A design method for refined inspection of offshore wind turbine pods based on cooperation between aircraft and boat

Abstract

The present invention discloses a method for designing a refined inspection scheme for an offshore wind power pod based on the cooperation of a motorboat. The actual position information of a drone and an unmanned boat is obtained through the kinematic equation of the motorboat cooperative system, and the inspection waypoints of the offshore wind turbine pod to be inspected are obtained according to the offshore wind power pod to be inspected. The inspection path is jointly planned for the unmanned boat and the drone through the main navigation waypoints and the subordinate waypoints, so as to avoid the storage resource occupation caused by repeatedly setting the waypoints; based on the motion model of the virtual unmanned boat and the virtual drone, the position reference signal of the motorboat cooperative system is obtained according to the inspection waypoints; the inspection relative azimuth is obtained according to the actual position information and the position reference signal, and the controller is designed according to the inspection relative azimuth to realize the inspection task of the offshore wind power pod. The present invention avoids the high optimization calculation cost and time consumption problems, can quickly make adjustments and decisions for complex and changeable marine environments and different task scenarios, and can update the position and attitude information of the cooperative system in real time to effectively realize path planning and adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of motor-vessel coordinated guidance and control, and in particular to a design method for a refined inspection scheme of an offshore wind power pod based on motor-vessel coordination. Background Art

[0002] Wind power generation has attracted widespread attention as a clean energy source that can replace fossil fuels. The key equipment of wind power generation technology is the wind turbine, which converts wind energy into electrical energy indirectly by capturing wind power to drive the blades to rotate. Wind turbines do not exist alone, but are installed in wind farms consisting of multiple wind turbines [1]. According to the different installation environments of wind turbines, wind farms can be further divided into land wind farms and offshore wind farms [2]. Compared with land wind farms, offshore wind farms can obtain more stable and strong wind resources and are not restricted by land use requirements, which has obvious advantages. However, offshore wind farms face some harsh environmental conditions, such as sea breeze, salt spray, freezing, etc. These factors affect the safety and reliability of wind turbine equipment. Therefore, it is crucial to carry out regular inspection and maintenance of wind farms.

[0003] Traditional offshore wind farm inspection methods mainly include manual inspection and remote sensing inspection. Manual inspection refers to technicians visually inspecting various parts of the wind turbine by taking an inspection ship or helicopter to the tower. Although this method is relatively direct, its execution process is time-consuming and labor-intensive, and there are certain safety risks and operational limitations. Although remote sensing inspection saves time and human resources and achieves coverage of a large area of ​​wind farms, it is limited by resolution and cannot perform refined inspections, and there are also certain limitations. In order to solve the problems of manual risks and operational limitations in the inspection process and improve inspection efficiency, many advanced unmanned system technologies have been introduced into the design of offshore wind farm inspection solutions. An existing framework for using drones to inspect wind turbines in offshore wind farms [3] is available. This framework transforms the problem of drone inspection of offshore wind farms into a configuration optimization problem and a fleet path planning problem. Then, through greedy algorithms, approximate dynamic programming algorithms, heuristic algorithms, etc., the configuration optimization problem and the fleet path planning problem are approximately solved to obtain the number of drones required in the wind farm and the optimal fleet inspection path. However, this framework only abstracts the wind turbines that need to be inspected as particles and only considers the path planning problem at a macro level, without fully considering the refinement and engineering practicality issues.

[0004] In addition, in the existing autonomous inspection schemes for offshore wind farms, the wind farm is usually abstracted as a two-dimensional plane, and the offshore wind turbines are regarded as particles evenly distributed on the plane. The designed inspection scheme aims to solve the problem of optimal inspection path planning on this plane using a single or multiple intelligent devices. These intelligent devices are mainly unmanned ships or drones, which replace traditional inspection methods by carrying cameras, sensors, thermal imagers and other equipment [4,5]. However, the inspection paths designed by the existing schemes do not effectively take into account the actual conditions such as the wind turbine posture and the prevailing main wind direction, and cannot comprehensively and finely detect the different equipment of the wind turbine. In addition, there are certain limitations to using only a single type of intelligent device (such as unmanned ships, drones) for inspection.

[0005] Based on the above analysis, the existing offshore wind farm inspection scheme design has the following four defects:

[0006] 1. The existing inspection scheme regards the wind turbine as a particle and only considers its plane position information to design the inspection route. It does not fully consider factors such as wind turbine posture, hub height, and prevailing main wind direction in the design of the inspection scheme;

[0007] 2. Wind turbines are generally composed of pods, blades and other parts. The existing inspection scheme simplifies them into particles, so it is impossible to design inspection routes for specific parts or equipment, making it difficult to achieve refined inspection;

[0008] 3. Only unmanned ships are used for inspection. Although unmanned ships have good cruising capabilities, they are restricted by altitude and have limited inspection vision. Only drones are used for inspection. Although drones can make up for the limited inspection vision of unmanned ships and have excellent maneuverability, they are limited by their endurance and have limited range for medium and long-distance offshore wind farms.

[0009] 4. The existing inspection scheme plans the inspection routes of unmanned ships or drones offline. It cannot quickly respond to changes in the marine environment and the differentiated needs of users, and cannot effectively adjust the equipment operating conditions in real time. Its immediacy and adaptability are poor. Summary of the invention

[0010] The present invention provides a design method for a refined inspection scheme of an offshore wind power pod based on cooperation between a motorboat and a boat, so as to overcome the above-mentioned technical problems.

[0011] In order to achieve the above object, the technical solution of the present invention is:

[0012] A method for designing a refined inspection scheme for an offshore wind turbine pod based on cooperation between a motorboat and a boat comprises the following steps:

[0013] S1: Obtain the kinematic equation of the drone-ship cooperative system to obtain the actual position information of the drone and the unmanned ship;

[0014] S2: Obtain inspection waypoints based on the offshore wind turbine nacelle to be inspected, taking into account the prevailing wind direction at sea, the wind turbine attitude and the wind turbine hub height;

[0015] The inspection waypoints include an unmanned ship inspection path obtained based on a primary navigation waypoint set and an unmanned aerial vehicle inspection path obtained based on a primary navigation waypoint set and a subordinate waypoint set;

[0016] The main navigation waypoint set is a set of waypoints set for guiding the unmanned ship and the unmanned aerial vehicle to navigate along the main forward direction; the subordinate waypoint set is a set of waypoints set for guiding the unmanned aerial vehicle to perform offshore wind turbine pod inspection operations;

[0017] S3: obtaining motion models of the virtual unmanned ship and the virtual unmanned aircraft, and obtaining a position reference signal of the aircraft-ship cooperative system according to the inspection waypoints;

[0018] S4: Obtaining the inspection relative azimuth according to the actual position information and the position reference signal, and obtaining a controller according to the inspection relative azimuth to achieve the inspection task of the offshore wind power pod.

[0019] Furthermore, the kinematic equation of the vehicle-vessel cooperative system described in S1 is expressed as

[0020]

[0021]

[0022] Where: x s ,y s ,ψ s Respectively represent the unmanned ship in the preset coordinate system OE X E Y E Z u is the horizontal coordinate, vertical coordinate and heading angle of the position under s ,v s ,r s They represent the unmanned ship in the preset coordinate system OS X S Y S Z The forward speed, drift speed and heading angular velocity under x a ,y a ,z a Respectively represent the drone in the preset coordinate system OE X E Y E Z The horizontal coordinate, vertical coordinate and vertical coordinate of the position under φ a Indicates that the drone orbits the coordinate system OE X E Y E Z Roll angle under θa Indicates that the drone orbits the coordinate system OE X E Y E Z The pitch angle at the bottom; ψ a Indicates that the drone orbits the coordinate system OE X E Y E Z The heading angle below; u a Indicates that the drone is in the preset coordinate system OA X A Y A Z The forward speed under v a Indicates that the drone is in the coordinate system OA X A Y A Z The crosswind speed under the a Indicates that the drone is in the coordinate system OA X A Y A Z Climbing speed under a Represents the drone orbiting the coordinate system OA X A Y A Z Rolling angular velocity; q a Represents the drone orbiting the coordinate system OA X A Y A Z The pitch angular velocity of the drone around the coordinate system OA X A Y A Z The heading angular velocity.

[0023] Furthermore, the S3 specifically includes the following steps:

[0024] S31: Obtain the motion model of the virtual unmanned ship and the virtual unmanned aerial vehicle, the expression of the motion model of the virtual unmanned ship and the virtual unmanned aerial vehicle is:

[0025]

[0026] Where: k = s, a represents the general term for virtual drones and virtual unmanned ships, that is, when k is s, it represents a virtual unmanned ship, and when k is a, it represents a virtual drone; x kd ,y kd ,ψ kd Respectively represent the position reference coordinates and reference heading angle of the virtual unmanned ship / unmanned aerial vehicle; z ad Indicates the reference altitude of the drone; z H Indicates the planned flight altitude; u kd ,r kd They represent the forward speed and heading angular velocity of the virtual unmanned ship / UAV respectively;

[0027] S32: Setting the planned speed u of the virtual unmanned ship according to the unmanned ship inspection path sd , and according to the planned speed u of the virtual unmanned ship sd Obtain the position reference signal and total sailing time of the virtual unmanned ship;

[0028] The total flight time includes the straight track flight time and the curved track flight time;

[0029] And the expression of the straight line trajectory navigation time is

[0030]

[0031]

[0032] Where: D A-Aarcin ,D Aarcout-A are all expressed as the length of the straight line trajectory; u sd Indicates the planned speed of the virtual unmanned ship; Indicates the straight line trajectory D A-Aarcin the time taken; Indicates the straight line trajectory D Aarcout-A the time taken;

[0033] The expression of the curvilinear trajectory navigation time is:

[0034]

[0035] Where: Δφ (i) Indicates the main navigation waypoint arrive Steering deviation angle; Indicates the main navigation waypoint Set turning radius;

[0036] S33: Obtaining the planned speed u of the virtual drone according to the total flight time ad , and the planned speed u of the virtual drone ad It is obtained by dividing the total distance of the drone inspection path by the total flight time;

[0037] The planned speed u of the virtual UAV ad The motion model of the virtual UAV is introduced to obtain the position reference signal of the virtual unmanned ship.

[0038] Furthermore, in S4, the expression for obtaining the inspection relative azimuth according to the actual position information and the position reference signal is:

[0039]

[0040] Where:kr Indicates the inspection relative azimuth between the ship-vessel cooperative system and the virtual unmanned ship / drone;

[0041] Furthermore, the S2 specifically includes the following steps:

[0042] S21: Based on the set mission requirements and navigation plan, the current wind turbine attitude is obtained according to the prevailing wind direction at sea, and the main navigation waypoints of the offshore wind turbine pod to be inspected are defined according to the current wind turbine attitude and the wind turbine hub height. With slave waypoints To obtain the main navigation waypoint set A and the subordinate waypoint set B;

[0043] The expressions of the main navigation waypoint set A and the subordinate waypoint set B are as follows:

[0044]

[0045]

[0046] Where: m, n represent the number of main navigation waypoints and subordinate waypoints respectively; represents the i-th main navigation waypoint; represents the jth dependent waypoint;

[0047] S22: Acquire inspection waypoints according to the main navigation waypoint set A and the subordinate waypoint set B;

[0048] The inspection waypoints include an unmanned ship inspection path obtained based on a primary navigation waypoint set and an unmanned aerial vehicle inspection path obtained based on a primary navigation waypoint set and a subordinate waypoint set;

[0049] The unmanned ship inspection path includes an unmanned ship straight track path and an unmanned ship curved track path, which is expressed as

[0050]

[0051] Where: They respectively represent the starting waypoint and the ending waypoint of any straight line trajectory of the unmanned ship inspection path; They respectively represent the starting waypoint and the ending waypoint of another straight line trajectory of the unmanned ship inspection path; Indicates the i-th main navigation waypoint The starting virtual waypoint and the ending virtual waypoint of the two segments of the curve trajectory obtained nearby;

[0052] The inspection path of the UAV includes a dominant straight line trajectory and a dominant curve trajectory obtained based on the main navigation waypoints and a subordinate straight line trajectory and a subordinate curve trajectory obtained based on the subordinate waypoints;

[0053] The dominant straight line trajectory and the dominant curved trajectory are obtained by sequentially connecting virtual waypoints obtained by vertically mapping the waypoints of the unmanned ship inspection path according to the preset UAV flight altitude;

[0054] The subordinate straight line trajectory and the subordinate curved line trajectory are obtained by sequentially connecting the subordinate waypoints according to the preset UAV flight altitude;

[0055] Then the UAV inspection path is expressed as

[0056]

[0057] Where: Respectively Mapped virtual waypoints for primary navigation waypoints; Respectively represent the waypoints at both ends of the dominant straight line trajectory; Indicates that according to the i-th main navigation waypoint The obtained starting mapped virtual waypoint and ending mapped virtual waypoint of the dominant curve trajectory; Respectively represent the j-1th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the jth subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the j+1th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the j+2th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Indicates the starting and ending waypoints of any UAV's subordinate straight line trajectory.

[0058] Beneficial effects: The present invention provides a design method for a refined inspection scheme for an offshore wind turbine pod based on motorboat collaboration, which obtains the actual position information of the UAV and the unmanned boat by constructing the kinematic equation of the motorboat collaborative system, so that the unmanned boat can sail in the waters near the wind turbine to provide flight guarantee and technical support for the UAV, making up for the lack of the UAV's endurance and helping the UAV to expand its communication range; and by considering the prevailing main wind direction at sea, the attitude of the wind turbine and the height of the wind turbine hub, the inspection waypoints of the offshore wind turbine pod to be inspected are obtained, and the position reference signals for the unmanned boat are planned through the main navigation waypoints. The position and attitude reference information of the UAV are jointly planned by the main navigation waypoints and the subordinate waypoints to avoid the storage resource occupation caused by the repeated setting of waypoints, and at the same time, the refined inspection path acquisition of the offshore wind farm is realized; based on the motion model of the virtual unmanned boat and the virtual UAV, the position reference signal of the motorboat collaborative system is obtained according to the inspection waypoints; the inspection relative azimuth is obtained according to the actual position information and the position reference signal, and the controller is obtained according to the inspection relative azimuth to realize the inspection task of the offshore wind turbine pod. The present invention avoids the high optimization calculation cost and time consumption problems, can quickly make adjustments and decisions for complex and changeable marine environments and different mission scenarios, update the position and posture information of the collaborative system in real time, and effectively plan and adjust the path according to the updated data signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0060] Figure 1 It is a flow chart of the design method of the refined inspection scheme of the offshore wind power pod based on the cooperation of the aircraft and the boat of the present invention;

[0061] Figure 2 This is a schematic diagram of the offshore wind turbine structure and the ship-machine cooperative pod inspection in this embodiment;

[0062] Figure 3 This is a schematic diagram of the refined inspection and guidance principle of the offshore wind power pod based on the cooperation of the aircraft and boat in this embodiment;

[0063] Figure 4 It is a two-dimensional wind field diagram under the test environment in this embodiment;

[0064] Figure 5 This is a top view of the route planning for the coordinated inspection of a 4×4 offshore wind farm wind turbine nacelle by a machine and a ship in this embodiment;

[0065] Figure 6This is a side view of the route planning for the coordinated inspection of the first row of fan nacelles by the aircraft and ship in this embodiment;

[0066] Figure 7 A three-dimensional diagram of the route planning for the coordinated inspection of a single wind turbine pod by a machine and a ship in this embodiment;

[0067] Figure 8 This is a simulation diagram of the heading reference signal of the unmanned ship / unmanned aerial vehicle in this embodiment;

[0068] Fig. 9 This is a flowchart of the refined inspection and guidance process of the offshore wind power pod coordinated by the machine and ship in this embodiment. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] This embodiment provides a design method for a refined inspection scheme for an offshore wind turbine pod based on cooperation between a motorboat and a motorboat. Figure 1 As shown, the following steps are included:

[0071] S1: Obtain the kinematic equation of the vehicle-vessel cooperative system to obtain the actual position information of the UAV and the unmanned ship; specifically, the expression of the kinematic equation of the vehicle-vessel cooperative system is:

[0072]

[0073]

[0074] Where: x s ,y s ,ψ s They represent the unmanned ship in the preset coordinate system OE X E Y E Z u is the horizontal coordinate, vertical coordinate and heading angle of the position under s ,v s ,r s They represent the unmanned ship in the preset coordinate system OS X S Y S Z The forward speed, drift speed and heading angular velocity under x a ,y a ,z a Respectively represent the drone in the preset coordinate system OEX E Y E Z The horizontal coordinate, vertical coordinate and vertical coordinate of the position under φ a Indicates that the drone orbits the coordinate system OE X E Y E Z Roll angle under θ a Indicates that the drone orbits the coordinate system OE X E Y E Z The pitch angle at the bottom; ψ a Indicates that the drone orbits the coordinate system OE X E Y E Z The heading angle below; u a Indicates that the drone is in the preset coordinate system OA X A Y A Z The forward speed under v a Indicates that the drone is in the coordinate system OA X A Y A Z The crosswind speed under the a Indicates that the drone is in the coordinate system OA X A Y A Z Climbing speed under a Represents the drone orbiting the coordinate system OA X A Y A Z Rolling angular velocity; q a Represents the drone orbiting the coordinate system OA X A Y A Z Pitch angular velocity; r a Represents the drone orbiting the coordinate system OA X A Y A Z The angular velocity of heading, where OE X E Y E Z 、OS X S Y S Z and OA X A Y A Z They are the earth coordinate system, the attached coordinate system of the unmanned ship and the attached coordinate system of the unmanned aerial vehicle respectively;

[0075] S2: Obtain inspection waypoints based on the offshore wind turbine nacelle to be inspected, taking into account the prevailing wind direction at sea, the wind turbine attitude and the wind turbine hub height;

[0076] The inspection waypoints include an unmanned ship inspection path obtained based on a primary navigation waypoint set and an unmanned aerial vehicle inspection path obtained based on a primary navigation waypoint set and a subordinate waypoint set;

[0077] The main navigation waypoint set is a set of waypoints set for guiding the unmanned ship and the unmanned aerial vehicle to navigate along the main forward direction; the subordinate waypoint set is a set of waypoints set for guiding the unmanned aerial vehicle to perform the inspection operation of the offshore wind turbine pod, which specifically includes the following steps:

[0078] S21: Based on the set mission requirements and navigation plan, the current wind turbine attitude is obtained according to the prevailing wind direction at sea, and the main navigation waypoints of the offshore wind turbine pod to be inspected are defined according to the current wind turbine attitude and the wind turbine hub height. With slave waypoints To obtain the main navigation waypoint set A and the subordinate waypoint set B;

[0079] Among them, the prevailing main wind direction is the wind direction that occurs most frequently at the location of the offshore wind farm at the current time (season / time). It affects the attitude of the wind turbine. When the prevailing main wind direction is the south wind, the blades of the wind turbine face south and the pod faces north. Different prevailing main wind directions make the attitude of the wind turbine different, thus affecting the selection of waypoints (in this embodiment, it is hoped that the drone will go around the pod about half a circle to complete the inspection), and the hub height, to be precise, affects the selection of the planned inspection height, and the planned inspection height is 2.5% to 5% higher than the hub height of the wind turbine to ensure that the drone can fly half a circle obliquely above the pod. By combining the drone and the unmanned boat and raising the drone to the optimal inspection altitude, it is ensured that the collaborative system has a wide inspection field of view, and by carrying cameras, sensors and other devices, the drone can set the main navigation waypoints To achieve continuous inspection of multiple offshore wind turbines in a single row or column, such as Figure 2 As shown, the offshore wind turbine nacelle wind turbine is divided into four parts: blades, hub, nacelle and tower, and subordinate waypoints are defined according to the four parts. To achieve refined inspection route design for offshore wind farms;

[0080] The expressions of the main navigation waypoint set A and the subordinate waypoint set B are as follows:

[0081]

[0082]

[0083] Where: m, n represent the number of main navigation waypoints and subordinate waypoints respectively; represents the i-th main navigation waypoint; represents the jth dependent waypoint;

[0084] S22: Acquire inspection waypoints according to the main navigation waypoint set A and the subordinate waypoint set B;

[0085] The inspection waypoints include an unmanned ship inspection path obtained based on a primary navigation waypoint set and an unmanned aerial vehicle inspection path obtained based on a primary navigation waypoint set and a subordinate waypoint set;

[0086] Among them, the main navigation waypoint set A is used to plan the navigation trajectory of the unmanned ship, and the main navigation waypoint set A and the subordinate waypoint set B jointly plan the flight trajectory for the drone. Specifically, take the union of waypoint sets A and B, and record R=A∪B; then sort the waypoints in the new waypoint set R according to the main forward direction; finally, use the sorted waypoint set R to plan a reference path for the drone. An example of the main forward direction is: for example, inspecting an offshore wind farm with 4 rows and 4 columns, according to the task requirements, the motor ship (boat) system sails from the lower left corner of the wind farm in a serpentine shape (first row from left to right → second row from right to left → third row from left to right → fourth row from right to left) and finally reaches the upper left corner of the wind farm. This serpentine route is the set main forward direction;

[0087] The unmanned ship inspection path includes an unmanned ship straight track path and an unmanned ship curved track path, which is expressed as

[0088]

[0089] Where: They respectively represent the starting waypoint and the ending waypoint of any straight line trajectory of the unmanned ship inspection path; They respectively represent the starting waypoint and the ending waypoint of another straight line trajectory of the unmanned ship inspection path; Indicates the i-th main navigation waypoint The starting virtual waypoint and the ending virtual waypoint of the two segments of the curve trajectory obtained nearby;

[0090] The inspection path of the UAV includes a dominant straight line trajectory and a dominant curve trajectory obtained based on the main navigation waypoints and a subordinate straight line trajectory and a subordinate curve trajectory obtained based on the subordinate waypoints;

[0091] The dominant straight line trajectory and the dominant curved trajectory are obtained by sequentially connecting virtual waypoints obtained by vertically mapping the waypoints of the unmanned ship inspection path according to the preset UAV flight altitude;

[0092] The subordinate straight line trajectory and the subordinate curved line trajectory are obtained by sequentially connecting the subordinate waypoints according to the preset UAV flight altitude;

[0093] Then the UAV inspection path is expressed as

[0094]

[0095] Where: Respectively Mapped virtual waypoints for primary navigation waypoints; Respectively represent the waypoints at both ends of the dominant straight line trajectory; Indicates that according to the i-th main navigation waypoint The obtained starting mapped virtual waypoint and ending mapped virtual waypoint of the dominant curve trajectory; Respectively represent the j-1th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the jth subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the j+1th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the j+2th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Indicates the starting waypoint and the ending waypoint of any UAV subordinate straight line trajectory, that is, the ending virtual waypoint of any subordinate curve trajectory is connected with the starting virtual waypoint of the adjacent subordinate curve trajectory, that is, the subordinate straight line trajectory is obtained; Waypoints at both ends of one of the dominant straight line trajectories; Waypoints at both ends of another dominant straight line trajectory;

[0096] S3: obtaining motion models of the virtual unmanned ship and the virtual unmanned aircraft, and obtaining a position reference signal of the aircraft-ship cooperative system according to the inspection waypoints;

[0097] like Fig. 9 As shown, the specific steps include:

[0098] S31: Obtain the motion model of the virtual unmanned ship and the virtual unmanned aerial vehicle, the expression of the motion model of the virtual unmanned ship and the virtual unmanned aerial vehicle is:

[0099]

[0100] Where: k = s, a represents the general term for virtual drones and virtual unmanned ships, that is, when k is s, it represents a virtual unmanned ship, and when k is a, it represents a virtual drone; x kd ,y kd ,ψ kd Respectively represent the position reference coordinates and reference heading angle of the virtual unmanned ship / unmanned aerial vehicle; z ad Indicates the reference altitude of the drone; z H Indicates the planned flight altitude; ukd ,r kd They represent the forward speed and heading angular velocity of the virtual unmanned ship / drone respectively; u sd It is artificially set. kd is a function of time t;

[0101] Specifically, in the offshore wind turbine pod inspection mission, the inspection path of the virtual unmanned ship is set in the waters near the wind turbine to complete the protection and support of the virtual drone inspection operation. The virtual drone rises to the planned flight altitude and sails about half a circle around the offshore wind turbine. In this mission, the planned flight altitude of the drone is the optimal flight altitude z H , which is usually set manually, and its value is 2.5% to 5% higher than the hub height of the wind turbine. The selection of the main navigation waypoint set A mainly considers that the unmanned ship can sail in the safe waters outside or inside the offshore wind farm; the selection of the subordinate waypoint set B is to ensure that the UAV can bypass the top of the wind turbine to inspect the pod when approaching a single wind turbine, and ensure that it flies in a safe airspace larger than the blade radius. The reference path generation of the virtual unmanned ship is globally continuous, while the reference route of the virtual UAV is stage-by-stage continuous. This is because due to the limitation of the UAV's endurance, after continuously inspecting multiple wind turbines in a single row or column, it is necessary to land back on the unmanned ship for power replenishment, and then take off again when inspecting the next row / column of wind turbines;

[0102] S32: Setting the planned speed u of the virtual unmanned ship according to the unmanned ship inspection path sd , and according to the planned speed u of the virtual unmanned ship sd Obtain the position reference signal and total sailing time of the virtual unmanned ship;

[0103] The total flight time includes the straight track flight time and the curved track flight time;

[0104] Specifically, Figure 3 USV represents a real unmanned ship, UAV represents a real drone, LVS represents a virtual unmanned ship, and LVA represents a virtual drone. The three waypoints are selected by the unmanned ship. For example, the inspection path obtained by the virtual unmanned ship is roughly This path can be considered as a straight line trajectory at both ends With a curved trajectory Composition, the corresponding flight time for the straight track part

[0105] And the expression of the straight line trajectory navigation time is

[0106]

[0107]

[0108] Where: D A-Aarcin ,D Aarcout-A are all expressed as the length of the straight line trajectory; u sd Indicates the planned speed of the virtual unmanned ship; Indicates the straight line trajectory D A-Aarcin the time taken; Indicates the straight line trajectory D Aarcout-A the time taken;

[0109] For curved trajectories Sailing time Its expression is

[0110]

[0111] Where: Δφ (i) Indicates the main navigation waypoint arrive Steering deviation angle; Indicates the main navigation waypoint Set turning radius;

[0112] Order three parts of time The sum of arrive The sailing time of each section is added together to get the total sailing time;

[0113] S33: Obtaining the planned speed u of the virtual drone according to the total flight time ad , and the planned speed u of the virtual drone ad It is obtained by dividing the total distance of the drone inspection path by the total flight time;

[0114] Specifically, by sequentially placing each waypoint (such as ) and turning waypoints (such as ) are added together, and then the total distance of the logical virtual drone is divided by the total flight time, that is, the planned speed u of the virtual drone is estimated and obtained. ad The value of

[0115] The planned speed u of the virtual UAV ad Bring in the motion model of the virtual drone and obtain the position reference signal of the virtual unmanned ship;

[0116] S4: obtaining an inspection relative azimuth according to the actual position information and the position reference signal, and obtaining a controller according to the inspection relative azimuth to achieve an inspection task of the offshore wind turbine pod;

[0117] Specifically, the expression for obtaining the inspection relative azimuth according to the actual position information and the position reference signal is:

[0118]

[0119] Where: kr Indicates the inspection relative azimuth between the ship-vessel cooperative system and the virtual unmanned ship / drone;

[0120] And based on the obtained relative azimuth of the inspection, the corresponding controller can be designed through the existing control algorithm to realize the inspection task of the offshore wind turbine pod, and the existing control algorithm at least includes a simple adaptive neural robust control algorithm or an adaptive dynamic sliding mode control algorithm. The method of obtaining the controller is based on the relative position, attitude error and relative azimuth of the inspection between the aircraft-ship collaborative system and the virtual unmanned ship / unmanned aircraft, and is obtained through the existing control algorithm design. It is not the invention point of the present application and will not be repeated here.

[0121] In order to verify the effectiveness of the design method of the refined inspection scheme of the offshore wind turbine pod based on the cooperation of the motorboat proposed in this embodiment, a 4×4 offshore wind farm will be taken as the research object, and the numerical simulation experiment will be carried out using the MATLAB platform. The 16 wind turbines inside the wind farm are of the same size and specifications. Among them, the blade radius of the wind turbine is 40 meters, the hub height is 70 meters, and the distance between two adjacent wind turbines is 600 meters. The test environment interference is as follows: The prevailing main wind direction in the sea area where the wind farm is located is south wind, and the wind speed is 7.20 meters / second. Figure 4 The figure shows a two-dimensional wind field diagram under the test environment. The two-dimensional wind field is generated using the method introduced in reference [6].

[0122] According to the above conditions, select the planned speed u of the logical virtual ship sd The total flight time is calculated to be 8 knots (about 4.12 m / s), and the total flight time is about 3100 seconds. The planned speed u of the logical virtual drone is estimated. ad is 5.58 m / s; the planned flight altitude of the UAV is z H Set it to 72 meters; set the main navigation waypoint set A and the slave waypoint set B as follows:

[0123] A={(0,0),(100,0),(300,100),(3000,100),(3000,700),(300,700),(300,1300),(3000,1300),(3000,1900),(300,1900),(0,1700)}

[0124]

[0125] like Figures 5 to 8As shown in FIG. 1 , the inspection path design result of the offshore wind turbine pod inspection operation under the above test conditions using the method of the present invention is given. Figure 5 As shown in the figure, the selection of waypoints fully considers the prevailing wind direction at the offshore wind farm. The virtual unmanned ship and virtual drone can accurately plan a continuous inspection path for the ship-machine collaborative inspection system based on the selected waypoint information. Figure 6 to Figure 7 The route planning details of the pod inspection mission for the first row of wind turbines and a single wind turbine are given respectively. Among them, the inspection route of the unmanned boat is designed in the vicinity of the periphery or interior of the wind farm. The drone keeps synchronization with the inspection path of the unmanned boat when it is far away from the wind turbine, and the inspection route is designed separately considering the safety distance when it is close to the wind turbine. The safety distance is the minimum distance to ensure that the drone does not collide with the main structure of the wind turbine, such as the blades and pod. Figure 8 The change of the reference heading angle of the collaborative system during the test is shown. Compared with the LOS guidance algorithm [7], the proposed method solves the problem that the unmanned ship and the UAV cannot generate a curved inspection path near the waypoint. The reference position and attitude information generated by the designed method is real-time, which can further calculate the relative azimuth angle of the unmanned ship and the UAV, providing conditions for the subsequent design of an adaptive control algorithm.

[0126] Through the above test results, the use of the present invention can bring three beneficial effects:

[0127] 1. The present invention solves the defect that the traditional offshore wind farm inspection task cannot realize refined inspection. The designed inspection scheme fully considers the posture information of the wind turbine and the prevailing main wind direction of the sea area where the wind farm is located, and gives full play to the advantages of both unmanned ships and unmanned aerial vehicles, which has practical significance for improving the inspection accuracy and inspection efficiency of offshore wind farms;

[0128] 2. The combined guidance method proposed in the present invention (the design method of refined inspection scheme for offshore wind turbine pod based on cooperation between aircraft and boat) can effectively solve the limitation that the traditional LOS guidance algorithm cannot be used for curved segment track planning, and at the same time effectively consider the problem of storage resource occupation, avoiding the waste of resources caused by repeated selection of waypoints;

[0129] 3. The present invention realizes the online planning of the inspection route of the collaborative system, which can be dynamically adjusted for different task scenarios and user needs. Compared with the traditional offline path planning method, it is more flexible and reduces the optimization calculation cost and calculation time, with significant engineering application value. At the same time, it provides excellent conditions for the subsequent online adaptive control algorithm design.

[0130] The documents involved in this embodiment are as follows:

[0131] [1] Li Yan, Wu Di, Hong Chang, et al. Research on optimization strategy of wind turbine layout in large offshore wind farms[J]. Solar Energy, 2020, 2020(02): 67-74.

[0132] [2] Xiang Chenxi, Xiang Kangli, Huang Xianan. Analysis of the trend of offshore wind power cost changes and its influencing factors[J]. Sustainable Energy, 2020, 10(2): 17-21.

[0133] [3]CHUNGH,MAHARJAN S,ZHANGY,etal.PlacementandRoutingOptimizationforAutomated Inspection with Unmanned Aerial Vehicles:A Study in Offshore WindFarm[J].IEEE Transactions on IndustrialInformatics,2020,17(5):3032-3043.

[0134] [4]HUANG X,WANG G,LU Y,et al.Study on a Boat-Assisted DroneInspection Scheme for the ModernLarge-Scale OffshoreWindFarm[J].IEEE SystemsJournal,2023,17(3):4509-4520.

[0135] [5]DIAS A,ALMEIDAJ,OLIVEIRAA,etal.UnmannedAerialVehicleforWind-turbine Inspection.NextStep:Offshore[C].Proceedings of theOceansConference2022,HamptonRoads,VirginiaBeach,USA,F Oct.,2022.

[0136] [6]Guoqing Zhang,Jiqiang Li,Bo Li,et al.Improved integral LOSguidance and path-following control for an unmannedrobot sailboat via therobust neural damping technique.The Journal ofNavigation,2019,72(6):1378-1398.

[0137] [7] Yu Yalei, Su Rongbin, Feng Xu, et al. Backstepping adaptive path tracking control of unmanned ship based on rapidly changing LOS[J]. Chinese Journal of Ship Research, 2019, 14(03): 163-171.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A design method for a refined inspection scheme for an offshore wind turbine pod based on cooperation between a motorboat and a boat, characterized in that: The following steps are involved: S1: Obtain the kinematic equation of the drone-ship cooperative system to obtain the actual position information of the drone and the unmanned ship; The kinematic equation of the vehicle-vessel cooperative system is expressed as Where: x s ,y s ,ψ s They represent the unmanned ship in the preset coordinate system OE X E Y E Z u is the horizontal coordinate, vertical coordinate and heading angle of the position under s ,v s ,r s They represent the unmanned ship in the preset coordinate system OS X S Y S Z The forward speed, drift speed and heading angular velocity under x a ,y a ,z a Respectively represent the drone in the preset coordinate system OE X E Y E Z The horizontal coordinate, vertical coordinate and vertical coordinate of the position under φ a Indicates that the drone orbits the coordinate system OE X E Y E Z Roll angle under θ a Indicates that the drone orbits the coordinate system OE X E Y E Z The pitch angle at the bottom; ψ a Indicates that the drone orbits the coordinate system OE X E Y E Z The heading angle below; u a Indicates that the drone is in the preset coordinate system OA X A Y A Z The forward speed under v a Indicates that the drone is in the coordinate system OA X A Y A Z The crosswind speed under the a Indicates that the drone is in the coordinate system OA X A Y A Z Climbing speed under a Represents the drone orbiting the coordinate system OA X A Y A Z Rolling angular velocity; q a Represents the drone orbiting the coordinate system OA X A Y A Z Pitch angular velocity; r a Represents the drone orbiting the coordinate system OA X A Y A Z The angular velocity of heading; S2: Obtain inspection waypoints based on the offshore wind turbine nacelle to be inspected, taking into account the prevailing wind direction at sea, the wind turbine attitude and the wind turbine hub height; The inspection waypoints include an unmanned ship inspection path obtained based on a primary navigation waypoint set and an unmanned aerial vehicle inspection path obtained based on a primary navigation waypoint set and a subordinate waypoint set; The main navigation waypoint set is a set of waypoints set to guide the unmanned ship and the unmanned aerial vehicle to navigate along the main forward direction; The subordinate waypoint set is a set of waypoints set to guide the UAV to perform offshore wind turbine pod inspection operations; S3: obtaining motion models of the virtual unmanned ship and the virtual unmanned aircraft, and obtaining a position reference signal of the aircraft-ship cooperative system according to the inspection waypoints; The specific steps include: S31: Obtain the motion model of the virtual unmanned ship and the virtual unmanned aerial vehicle. The expression of the motion model of the virtual unmanned ship and the virtual unmanned aerial vehicle is: Where: k = s, a represents the general term for virtual drones and virtual unmanned ships, that is, when k is s, it represents a virtual unmanned ship, and when k is a, it represents a virtual drone; x kd ,y kd ,ψ kd Respectively represent the position reference coordinates and reference heading angle of the virtual unmanned ship / unmanned aerial vehicle; z ad Indicates the reference altitude of the drone; z H Indicates the planned flight altitude; u kd ,r kd They represent the forward speed and heading angular velocity of the virtual unmanned ship / UAV respectively; S32: Setting the planned speed u of the virtual unmanned ship according to the unmanned ship inspection path sd , and according to the planned speed u of the virtual unmanned ship sd Obtain the position reference signal and total sailing time of the virtual unmanned ship; The total flight time includes the straight track flight time and the curved track flight time; And the expression of the straight line trajectory navigation time is Where: D A-Aarcin ,D Aarcout-A are all expressed as the length of the straight line trajectory; u sd Indicates the planned speed of the virtual unmanned ship; Indicates the straight line trajectory D A-Aarcin the time taken; Indicates the straight line trajectory D Aarcout-A the time taken; The expression of the curvilinear trajectory navigation time is: Where: Δφ (i) Indicates the main navigation waypoint arrive Steering deviation angle; Indicates the main navigation waypoint Set turning radius; S33: Obtaining the planned speed u of the virtual drone according to the total flight time ad , and the planned speed u of the virtual drone ad It is obtained by dividing the total distance of the drone inspection path by the total flight time; The planned speed u of the virtual UAV ad Bring in the motion model of the virtual drone and obtain the position reference signal of the virtual unmanned ship; S4: Obtaining the inspection relative azimuth according to the actual position information and the position reference signal, and obtaining a controller according to the inspection relative azimuth to achieve the inspection task of the offshore wind power pod.

2. The method for designing a refined inspection scheme for an offshore wind turbine pod based on cooperation between a motorboat and a motorboat according to claim 1 is characterized in that: The expression for obtaining the inspection relative azimuth angle according to the actual position information and the position reference signal in S4 is: Where: kr Indicates the relative azimuth of the inspection between the ship-vessel cooperative system and the virtual unmanned ship / drone.

3. The method for designing a refined inspection scheme for an offshore wind turbine pod based on cooperation between a motorboat and a boat according to claim 1 is characterized in that: The S2 specifically includes the following steps: S21: Based on the set mission requirements and navigation plan, the current wind turbine attitude is obtained according to the prevailing wind direction at sea, and the main navigation waypoints of the offshore wind turbine pod to be inspected are defined according to the current wind turbine attitude and the wind turbine hub height. With slave waypoints To obtain the main navigation waypoint set With dependent waypoint sets The main navigation waypoint set With dependent waypoint sets The expression is Where: m, n represent the number of main navigation waypoints and subordinate waypoints respectively; represents the i-th main navigation waypoint; represents the jth dependent waypoint; S22: Based on the main navigation waypoint set With dependent waypoint sets Get inspection waypoints; The inspection waypoints include an unmanned ship inspection path obtained based on a primary navigation waypoint set and an unmanned aerial vehicle inspection path obtained based on a primary navigation waypoint set and a subordinate waypoint set; The unmanned ship inspection path includes an unmanned ship straight track path and an unmanned ship curved track path, which is expressed as Where: They respectively represent the starting waypoint and the ending waypoint of any straight line trajectory of the unmanned ship inspection path; They respectively represent the starting waypoint and the ending waypoint of another straight line trajectory of the unmanned ship inspection path; Indicates the i-th main navigation waypoint The starting virtual waypoint and the ending virtual waypoint of the two segments of the curve trajectory obtained nearby; The inspection path of the UAV includes a dominant straight line trajectory and a dominant curve trajectory obtained based on the main navigation waypoints and a subordinate straight line trajectory and a subordinate curve trajectory obtained based on the subordinate waypoints; The dominant straight line trajectory and the dominant curved trajectory are obtained by sequentially connecting virtual waypoints obtained by vertically mapping the waypoints of the unmanned ship inspection path according to the preset UAV flight altitude; The subordinate straight line trajectory and the subordinate curved line trajectory are obtained by sequentially connecting the subordinate waypoints according to the preset UAV flight altitude; Then the UAV inspection path is expressed as Where: Respectively Mapped virtual waypoints for primary navigation waypoints; Respectively represent the waypoints at both ends of the dominant straight line trajectory; Indicates that according to the i-th main navigation waypoint The obtained starting mapped virtual waypoint and ending mapped virtual waypoint of the dominant curve trajectory; Respectively represent the j-1th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the jth subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the j+1th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Respectively represent the j+2th subordinate waypoint Virtual waypoints at both ends of the subordinate curve trajectory obtained nearby; Indicates the starting and ending waypoints of any UAV's subordinate straight line trajectory.

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