind turbine in the maintenance sublist, and sort the target wind turbines according to their maintenance priority to generate a maintenance sequence. Each wind turbine to be maintained in the maintenance sequence is used as a route node of the navigation route, and the current real-time position coordinates of the offshore wind power maintenance vessel are used as the starting route node of the navigation route. Following the order of the operation and maintenance sequence, each route node is connected sequentially to generate an initial navigation sub-route between adjacent route nodes; Based on the geographical coordinates of each prohibited navigation area, the safe buffer boundary of the prohibited navigation area is constructed by extending the distance corresponding to the preset safety threshold outward. Each initial navigation sub-route is spatially superimposed and compared with the safety buffer boundary of the corresponding prohibited navigation area to identify overlapping dangerous sections, correct the initial navigation sub-route, and obtain the optimized navigation sub-route. The optimized navigation subroutines are integrated according to the operation and maintenance sequence to form the navigation routes for each offshore wind power operation and maintenance vessel.

4. The navigation and positioning method for offshore wind power operation and maintenance vessels according to claim 3, characterized in that, The steps of identifying overlapping dangerous segments, correcting the initial navigation sub-route, and obtaining an optimized navigation sub-route include: If the initial navigation sub-route overlaps with the safety buffer boundary, the initial navigation sub-route in the overlapping area is marked as an overlapping danger segment. The danger start coordinate is marked at the starting point of the overlapping danger segment, and the danger end coordinate is marked at the ending point of the overlapping danger segment. Based on the starting coordinates of the danger, the ending coordinates of the danger, and the geographical coordinate range of the prohibited navigation area, the starting transition coordinates of the danger starting coordinates and the ending transition coordinates of the danger ending coordinates are symmetrically generated outside the safety buffer boundary. By sequentially connecting the starting coordinates of danger, the starting transition coordinates, the ending transition coordinates, and the ending coordinates of danger, a continuous detour route is formed, which is used to replace the overlapping danger segments in the initial navigation sub-route. The non-overlapping dangerous sections of the bypass route and the initial navigation sub-route are smoothly connected to obtain the optimized navigation sub-route.

5. The navigation and positioning method for offshore wind power operation and maintenance vessels according to claim 1, characterized in that, The steps for constructing an electronic fence for offshore wind power operation and maintenance vessels include: Real-time driving data of offshore wind power operation and maintenance vessels are collected, including current position coordinates, speed, heading angle and turning radius. The monitoring range radius is dynamically set with the current position coordinates of the offshore wind power operation and maintenance vessel as the center and combined with the speed. At the same time, a fixed proportion of the vessel's turning radius is added as the range expansion amount to generate a dynamic monitoring range. Real-time access to environmental monitoring data and traffic dynamic data of other vessels within the dynamic monitoring range; Based on the environmental adaptability standards for safe navigation of offshore wind power maintenance vessels, identify severe sea areas that exceed the environmental adaptability standards, and divide the distribution range of severe sea areas based on the spatial distribution characteristics of these areas. Trajectory analysis is performed on traffic dynamic data to generate the navigation trajectory line of each vessel, and the distribution range of other vessel routes is divided by combining the preset vessel safety avoidance threshold. Based on the dynamic monitoring range, the distribution range of severe sea areas and the distribution range of other vessel routes are included in the boundary constraints to form the outline of the electronic fence.

6. The navigation and positioning method for offshore wind power operation and maintenance vessels according to claim 1, characterized in that, The steps for calculating the positioning confidence level of each offshore wind power operation and maintenance vessel include: Collect actual positioning data of each offshore wind power operation and maintenance vessel, including real-time positioning coordinates, positioning timestamps and positioning signal strength data, sort and integrate the actual positioning data according to the positioning timestamp order, and generate real-time driving trajectory; Retrieve the corrected navigation route of the corresponding offshore wind power operation and maintenance vessel, calculate the vertical deviation distance and cumulative deviation distance between the real-time driving trajectory and the corresponding navigation route segment segment by segment, and generate the fitting degree parameter of each navigation route segment according to the ratio of the cumulative deviation distance to the distance of the navigation route segment. Identify abrupt inflection points in the real-time driving trajectory, record the location coordinates, location timestamp, and deviation from the navigation route for each abrupt inflection point, and integrate them to form a fluctuation characteristic dataset; The cumulative duration of positioning signal loss for each offshore wind power maintenance vessel, the longest duration of a single loss, and the total frequency of loss were statistically analyzed, and signal loss assessment parameters were generated through weighted calculation. Using fitting degree parameters, the density of abrupt change inflection points and average deviation amplitude in the fluctuation characteristic dataset, and signal loss assessment parameters as core evaluation indicators, a multi-dimensional positioning trust evaluation system is constructed, and weight coefficients are assigned to each core evaluation indicator. After normalizing each core evaluation indicator, it is substituted into the multi-dimensional positioning trust evaluation system, and a weighted summation is performed according to the weight coefficients to obtain the positioning trust value of each offshore wind power operation and maintenance vessel.

7. The navigation and positioning method for offshore wind power operation and maintenance vessels according to claim 1, characterized in that, The step of filtering auxiliary positioning vessels for the failed vessels based on positioning trust levels includes: When the positioning of a certain offshore wind power operation and maintenance vessel fails, it is marked as a failed vessel, and the real-time positioning confidence value, current positioning coordinates and navigation status data of all other offshore wind power operation and maintenance vessels in the target sea area are retrieved in real time. A preset trust threshold for auxiliary positioning vessels is set, and offshore wind power operation and maintenance vessels with a positioning trust level higher than the trust threshold are selected as candidate auxiliary vessels to form a candidate vessel list. Using the last valid positioning coordinates of the failed vessel as the reference coordinates, calculate the actual reachable distance between each candidate auxiliary vessel and the reference coordinates, and eliminate candidate auxiliary vessels whose actual reachable distance exceeds the preset shipborne relative positioning perception threshold. The remaining candidate auxiliary vessels are sorted from high to low according to their positioning confidence scores, and a preset number of offshore wind power operation and maintenance vessels are selected as auxiliary positioning vessels according to the sorting.

8. A navigation and positioning system for offshore wind power operation and maintenance vessels, characterized in that, The method for implementing any one of claims 1-7 includes a task allocation module, a dynamic planning module, a navigation monitoring module, and an emergency response module; The task allocation module is used to collect the location information of the target wind turbines and offshore wind power maintenance vessels in the target sea area in real time, and generate and update the maintenance sub-list of each offshore wind power maintenance vessel. The dynamic planning module determines the order of the navigation route nodes based on the location information and maintenance priority of the target wind turbines in the maintenance sublist, generates the initial navigation sub-route between each route node, and corrects the initial navigation sub-route according to the geographical coordinate range of the prohibited navigation area to obtain the navigation route of each offshore wind power maintenance vessel. The navigation monitoring module is used to generate a dynamic monitoring range based on the navigation data of offshore wind power maintenance vessels, access environmental monitoring data and traffic dynamic data of the target sea area within the dynamic monitoring range, and construct an electronic fence for offshore wind power maintenance vessels. And when the navigation route of the offshore wind power operation and maintenance vessel exceeds the range of the electronic fence, the navigation route of the offshore wind power operation and maintenance vessel is updated and corrected. The emergency response module is used to collect the actual positioning data of each offshore wind power operation and maintenance vessel in real time, generate real-time driving trajectory, construct a multi-dimensional positioning trust assessment system, calculate the positioning trust level of each offshore wind power operation and maintenance vessel based on the corrected navigation route, identify the failed vessels with missing positioning, and filter the auxiliary positioning vessels of the failed vessels in combination with the positioning trust level, so as to generate the predicted positioning result and positioning trust interval of the failed vessels.

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