Offshore wind turbine inspection system and method based on unmanned aerial vehicle hangar

Abstract

The invention discloses an offshore wind turbine inspection system and method based on an unmanned aerial vehicle hangar, and relates to the technical field of unmanned aerial vehicle offshore inspection, and the method comprises the following steps: testing a relation function between the electric quantity consumed when an unmanned aerial vehicle flies and the wind direction and wind power, and naming the relation function as a power consumption influence function; obtaining a layout diagram of the hangar and the offshore wind turbine, and constructing a position distribution diagram through position information in the layout diagram; estimating the estimated total power consumption of the unmanned aerial vehicle flying on the inspection route based on the position distribution diagram, the wind direction and the wind power in combination with a power consumption influence function; based on the estimated total power consumption, the routing inspection time length which can be distributed to each offshore wind turbine is evaluated; the method is used for solving the problem that the inspection time of the unmanned aerial vehicle on the inspection position is insufficient due to the fact that the electric quantity planning is not accurate enough in the existing unmanned aerial vehicle maritime inspection technology.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) offshore inspection, and in particular to an offshore wind turbine inspection system and method based on an unmanned aerial vehicle (UAV) hangar. Background Art

[0002] Drone maritime inspection technology refers to the technology of using drones (unmanned aerial vehicles) to conduct inspections, monitoring and investigations in the marine field. This technology uses drones equipped with various sensors and camera equipment to conduct real-time monitoring and data collection of marine facilities, ships and marine ecological environment. Drone maritime inspection technology can be applied to marine resource surveys, marine environmental monitoring, coastline patrols, fishery monitoring and maritime rescue. It has the advantages of high efficiency, flexibility, low cost, safety and reliability, and provides new technical means and solutions for marine work.

[0003] Existing drone inspection technologies at sea usually complete inspections through manual remote control or automatic flight along a predetermined route. During the inspection process, drones cannot generate energy on their own and need to be charged in a hangar. Therefore, it is particularly important to control the power during drone inspections at sea. Accurate control of power can increase the inspection time of each inspection point to allow for more detailed inspections. If there is no power planning, only a rough inspection of the inspection points can be performed by human feel to ensure that the drone can return to the hangar safely. Existing drone inspection technologies at sea usually only evaluate power consumption based on flight mileage. Drones are affected by wind when they are running. They can save power when the wind is blowing, but save power when the wind is blowing. More electricity is consumed when flying, and the wind on the sea is usually strong, which has a more prominent impact on drones. Therefore, it is more difficult to control the power of drones. For example, in the patent application with publication number CN115185279A, an offshore wind turbine inspection method and system based on the linkage of drones and unmanned ships are disclosed. The control of the drone in this solution only stays at the basic take-off, landing and operation control, and there is no precise control of the power of the drone, resulting in the drone being unable to control the inspection time of the inspection points based on the power, which further leads to the problem of insufficiently detailed inspection of the inspection points. The existing drone offshore inspection technology also has the problem of inaccurate power planning, resulting in insufficient inspection time for the drone at the inspection location. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the prior art to at least a certain extent, by selecting an open area and conducting flight tests on a drone under different wind environments, recording the test data, and then calculating and constructing a wind power consumption relationship diagram and an angle power consumption ratio relationship diagram based on the test data, and then analyzing the influence function of the drone's power consumption and wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram, and then obtaining a layout diagram of the hangar and the offshore wind turbine, constructing a position distribution map through the position information in the layout diagram, and obtaining the wind direction and wind force on the sea surface at the same time, controlling the drone to inspect along a predetermined inspection route, and estimating the estimated total power consumption of the drone flying on the inspection route based on the position distribution map, wind direction and wind force and in combination with the power consumption influence function, and finally evaluating the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption, so as to solve the problem that the existing drone offshore inspection technology still has insufficient precision in power planning, resulting in insufficient inspection time for the drone at the inspection location.

[0005] To achieve the above objectives, in a first aspect, the present application provides an offshore wind turbine inspection method based on a drone hangar, comprising the following steps:

[0006] The relationship function between the power consumption of the UAV during flight and the wind direction and wind force is named as the power consumption influence function;

[0007] Obtain the layout diagram of the hangar and offshore wind turbines, and construct a location distribution map based on the location information in the layout diagram;

[0008] Obtain the wind direction and wind force on the sea surface, control the drone to conduct inspections along the predetermined inspection route, and estimate the total power consumption of the drone flying along the inspection route based on the location distribution map, wind direction and wind force combined with the power consumption influence function;

[0009] Evaluate the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption.

[0010] Furthermore, the relationship function between the power consumption of the drone during flight and the wind direction and wind force is tested, which is named as the power consumption influence function and includes the following sub-steps:

[0011] Select an open area and conduct flight tests on the drone in different wind conditions, and record the test data;

[0012] Calculate and construct wind power consumption relationship diagram and angle power consumption ratio relationship diagram based on test data;

[0013] Based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram, the influence function of the drone's power consumption and wind force and wind direction is analyzed.

[0014] Furthermore, an open area is selected and a flight test of the UAV is conducted under different wind conditions. The recording of the test data includes the following sub-steps:

[0015] An open area is selected, where the open area is a plain terrain and there is an open area with a diameter of the first test distance;

[0016] Get the maximum wind speed that the drone can withstand, set the starting wind speed, and take the starting wind speed to the maximum wind speed as a range, named wind speed range;

[0017] The wind force interval is evenly divided into a first test number of subintervals, which are named wind force subintervals, and the interval between two adjacent wind force subintervals is marked as a test wind force, and the starting wind force is also marked as a test wind force;

[0018] The test wind forces are numbered in the order from small to large in the wind force range, and the symbol W is used to represent the wind force. n It represents, where n∈Z+ and n is the serial number of W, Z+ represents a positive integer, and the maximum value of n is the first test quantity;

[0019] Set the wind test experiment group of the first test number, through the symbol F n Indicates that, and F n The wind force level in the experiment is W n ;

[0020] Set the flight angle, which includes the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle. The flight angle is the angle between the flight direction of the drone and the wind direction, and the flight angle increases in sequence. The first angle is 0°, the seventh angle is 180°, 0° means that the flight direction of the drone is opposite to the wind direction, which is the headwind direction, and 180° means that the flight direction of the drone is the same as the wind direction, which is the downwind direction;

[0021] Different wind force test experimental groups are tested based on the flight angle and the test data are recorded.

[0022] Further, testing different wind force test groups based on the flight angle and recording the test data includes the following sub-steps:

[0023] For F n , monitor the wind direction and wind force in the open area. When the wind force is W n When the test is completed, the UAV is controlled to fly at the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle respectively, and the flight distance is the first test distance. After the flight, the tester brings the UAV back to the starting position and performs the flight again, and each flight angle performs the first number of flights;

[0024] For each flight angle, record the power consumed by the drone from the beginning to the end of the test, marked as the test power consumption, and represented by the symbol T(n,θ), where θ is the flight angle and (n,θ) is the serial number of T, T(n,θ) represents F n The power consumption of the test when the flight angle is θ;

[0025] Calculate N1×N2, and mark the calculation result as the flight distance, where N1 is the first test distance and N2 is the first flight number.

[0026] Furthermore, calculating and constructing a wind power consumption relationship diagram and an angle power consumption ratio relationship diagram based on the test data includes the following sub-steps:

[0027] Mark the flight distance as L, calculate T(n,180°) / L, and mark the result as unit power consumption, represented by the symbol E;

[0028] W n As the X-axis, the unit power consumption as the Y-axis to establish a plane rectangular coordinate system, named wind power consumption relationship diagram, F n The corresponding W n And the unit power consumption is entered into the wind power consumption relationship diagram;

[0029] Calculate T(n,θ) / L, mark the result as power consumption per unit angle, represented by symbol EO, where θ does not include the seventh angle; calculate EO / E, mark the result as power consumption ratio, represented by symbol H(n,θ), where θ does not include the seventh angle;

[0030] A plane rectangular coordinate system is established with θ as the horizontal axis and H(n,θ) as the vertical axis, and is named as the angle power consumption proportional relationship diagram. H(n,θ) is entered into the angle power consumption proportional relationship diagram according to the corresponding θ.

[0031] Furthermore, analyzing the influence function of the power consumption of the drone and the wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram includes the following sub-steps:

[0032] Regression analysis is performed on the wind power consumption relationship diagram. The wind power consumption relationship diagram is regressed by exponential regression to obtain a wind power consumption equation. The wind power consumption equation format is WPC = a × e -b×WP , where WPC is wind power consumption efficiency, WP is wind power, a and b are constants inherent in the regression equation, and e is a natural constant;

[0033] Based on the difference of n in H(n,θ) in the angle power consumption ratio relationship diagram, the coordinate point is named as the nth coordinate point, and the angle power consumption ratio relationship diagram is subjected to regression analysis. The nth coordinate point in the angle power consumption ratio relationship diagram is regressed by linear regression to obtain the angle power consumption ratio equation. The angle power consumption ratio equation format is PCV n =c×θ+d, where PCV n is the angular power consumption ratio of the nth coordinate point, θ is the flight angle, and c and d are constants inherent in the regression equation;

[0034] Get all PCVs when θ=0° n And marked as PCO n , get PCO n The corresponding W n , with W n For the X-axis, PCO n Establish a plane rectangular coordinate system for the Y axis, named the lowest scale distribution map, and set W n And the corresponding PCO n Enter the minimum proportion distribution map;

[0035] Performing linear regression on the minimum proportion distribution graph to obtain a minimum proportion distribution equation, wherein the minimum proportion distribution equation has a format of PCO=f×WP+g, wherein PCO is the minimum proportion, and f and g are inherent constants of the regression equation;

[0036] Substitute the wind power WP into the minimum proportional distribution equation, solve for PCO, and then substitute the coordinate points (0°, PCO) and (180°, 1) into the angle power consumption proportional equation PCV n =c×θ+d, after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angle power consumption ratio;

[0037] WPC is the wind power consumption efficiency in the positive and negative wind directions. Multiplying it with PCR can estimate the wind power consumption efficiency of the drone during flight based on the angle between the flight direction of the drone and the wind direction, which is marked as the estimated power consumption efficiency. The estimated power consumption efficiency is calculated by the power consumption influence function, which is EPC=WPC×PCR=(a×e -b×WP )×(c×θ+d).

[0038] Further, obtaining a layout diagram of the hangar and the offshore wind turbines, and constructing a location distribution map using the location information in the layout diagram includes the following sub-steps:

[0039] Obtaining a layout diagram of the hangar and the offshore wind turbine, wherein the layout diagram includes the longitude and latitude of the hangar and the longitude and latitude of the wind turbine;

[0040] A plane rectangular coordinate system is established with the longitude and latitude of the hangar as the origin, due east as the X-axis, and due north as the Y-axis, and is named the location distribution map;

[0041] Based on the longitude and latitude distance calculation method, the angle and distance between the longitude and latitude of the wind turbine and the longitude and latitude of the hangar are calculated to obtain the relative angle and relative distance. The offshore wind turbine is marked on the location distribution map according to the relative angle and relative distance.

[0042] Furthermore, the wind direction and wind force on the sea surface are obtained, and the drone is controlled to perform inspections along a predetermined inspection route. The estimated total power consumption of the drone flying along the inspection route is estimated based on the location distribution map, wind direction and wind force and combined with the power consumption influence function, including the following sub-steps:

[0043] Get the wind direction and wind force on the sea surface, marked as real-time wind direction and real-time wind force respectively;

[0044] Controlling the drone to perform inspection along a predetermined inspection route, marking the inspection route in the location distribution map, wherein the inspection route is composed of a first number of straight lines, and naming a single straight line as an inspection sub-route;

[0045] The inspection sub-routes are numbered and marked with R i Indicates that, where i∈Z+ and i is the serial number of R, get R i The angle relative to the real-time wind direction is marked as the course angle and is indicated by the symbol A. i Indicates that R is obtained i The length of the route is indicated by the symbol D i Indicates that the angle of the route is determined to be the same as the flight angle;

[0046] For R i , WP is equal to the real-time wind force and θ = A i Substitute into EPC = (a × e -b×WP )×(c×θ+d), and EPC is calculated;

[0047] Calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i After analysis, the sum of the estimated sub-power consumption is calculated to obtain the estimated total power consumption.

[0048] Furthermore, evaluating the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption includes the following sub-steps:

[0049] Get the power of the drone when it takes off from the hangar, marked as take-off power, represented by the symbol PU, and get the landing power threshold of the drone. The landing power threshold is a preset value, represented by the symbol PD, which is used to ensure that the drone still has the landing power threshold after returning to the hangar. Even if there is a deviation during the flight, resulting in excessive power consumption, it can ensure that the drone can return to the hangar safely;

[0050] Calculate PU-PD, mark the result as PH, and then calculate PH-EPU to get the total power consumption of shooting, represented by the symbol PK, where EPU is the estimated total power consumption;

[0051] Substitute WP equal to the real-time wind force and θ = 90° into EPC = (a × e -b×WP )×(c×θ+d), and the calculated result is marked as the cruise power consumption efficiency, which is represented by the symbol EPD;

[0052] Get the comprehensive moving speed of the UAV, marked as Q, calculate (PK / EPD) / Q, get the total time the UAV takes to surround the offshore wind turbines, marked as TAL, then get the number of offshore wind turbines, marked as V, calculate TAL / V, and get the inspection time that can be allocated to each offshore wind turbine.

[0053] In a second aspect, the present application provides an offshore wind turbine inspection system based on a drone hangar, including an impact analysis module, a layout acquisition module, an estimated power consumption calculation module, and an inspection duration calculation module; the layout acquisition module, the estimated power consumption calculation module, and the inspection duration calculation module are respectively connected to the impact analysis module data;

[0054] The impact analysis module is used to test the relationship function between the power consumption of the drone during flight and the wind direction and wind force, which is named as the power consumption impact function;

[0055] The layout acquisition module is used to acquire the layout diagram of the hangar and the offshore wind turbines, and construct a location distribution map through the location information in the layout diagram;

[0056] The estimated power consumption calculation module is used to obtain the wind direction and wind force on the sea surface, control the drone to inspect according to the predetermined inspection route, and estimate the estimated total power consumption of the drone flying on the inspection route based on the location distribution map, wind direction and wind force and combined with the power consumption influence function;

[0057] The inspection duration calculation module is used to evaluate the inspection duration that can be allocated to each offshore wind turbine based on the estimated total power consumption.

[0058] Beneficial effects of the present invention: The present invention selects an open area and performs flight tests on a drone under different wind environments, records test data, and then calculates and constructs a wind power consumption relationship diagram and an angle power consumption ratio relationship diagram based on the test data, and then analyzes the influence function of the drone's power consumption and wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram. The advantage is that the influence of wind force and wind direction on the drone's power consumption can be obtained, and at the same time, the angle between the drone and the wind direction is added as a reference factor, which further improves the accuracy of the influence function and improves the accuracy and effectiveness of the drone power consumption analysis;

[0059] The present invention obtains a layout diagram of a hangar and offshore wind turbines, constructs a location distribution diagram through the location information in the layout diagram, obtains the wind direction and wind force on the sea surface, controls the drone to perform inspections along a predetermined inspection route, estimates the estimated total power consumption of the drone flying on the inspection route based on the location distribution diagram, wind direction and wind force and in combination with a power consumption influence function, and finally evaluates the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption. The advantage is that the estimated total power consumption required for the round-trip journey of the drone is calculated through the power consumption influence function, and the remaining power can be used for a detailed inspection near the wind turbine, and then evenly distributed to each wind turbine, which can provide a reference for the time that each wind turbine can stay at its location, thereby increasing the inspection time of the wind turbine and improving the accuracy and safety of the drone's offshore wind turbine inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a functional block diagram of the system of the present invention;

[0061] Figure 2 A schematic diagram of determining the relative angle of the present invention;

[0062] Figure 3 The wind power consumption relationship diagram of the present invention;

[0063] Figure 4 This is a graph showing the relationship between the angle power consumption ratio of the present invention;

[0064] Figure 5 PCV1 to PCV 10 Schematic diagram of

[0065] Figure 6 is the minimum ratio distribution diagram of the present invention;

[0066] Figure 7 is a schematic diagram of a location distribution map of the present invention;

[0067] Figure 8 A schematic diagram of an inspection route of the present invention;

[0068] Fig. 9 The figure is a flow chart of the steps of the method of the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] Example 1, please refer to Figure 1 As shown, the present application provides an offshore wind turbine inspection system based on a drone hangar, including an impact analysis module, a layout acquisition module, an estimated power consumption calculation module, and an inspection duration calculation module; the layout acquisition module, the estimated power consumption calculation module, and the inspection duration calculation module are respectively connected to the impact analysis module data;

[0071] The impact analysis module is used to test the relationship function between the power consumption of the UAV during flight and the wind direction and wind force, which is named as the power consumption impact function; the impact analysis module includes a flight test unit, a relationship diagram construction unit and an impact analysis unit;

[0072] The flight test unit is used to select an open area and perform flight tests on the UAV in different wind conditions, and record the test data;

[0073] The flight test unit is configured with a flight test strategy, which includes:

[0074] Select an open area, which is a plain terrain with an open area with a diameter equal to the first test distance;

[0075] Get the maximum wind speed that the drone can withstand, set the starting wind speed, and take the starting wind speed to the maximum wind speed as a range, named wind speed range;

[0076] In practical applications, the standard for open space is that there are no buildings in the area, and it is usually built in an area far away from the city. The first test distance is to ensure that the drone can move forward a certain distance in the wind without obstruction for subsequent analysis. In this embodiment, the first test distance is set to 2km, that is, a circular open space with a diameter of 2km is required as a test site; the ultimate wind force refers to the maximum wind force level at which the drone can fly, that is, the maximum tolerable wind speed in various factory indicators of the drone under normal circumstances. The ultimate wind force that drones of different manufacturers and models can withstand is different. The ultimate wind force of the drone in this embodiment is 15m / s; Under normal circumstances, there is always wind in open space, and calm and windless conditions are extremely rare, while there must be wind on the sea surface, and the wind on the sea surface is usually large, so the starting wind force is set to reduce the meaningless low wind force analysis process and speed up the test efficiency. The starting wind force in this embodiment is set to 2m / s, and the wind force range is [2m / s, 15m / s];

[0077] The wind force interval is evenly divided into a first test number of subintervals, which are named wind force subintervals, and the interval between two adjacent wind force subintervals is marked as a test wind force, and the starting wind force is also marked as a test wind force;

[0078] In practical applications, the first test quantity is set to refine the wind speed interval into multiple values ​​for test analysis to evaluate the relationship between power consumption and wind speed. The first test quantity is usually not less than 10. In this embodiment, the first test quantity is set to 10, that is, [2m / s, 15m / s] is evenly divided into 10 wind speed sub-intervals, namely [2m / s, 3.3m / s], [3.3m / s, 4.6m / s], [4.6m / s, 5.9m / s], [5.9m / s, 7.2m / s], [7.2m / s, 8.5m / s], [8.5m / s, 9.8m / s], [9.8m / s, 11.1m / s], [ 11.1m / s,12.4m / s], [12.4m / s,13.7m / s] and [13.7m / s,15m / s]. The intersection of any two wind sub-intervals is the test wind force. The test wind forces include 2m / s, 3.3m / s, 4.6m / s, 5.9m / s, 7.2m / s, 8.5m / s, 9.8m / s, 11.1m / s, 12.4m / s and 13.7m / s. The reason for not considering 15m / s is that 15m / s is the limit wind force that the drone can withstand. It is usually not recommended for drones to fly in the limit wind force to avoid accidents. Therefore, the situation of 15m / s is not considered.

[0079] The test wind forces are numbered in the order from small to large in the wind force range, and the symbol W is used to represent the wind force. nIt represents, where n∈Z+ and n is the serial number of W, Z+ represents a positive integer, and the maximum value of n is the first test quantity;

[0080] Set the first test number of wind test experimental groups, represented by the symbol F n Indicates that, and F n The wind force level in the experiment is W n ;

[0081] In practical applications, W1 to W are obtained by sorting the numbers. 10 The wind speeds are 2m / s, 3.3m / s, 4.6m / s, 5.9m / s, 7.2m / s, 8.5m / s, 9.8m / s, 11.1m / s, 12.4m / s and 13.7m / s, respectively. Ten wind force test groups are set up to obtain the wind speeds from F1 to F 10 The corresponding test wind forces are W1 to W 10 In actual testing, the wind force at the test site does not need to be strictly in accordance with the test wind force. It only needs to ensure that the deviation between the wind force and the test wind force corresponding to the wind force test experimental group does not exceed 0.5m / s. In specific analysis, the actual test wind force can be uploaded. For example, for F1, the test wind force is W1=2m / s. In actual testing, the wind force at the test site can be tested between [1.5m / s, 2.5m / s]. Assuming that the wind force at the test site is 1.9m / s during this test, W1 can be changed to 1.9m / s when entering data later.

[0082] See also Figure 2 As shown, the flight angle is set, and the flight angle includes a first angle, a second angle, a third angle, a fourth angle, a fifth angle, a sixth angle and a seventh angle. The flight angle is the angle between the flight direction of the UAV and the wind direction, and the flight angle increases in sequence. Among them, the first angle is 0°, the seventh angle is 180°, 180° represents that the flight direction of the UAV and the wind direction are opposite directions, which is the positive headwind direction, and 0° represents that the flight direction of the UAV is the same as the wind direction, which is the positive downwind direction;

[0083] In practical applications, the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle are set to 0°, 30°, 60°, 90°, 120°, 150° and 180° respectively. In this embodiment, the angle between the flight direction and the wind direction is named as the relative angle. The determination of the relative angle is as follows: Figure 2 As shown, this embodiment only considers the relationship in a two-dimensional state, and presents the determination of the relative angle in the form of a top view;

[0084] Test different wind force test groups based on flight angles and record test data;

[0085] For Fn , monitor the wind direction and wind force in the open area. When the wind force is W n When the test is completed, the UAV is controlled to fly at the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle respectively, and the flight distance is the first test distance. After the flight, the tester brings the UAV back to the starting position and performs the flight again, and each flight angle performs the first number of flights;

[0086] For each flight angle, record the power consumed by the drone from the beginning to the end of the test, marked as the test power consumption, and represented by the symbol T(n,θ), where θ is the flight angle and (n,θ) is the serial number of T, T(n,θ) represents F n The power consumption of the test when the flight angle is θ;

[0087] Calculate N1×N2, and mark the calculation result as the flight distance, where N1 is the first test distance and N2 is the first flight number;

[0088] In actual applications, real-time monitoring of wind direction and wind force is performed. n When F n In the test, the wind speed was monitored to be 4.9m / s, and the error with W3=4.6m / s was no more than 0.5m / s, so the F3 test was directly performed. The first flight number was set to increase the power consumption of the drone, so as to perform a more accurate analysis. The first flight number was set to 8 times. There was no fixed value for the first flight number, and usually the power consumption of the drone was made to reach more than 10%. For F3, 8 flights were performed with the relative angle as the first angle. After 8 flights, the test power consumption was recorded as T(3,0°). By analogy, 8 flights were performed for each flight angle, and T(3,30°), T(3,60°), T(3,90°), T(3,120°), T(3,150°) and T(3,180°) were obtained. Similarly, the test power consumption of other wind force test experimental groups was analyzed. Since N1=2km and N2=8, the flight distance was calculated to be 16km.

[0089] The relationship diagram construction unit is used to calculate and construct a wind power consumption relationship diagram and an angle power consumption ratio relationship diagram based on the test data;

[0090] The relationship graph construction unit is configured with a relationship graph construction strategy, which includes:

[0091] Mark the flight distance as L, calculate T(n,180°) / L, and mark the result as unit power consumption, represented by the symbol E;

[0092] See also Figure 3 As shown, Wn As the X-axis, the unit power consumption as the Y-axis to establish a plane rectangular coordinate system, named wind power consumption relationship diagram, F n The corresponding W n And the unit power consumption is entered into the wind power consumption relationship diagram;

[0093] In practical applications, unit power consumption means the UAV is in W n The power consumed per kilometer when flying against the wind at a wind speed of n Each of them corresponds to a unit power consumption E. E is calculated and displayed in the order of n from small to large, and the results are 1.7500% / km, 1.5625% / km, 1.3750% / km, 1.1875% / km, 1.0625% / km, 0.9375% / km, 0.8125% / km, 0.7500% / km, 0.6875% / km and 0.6250% / km. The calculation results are retained to four decimal places, and the wind power consumption relationship diagram is constructed as shown below Figure 3 As shown, since the wind environment of F3 is 4.9m / s, the coordinates corresponding to F3 are (4.9,1.375);

[0094] Calculate T(n,θ) / L, mark the result as power consumption per unit angle, represented by symbol EO, where θ does not include the seventh angle; calculate EO / E, mark the result as power consumption ratio, represented by symbol H(n,θ), where θ does not include the seventh angle;

[0095] In practical applications, the unit power consumption only considers the power consumption of the drone when it is completely against the wind. In this embodiment, the relative angle between the flight direction of the drone and the wind direction also needs to be considered. Taking T(3,0°) as an example, in this embodiment, the EO corresponding to T(3,0°) is calculated to be 0.7144% / km, and then the ratio of the EO of T(3,0°) to the E of T(3,180°) is calculated to obtain H(3,0°) as 0.9525. The calculation result retains four decimal places, and the calculation of the remaining H(n,θ) is the same as H(3,0°);

[0096] See also Figure 4 As shown, a plane rectangular coordinate system is established with θ as the horizontal axis and H(n,θ) as the vertical axis, named as the angle power consumption ratio relationship diagram, and H(n,θ) is entered into the angle power consumption ratio relationship diagram according to the corresponding θ;

[0097] In practical applications, under normal circumstances, the greater the wind force, the smaller the ratio of the power consumption of the drone when flying with the wind and against the wind, and the smaller the relative angle, the smaller the ratio of the power consumption of the drone relative to the power consumption of the drone when flying with the wind and against the wind. That is, the greater the wind force, the smaller the angle power consumption ratio of the drone, and the smaller the relative angle, the smaller the angle power consumption ratio of the drone. Different legends are used to represent H(n,θ) of different wind force test experimental groups, that is, each n corresponds to a legend, and the angle power consumption ratio relationship diagram is constructed as follows Figure 4 As shown;

[0098] The impact analysis unit is used to analyze the impact function of the power consumption of the UAV with wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram;

[0099] The impact analysis unit is configured with an impact analysis strategy, which includes:

[0100] Regression analysis is performed on the wind power consumption relationship diagram. The wind power consumption relationship diagram is regressed by exponential regression to obtain the wind power consumption equation. The format of the wind power consumption equation is WPC = a × e -b×WP , where WPC is wind power consumption efficiency, WP is wind power, a and b are constants inherent in the regression equation, and e is a natural constant;

[0101] In actual application, it is observed that Figure 3 The coordinate points in the graph conform to the exponential distribution, so the regression analysis is performed using the exponential regression method, and the wind power consumption equation is WPC = 0.4973 × e 0.0906×WP , where a = 0.4973, b = -0.0906;

[0102] See also Figure 5 As shown, based on the difference of n in H(n,θ) in the angle power consumption ratio relationship diagram, the coordinate point is named the nth coordinate point, and the angle power consumption ratio relationship diagram is subjected to regression analysis. The nth coordinate point in the angle power consumption ratio relationship diagram is regressed by linear regression to obtain the angle power consumption ratio equation. The angle power consumption ratio equation format is PCV n =c×θ+d, where PCV n is the angular power consumption ratio of the nth coordinate point, θ is the flight angle, and c and d are constants inherent in the regression equation;

[0103] In practical applications, the greater the wind force, the greater the difference in power consumption when the drone is flying with the wind and against the wind. Therefore, the test results of different wind force test groups cannot be directly combined for comprehensive analysis. They are analyzed separately. Figure 4It is found that the nth coordinate points in the same wind test experimental group present a linear distribution, so they are linearly regressed to obtain 10 angle power consumption proportional equations, corresponding to PCV1 to PCV 10 ,like Figure 5 As shown, Figure 5 The straight lines in the figure represent PCV1 to PCV from top to bottom. 10 The angle power consumption proportional equation is found at the same time PCV1 to PCV 10 The corresponding line segments all pass through or are close to the coordinate point (180°, 1). This is because the denominator in the calculation process of H(n, θ) is the unit power consumption at 180°. Therefore, no matter how the wind speed changes, when the relative angle is 180°, the angle power consumption ratio is 1, and the angle power consumption ratio equation presents a linear distribution. If one point (180°, 1) is known, we only need to determine another point to get the accurate angle power consumption ratio equation.

[0104] See also Figure 6 As shown, all PCVs when θ = 0° are obtained. n And marked as PCO n , get PCO n The corresponding W n , with W n For the X-axis, PCO n Establish a plane rectangular coordinate system for the Y axis, named the lowest scale distribution map, and set W n And the corresponding PCO n Enter the minimum proportion distribution map;

[0105] Perform linear regression on the minimum proportion distribution graph to obtain the minimum proportion distribution equation. The minimum proportion distribution equation format is PCO = f × WP + g, where PCO is the minimum proportion, and f and g are inherent constants of the regression equation;

[0106] In practical applications, in this embodiment, PCV in different wind forces when θ = 0° is selected. n As a reference object for analysis, this is because θ = 0° is the other end point of the angle power consumption ratio equation, which is easier to analyze and construct the lowest ratio distribution diagram as shown in Figure 6 As shown, through Figure 6 It is found that the coordinate points also present a linear distribution, so a linear regression analysis is performed on them, and the lowest proportional distribution equation is obtained as PCO = -0.0257 × WP + 1.0446, where f = -0.0257, g = 1.0446;

[0107] Substitute the wind power WP into the minimum proportional distribution equation, solve for PCO, and then substitute the coordinate points (0°, PCO) and (180°, 1) into the angle power consumption proportional equation PCV n=c×θ+d, after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angle power consumption ratio;

[0108] In practical applications, by substituting the wind force WP into PCO = -0.0257 × WP + 1.0446, the angle power consumption ratio of the drone can be solved when the wind force is WP and the relative angle between the drone and the wind direction is 0°, and the coordinate point (0°, PCO), PCV n =c×θ+d has many different situations, and in practical application, it is necessary to determine the appropriate one according to the wind force, that is, substitute the coordinate points (0°, PCO) and (180°, 1) into it and solve c and d. After solving c and d, the correct angle power consumption ratio equation when the wind force is WP can be obtained; assuming that the wind force WP is 5.2m / s, substitute PCO=-0.0257×WP+1.0446 to calculate PCO as 0.9110, keep four decimal places in the calculation result, substitute (0°, 0.9110) and (180°, 1) into PCV n =c×θ+d, and the solution is c=0.0005, d=0.911. The calculation results are all retained to four decimal places to obtain the final angle power consumption ratio equation PCR=0.0005×θ+0.911;

[0109] WPC is the wind power consumption efficiency in the positive and negative wind directions. Multiplying it with PCR can estimate the wind power consumption efficiency of the drone during flight based on the angle between the flight direction of the drone and the wind direction, which is marked as the estimated power consumption efficiency. The estimated power consumption efficiency is calculated by the power consumption influence function. The power consumption influence function is EPC = WPC × PCR = (a × e -b×WP )×(c×θ+d);

[0110] In practical applications, WPC = 0.4973 × e 0.0906×WP , PCR = 0.0005 × θ + 0.911, and the power consumption influence function is EPC = (0.4973 × e 0.0906×WP )×(0.0005×θ+0.911).

[0111] The layout acquisition module is used to obtain the layout diagram of the hangar and the offshore wind turbine, and construct a location distribution map based on the location information in the layout diagram;

[0112] The layout acquisition module is configured with a layout acquisition strategy, which includes:

[0113] Obtain the layout diagram of the hangar and offshore wind turbines, which includes the longitude and latitude of the hangar and the longitude and latitude of the wind turbines;

[0114] See also Figure 7As shown, a plane rectangular coordinate system is established with the longitude and latitude of the hangar as the origin, due east as the X-axis, and due north as the Y-axis, and is named the location distribution map;

[0115] Based on the latitude and longitude distance calculation method, the angle and distance between the longitude and latitude of the wind turbine and the longitude and latitude of the hangar are calculated to obtain the relative angle and relative distance, and the offshore wind turbine is marked on the location distribution map according to the relative angle and relative distance;

[0116] In practical applications, the latitude and longitude distance calculation method is completed using the existing latitude and longitude distance calculation formula. This embodiment will not be specifically demonstrated in detail, and only the final position distribution map will be shown. The relative angle and relative distance are only used to determine the specific position of the offshore wind turbine relative to the hangar in the position distribution map. Therefore, this embodiment will not be specifically demonstrated in detail. The position distribution map is constructed as shown in FIG. Figure 7 shown.

[0117] The estimated power consumption calculation module is used to obtain the wind direction and wind force on the sea surface, control the drone to inspect according to the predetermined inspection route, and estimate the estimated total power consumption of the drone flying on the inspection route based on the location distribution map, wind direction and wind force and combined with the power consumption influence function;

[0118] The estimated power consumption calculation module is configured with an estimated power consumption calculation strategy, which includes:

[0119] Get the wind direction and wind force on the sea surface, marked as real-time wind direction and real-time wind force respectively;

[0120] See also Figure 8 As shown, the drone is controlled to perform inspections along a predetermined inspection route, and the inspection route is marked in a position distribution map. The inspection route is composed of a first number of straight lines, and a single straight line is named an inspection sub-route;

[0121] In practical applications, Figure 8 In the figure, the gray square represents the area where the drone needs to inspect the offshore wind turbines within the range after arriving at this area, that is, the inspection area. The straight lines in the first quadrant together constitute the inspection route, and the straight line between two inspection areas or between the inspection area and the hangar is an inspection sub-route. Figure 8 There are 9 inspection sub-routes and 8 inspection areas. The arrows on the inspection sub-routes represent the flight direction of the drone;

[0122] The inspection sub-routes are numbered and marked with R i Indicates that, where i∈Z+ and i is the serial number of R, get R i The angle relative to the real-time wind direction is marked as the course angle and is indicated by the symbol A. i Indicates that R is obtained i The length of the route is indicated by the symbol Di Indicates that the route angle is determined to be the same as the flight angle;

[0123] In practical applications, the R1 value R9 is obtained by numbering, 1≤i≤9. The route angle of each inspection sub-route can be calculated based on the flight direction and wind direction of the drone. The real-time wind speed is 6.8m / s, and the real-time wind direction is due west, that is, the wind blows due west. The route angles A1 to A9 are 166°, 157°, 52°, 52°, 30°, 25°, 128°, 128° and 29° respectively, and D1 to D9 are 15km, 8.57km, 5.4km, 4.1km, 4.89km, 6.3km, 4.7km, 4.54km and 14.1km respectively;

[0124] For R i , WP is equal to the real-time wind force and θ = A i Substitute into EPC = (a × e -b×WP )×(c×θ+d), and EPC is calculated;

[0125] Calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i Perform analysis, then calculate the sum of the estimated sub-power consumption to obtain the estimated total power consumption;

[0126] In practical applications, EPC = (0.4973 × e 0.0906×WP)×(0.0005×θ+0.911). As offshore wind turbines exist on the sea surface, and the wind force at sea is usually the same over a large area, if there is a difference, the corresponding calculation can be performed according to the real-time wind force in the area where the inspection sub-route is located. For example, the real-time wind force at R5 is 7.1m / s, while the real-time wind force at the remaining inspection sub-routes is 6.8m / s. When calculating R5, WP can be set to 7.1m / s. Taking R1 as an example, WP=6.8m / s, θ=A1=166°, substitute it into the calculation to get EPC=0.9153, keep four decimal places in the calculation result, and then calculate EPC×D1=0.9153×15=13.7295. The result is retained to four decimal places, indicating that the UAV will consume 13.7295% of the power after passing through the inspection sub-route R1. Similarly, the EPCs of R2 to R9 are calculated to be 0.9112, 0.8628, 0.8628, 0.8527, 0.8504, 0.8978, 0.8978 and 0.8522, respectively. Further calculations show that the estimated sub-power consumptions of R2 to R9 are 7.8090%, 4.6591%, 3.5375%, 4.1697%, 5.3575%, 4.2197%, 4.0760% and 3.4940%, respectively. The total estimated power consumption is 37%. The calculation results are retained to two decimal places and displayed as a percentage.

[0127] The inspection time calculation module is used to evaluate the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption;

[0128] The inspection duration calculation module is configured with inspection duration calculation strategies, which include:

[0129] Get the power of the drone when it takes off from the hangar, marked as takeoff power, represented by the symbol PU, and get the landing power threshold of the drone. The landing power threshold is a preset value, represented by the symbol PD, which is used to ensure that the drone still has the landing power threshold after returning to the hangar. Even if there is a deviation during the flight, resulting in excessive power consumption, it can ensure that the drone can return to the hangar safely;

[0130] Calculate PU-PD, mark the result as PH, and then calculate PH-EPU to get the total power consumption of shooting, represented by the symbol PK, where EPU is the estimated total power consumption;

[0131] In actual application, the take-off power PU is obtained to be 85%, the landing power threshold PD is 20%, and the calculated PH is 65%. The total shooting power PK is further calculated to be 28%, that is, the UAV has a total of 28% of its power used to shoot offshore wind turbines;

[0132] Substitute WP equal to the real-time wind force and θ = 90° into EPC = (a × e -b×WP )×(c×θ+d), and the calculated result is marked as the cruise power consumption efficiency, which is represented by the symbol EPD;

[0133] Get the comprehensive moving speed of the drone, marked as Q, calculate (PK / EPD) / Q, get the total time the drone takes to surround the offshore wind turbines, marked as TAL, then get the number of offshore wind turbines, marked as V, calculate TAL / V, and get the inspection time that can be allocated to each offshore wind turbine;

[0134] In practical applications, the calculation result of θ = 90° is used as the cruising power consumption efficiency because when the UAV takes pictures of the offshore wind turbine, it often needs to take 360° all-round pictures around the offshore wind turbine. At this time, no matter how the wind direction changes, the UAV can approximately make a circular motion around the offshore wind turbine. The angle between the motion trajectory and the wind direction at this time is between 0° and 180°, and the time is relatively close. Therefore, it can be approximately considered that the UAV is flying in a direction perpendicular to the wind direction, and it does not consume more power due to headwind, nor does it consume less power due to tailwind. Substitute WP = 6.8 m / s and θ = 90° into EPC = (0.4973×e 0.0906×WP )×(0.0005×θ+0.911), the cruise power consumption efficiency EPD=0.8803 is calculated, and the comprehensive moving speed of the UAV is 42km / h. The comprehensive moving speed represents the average moving speed of the UAV when it performs a surround shooting inspection task on the offshore wind turbine, which takes into account the time consumed in hovering. The total shooting time TAL=(PK / EPD) / Q=(28% / 0.8803% / km) / 18km / h=1.77h. The calculation result retains two decimal places, and the number of offshore wind turbines V is 8, that is, the number of inspection areas. Further calculation shows that the inspection time that can be allocated to each offshore wind turbine is 1.77h / 8=0.22125h≈13min.

[0135] Example 2, please refer to Fig. 9 As shown, the present application provides an offshore wind turbine inspection method based on a drone hangar, comprising the following steps:

[0136] Step S1, testing the relationship function between the power consumption of the UAV during flight and the wind direction and wind force, named as the power consumption influence function; Step S1 includes the following sub-steps:

[0137] Step S101, selecting an open area and performing a flight test on the UAV in different wind environments, and recording the test data;

[0138] Step S101 includes the following sub-steps:

[0139] Step S1011, selecting an open area, where the open area is a plain terrain and there is an open area with a diameter of a first test distance;

[0140] Step S1012, obtaining the maximum wind force that the drone can withstand, and setting the starting wind force, and taking the starting wind force to the maximum wind force as a range interval, named as the wind force interval;

[0141] Step S1013, evenly divide the wind force interval into a first test number of sub-intervals, named wind force sub-intervals, mark the interval between two adjacent wind force sub-intervals as test wind force, and also mark the starting wind force as test wind force;

[0142] Step S1014: number the test wind forces in the order of small to large in the wind force interval, and use the symbol W n It represents, where n∈Z+ and n is the serial number of W, Z+ represents a positive integer, and the maximum value of n is the first test quantity;

[0143] Step S1015, setting a first number of wind force test experiment groups, represented by symbol F n Indicates that, and F n The wind force level in the experiment is W n ;

[0144] Step S1016, setting the flight angle, which includes a first angle, a second angle, a third angle, a fourth angle, a fifth angle, a sixth angle and a seventh angle. The flight angle is the angle between the flight direction of the drone and the wind direction, and the flight angle increases in sequence. The first angle is 0°, and the seventh angle is 180°. 0° means that the flight direction of the drone and the wind direction are opposite directions, which is the headwind direction, and 180° means that the flight direction of the drone is the same as the wind direction, which is the downwind direction.

[0145] Step S1017, testing different wind force test experimental groups based on the flight angle, and recording the test data;

[0146] Step S1017 includes the following sub-steps:

[0147] Step S1017.1, for F n , monitor the wind direction and wind force in the open area. When the wind force is W n When the test is completed, the UAV is controlled to fly at the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle respectively, and the flight distance is the first test distance. After the flight, the tester brings the UAV back to the starting position and performs the flight again, and each flight angle performs the first number of flights;

[0148] Step S1017.2, for each flight angle, record the power consumed by the drone from the beginning of the test to the end of the test, marked as test power consumption, by the symbol T(n,θ), where θ is the flight angle and (n,θ) is the serial number of T, T(n,θ) represents F n The power consumption of the test when the flight angle is θ;

[0149] Step S1017.3, calculate N1×N2, and mark the calculation result as the flight distance, where N1 is the first test distance and N2 is the first flight number;

[0150] Step S102, calculating and constructing a wind power consumption relationship diagram and an angle power consumption ratio relationship diagram based on the test data;

[0151] Step S102 includes the following sub-steps:

[0152] Step S1021, mark the flight distance as L, calculate T(n,180°) / L, and mark the calculation result as unit power consumption, represented by symbol E;

[0153] Step S1022, with W n As the X-axis, the unit power consumption as the Y-axis to establish a plane rectangular coordinate system, named wind power consumption relationship diagram, F n The corresponding W n And the unit power consumption is entered into the wind power consumption relationship diagram;

[0154] Step S1023, calculate T(n,θ) / L, mark the calculation result as power consumption per unit angle, represented by symbol EO, where θ does not include the seventh angle, calculate EO / E, mark the calculation result as power consumption ratio, represented by symbol H(n,θ), where θ does not include the seventh angle;

[0155] Step S1024, establish a plane rectangular coordinate system with θ as the horizontal axis and H(n,θ) as the vertical axis, name it as the angle power consumption ratio relationship diagram, and enter H(n,θ) into the angle power consumption ratio relationship diagram according to the corresponding θ;

[0156] Step S103, analyzing the influence function of the power consumption of the drone and the wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram;

[0157] Step S103 includes the following sub-steps:

[0158] Step S1031, performing regression analysis on the wind power consumption relationship diagram, regressing the wind power consumption relationship diagram by exponential regression to obtain a wind power consumption equation, the format of which is WPC = a × e -b×WP, where WPC is wind power consumption efficiency, WP is wind power, a and b are constants inherent in the regression equation, and e is a natural constant;

[0159] Step S1032, based on the difference of n in H(n,θ) in the angle power consumption ratio relationship diagram, the coordinate point is named as the nth coordinate point, and the angle power consumption ratio relationship diagram is subjected to regression analysis. The nth coordinate point in the angle power consumption ratio relationship diagram is regressed by linear regression to obtain the angle power consumption ratio equation. The angle power consumption ratio equation format is PCV n =c×θ+d, where PCV n is the angular power consumption ratio of the nth coordinate point, θ is the flight angle, and c and d are constants inherent in the regression equation;

[0160] Step S1033, obtaining all PCVs when θ=0° n And marked as PCO n , get PCO n The corresponding W n , with W n For the X-axis, PCO n Establish a plane rectangular coordinate system for the Y axis, named the lowest scale distribution map, and set W n And the corresponding PCO n Enter the minimum proportion distribution map;

[0161] Step S1034, performing linear regression on the minimum proportion distribution graph to obtain a minimum proportion distribution equation, the format of which is PCO=f×WP+g, where PCO is the minimum proportion, and f and g are inherent constants of the regression equation;

[0162] Step S1035, substitute the wind power WP into the minimum distribution equation, solve to obtain PCO, and then substitute the coordinate points (0°, PCO) and (180°, 1) into the angle power consumption proportional equation PCV n =c×θ+d, after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angle power consumption ratio;

[0163] Step S1036, WPC is the wind power consumption efficiency in the positive and negative wind directions. Multiplying it with PCR can estimate the wind power consumption efficiency of the UAV during flight based on the angle between the flight direction of the UAV and the wind direction, which is marked as the estimated power consumption efficiency. The estimated power consumption efficiency is calculated by the power consumption influence function, which is EPC = WPC × PCR = (a × e -b×WP )×(c×θ+d);

[0164] Step S2, obtaining a layout diagram of the hangar and the offshore wind turbines, and constructing a location distribution map based on the location information in the layout diagram; Step S2 includes the following sub-steps:

[0165] Step S201, obtaining a layout diagram of the hangar and the offshore wind turbine, wherein the layout diagram includes the longitude and latitude of the hangar and the longitude and latitude of the wind turbine;

[0166] Step S202, establishing a plane rectangular coordinate system with the longitude and latitude of the hangar as the origin, due east as the X-axis, and due north as the Y-axis, and naming it a location distribution map;

[0167] Step S203, calculating the angle and distance between the longitude and latitude of the wind turbine and the longitude and latitude of the hangar based on the longitude and latitude distance calculation method to obtain a relative angle and a relative distance, and marking the offshore wind turbine in the location distribution map according to the relative angle and relative distance;

[0168] Step S3, obtaining the wind direction and wind force on the sea surface, controlling the drone to perform inspections along the predetermined inspection route, and estimating the total power consumption of the drone flying along the inspection route based on the location distribution map, wind direction and wind force and in combination with the power consumption influence function; Step S3 includes the following sub-steps:

[0169] Step S301, obtaining the wind direction and wind force on the sea surface, and marking them as real-time wind direction and real-time wind force respectively;

[0170] Step S302, controlling the drone to perform inspection along a predetermined inspection route, marking the inspection route in the location distribution map, the inspection route being composed of a first number of straight lines, and naming a single straight line as an inspection sub-route;

[0171] Step S303: number the inspection sub-routes, using the symbol R i Indicates that, where i∈Z+ and i is the serial number of R, get R i The angle relative to the real-time wind direction is marked as the course angle and is indicated by the symbol A. i Indicates that R is obtained i The length of the route is indicated by the symbol D i Indicates that the route angle is determined to be the same as the flight angle;

[0172] Step S304, for R i , WP is equal to the real-time wind force and θ = A i Substitute into EPC = (a × e -b×WP )×(c×θ+d), and EPC is calculated;

[0173] Step S305, calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i Perform analysis, then calculate the sum of the estimated sub-power consumption to obtain the estimated total power consumption;

[0174] Step S4, evaluating the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption; Step S4 includes the following sub-steps:

[0175] Step S401, obtaining the power of the drone when it takes off from the hangar, marked as the take-off power, represented by the symbol PU, and obtaining the landing power threshold of the drone, which is a preset value, represented by the symbol PD, to ensure that the drone still has the power of the landing power threshold after returning to the hangar, even if there is a deviation during the flight, resulting in excessive power consumption, it can ensure that the drone can return to the hangar safely;

[0176] Step S402, calculate PU-PD, mark the calculation result as PH, and then calculate PH-EPU to obtain the total power consumption of shooting, which is represented by the symbol PK, where EPU is the estimated total power consumption;

[0177] Step S403: Substitute WP equal to the real-time wind force and θ = 90° into EPC = (a × e -b×WP )×(c×θ+d), and the calculated result is marked as the cruise power consumption efficiency, which is represented by the symbol EPD;

[0178] Step S404, obtain the comprehensive moving speed of the drone, marked as Q, calculate (PK / EPD) / Q, obtain the total time the drone takes to surround the offshore wind turbines, marked as TAL, then obtain the number of offshore wind turbines, marked as V, calculate TAL / V, and obtain the inspection time that can be allocated to each offshore wind turbine.

[0179] Embodiment 3, the present application provides an electronic device, which may include: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in an offshore wind turbine inspection method based on a drone hangar are executed to achieve the following functions: test the relationship function between the power consumed by the drone during flight and the wind direction and wind force, named as the power consumption influence function; obtain the layout diagram of the hangar and the offshore wind turbine, and construct a location distribution diagram through the location information in the layout diagram; estimate the estimated total power consumption of the drone flying on the inspection route based on the location distribution diagram, wind direction and wind force and combined with the power consumption influence function; evaluate the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption.

[0180] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

[0181] Embodiment 4, the present application also provides a computer-readable storage medium, the present application provides a storage medium, on which a computer program is stored. When the computer program is executed by the processor, the steps in the above offshore wind turbine inspection method based on a drone hangar are executed to achieve the following functions: test the relationship function between the power consumed by the drone during flight and the wind direction and wind force, named as the power consumption influence function; obtain the layout diagram of the hangar and the offshore wind turbine, and construct a location distribution map through the location information in the layout diagram; estimate the estimated total power consumption of the drone flying on the inspection route based on the location distribution map, wind direction and wind force and combined with the power consumption influence function; evaluate the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption.

[0182] Through the description of the above implementation methods, the embodiments of the present invention can be provided as methods, systems or computer program products. Based on such an understanding, the above technical solutions can be essentially or partly contributed to the prior art in the form of software products, which can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and include several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0183] In the embodiments provided in the present application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of systems, modules and units can be electrical, mechanical or other forms.

[0184] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application 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 make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for inspecting offshore wind turbines based on a drone hangar, characterized in that: The steps include: The relationship function between the power consumption of the UAV during flight and the wind direction and wind force is named as the power consumption influence function; Obtain the layout diagram of the hangar and offshore wind turbines, and construct a location distribution map based on the location information in the layout diagram; Obtain the wind direction and wind force on the sea surface, control the drone to conduct inspections along the predetermined inspection route, and estimate the total power consumption of the drone flying along the inspection route based on the location distribution map, wind direction and wind force combined with the power consumption influence function; Evaluate the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption.

2. The offshore wind turbine inspection method based on a drone hangar according to claim 1 is characterized in that: The relationship function between the power consumption of the UAV during flight and the wind direction and wind force is named as the power consumption influence function, which includes the following sub-steps: Select an open area and perform flight tests on the drone in different wind conditions, and record the test data; Calculate and construct wind power consumption relationship diagram and angle power consumption ratio relationship diagram based on test data; Based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram, the influence function of the drone's power consumption and wind force and wind direction is analyzed.

3. The offshore wind turbine inspection method based on a drone hangar according to claim 2 is characterized in that: Select an open area and perform flight tests on the drone in different wind conditions. Recording test data includes the following sub-steps: An open area is selected, where the open area is a plain terrain and there is an open area with a diameter of the first test distance; Get the maximum wind speed that the drone can withstand, set the starting wind speed, and take the starting wind speed to the maximum wind speed as a range, named wind speed range; The wind force interval is evenly divided into a first test number of subintervals, which are named wind force subintervals, and the interval between two adjacent wind force subintervals is marked as a test wind force, and the starting wind force is also marked as a test wind force; The test wind forces are numbered in the order from small to large in the wind force range, and the symbol W is used to represent the wind force. n It represents, where n∈Z+ and n is the serial number of W, Z+ represents a positive integer, and the maximum value of n is the first test quantity; Set the wind test experiment group of the first test number, through the symbol F n Indicates that, and F n The wind force level in the experiment is W n ; Set the flight angle, which includes the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle. The flight angle is the angle between the flight direction of the drone and the wind direction, and the flight angle increases in sequence. The first angle is 0°, the seventh angle is 180°, 0° means that the flight direction of the drone is opposite to the wind direction, which is the headwind direction, and 180° means that the flight direction of the drone is the same as the wind direction, which is the downwind direction; Different wind force test experimental groups are tested based on the flight angle and the test data are recorded.

4. The offshore wind turbine inspection method based on a drone hangar according to claim 3 is characterized in that: Testing different wind force test groups based on flight angles and recording test data includes the following sub-steps: For F n , monitor the wind direction and wind force in the open area. When the wind force is W n When the test is completed, the UAV is controlled to fly at the first angle, the second angle, the third angle, the fourth angle, the fifth angle, the sixth angle and the seventh angle respectively, and the flight distance is the first test distance. After the flight, the tester brings the UAV back to the starting position and performs the flight again, and each flight angle performs the first number of flights; For each flight angle, record the power consumed by the drone from the beginning to the end of the test, marked as the test power consumption, and represented by the symbol T(n,θ), where θ is the flight angle and (n,θ) is the serial number of T, T(n,θ) represents F n The power consumption of the test when the flight angle is θ; Calculate N1×N2, and mark the calculation result as the flight distance, where N1 is the first test distance and N2 is the first flight number.

5. The offshore wind turbine inspection method based on a drone hangar according to claim 4 is characterized in that: Calculating and constructing the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram based on the test data includes the following sub-steps: Mark the flight distance as L, calculate T(n,180°) / L, and mark the result as unit power consumption, represented by the symbol E; W n As the X-axis, the unit power consumption as the Y-axis to establish a plane rectangular coordinate system, named wind power consumption relationship diagram, F n The corresponding W n And the unit power consumption is entered into the wind power consumption relationship diagram; Calculate T(n,θ) / L, mark the result as power consumption per unit angle, represented by symbol EO, where θ does not include the seventh angle; calculate EO / E, mark the result as power consumption ratio, represented by symbol H(n,θ), where θ does not include the seventh angle; A plane rectangular coordinate system is established with θ as the horizontal axis and H(n,θ) as the vertical axis, and is named as the angle power consumption proportional relationship diagram. H(n,θ) is entered into the angle power consumption proportional relationship diagram according to the corresponding θ.

6. The offshore wind turbine inspection method based on a drone hangar according to claim 5 is characterized in that: Analyzing the influence function of the power consumption of the drone on wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio relationship diagram includes the following sub-steps: Regression analysis is performed on the wind power consumption relationship diagram. The wind power consumption relationship diagram is regressed by exponential regression to obtain a wind power consumption equation. The wind power consumption equation format is WPC = a × e -b×WP , where WPC is wind power consumption efficiency, WP is wind power, a and b are constants inherent in the regression equation, and e is a natural constant; Based on the difference of n in H(n,θ) in the angle power consumption ratio relationship diagram, the coordinate point is named as the nth coordinate point, and the angle power consumption ratio relationship diagram is subjected to regression analysis. The nth coordinate point in the angle power consumption ratio relationship diagram is regressed by linear regression to obtain the angle power consumption ratio equation. The angle power consumption ratio equation format is PCV n =c×θ+d, where PCV n is the angular power consumption ratio of the nth coordinate point, θ is the flight angle, and c and d are constants inherent in the regression equation; Get all PCVs when θ=0° n And marked as PCO n , get PCO n The corresponding W n , with W n For the X-axis, PCO n Establish a plane rectangular coordinate system for the Y axis, named the lowest scale distribution map, and set W n And the corresponding PCO n Enter the minimum proportion distribution map; Performing linear regression on the minimum proportion distribution graph to obtain a minimum proportion distribution equation, wherein the minimum proportion distribution equation has a format of PCO=f×WP+g, wherein PCO is the minimum proportion, and f and g are inherent constants of the regression equation; Substitute the wind power WP into the minimum proportional distribution equation, solve for PCO, and then substitute the coordinate points (0°, PCO) and (180°, 1) into the angle power consumption proportional equation PCV n =c×θ+d, after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angle power consumption ratio; WPC is the wind power consumption efficiency in the positive and negative wind directions. Multiplying it with PCR can estimate the wind power consumption efficiency of the drone during flight based on the angle between the flight direction of the drone and the wind direction, which is marked as the estimated power consumption efficiency. The estimated power consumption efficiency is calculated by the power consumption influence function, which is EPC=WPC×PCR=(a×e -b×WP )×(c×θ+d).

7. The offshore wind turbine inspection method based on a drone hangar according to claim 6 is characterized in that: Obtaining the layout diagram of the hangar and the offshore wind turbines and constructing a location distribution map using the location information in the layout diagram includes the following sub-steps: Obtaining a layout diagram of the hangar and the offshore wind turbine, wherein the layout diagram includes the longitude and latitude of the hangar and the longitude and latitude of the wind turbine; A plane rectangular coordinate system is established with the longitude and latitude of the hangar as the origin, due east as the X-axis, and due north as the Y-axis, and is named the location distribution map; Based on the longitude and latitude distance calculation method, the angle and distance between the longitude and latitude of the wind turbine and the longitude and latitude of the hangar are calculated to obtain the relative angle and relative distance. The offshore wind turbine is marked on the location distribution map according to the relative angle and relative distance.

8. The offshore wind turbine inspection method based on a drone hangar according to claim 7 is characterized in that: Obtaining the wind direction and wind force on the sea surface, controlling the drone to perform inspections along the predetermined inspection route, and estimating the total power consumption of the drone flying along the inspection route based on the location distribution map, wind direction and wind force and combined with the power consumption influence function includes the following sub-steps: Get the wind direction and wind force on the sea surface, marked as real-time wind direction and real-time wind force respectively; Controlling the drone to perform inspection along a predetermined inspection route, marking the inspection route in the location distribution map, wherein the inspection route is composed of a first number of straight lines, and naming a single straight line as an inspection sub-route; The inspection sub-routes are numbered and marked with R i Indicates that, where i∈Z+ and i is the serial number of R, get R i The angle relative to the real-time wind direction is marked as the course angle and is indicated by the symbol A. i Indicates that R is obtained i The length of the route is indicated by the symbol D i Indicates that the angle of the route is determined to be the same as the flight angle; For R i , WP is equal to the real-time wind force and θ = A i Substitute into EPC = (a × e -b×WP )×(c×θ+d), and EPC is calculated; Calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i After analysis, the sum of the estimated sub-power consumption is calculated to obtain the estimated total power consumption.

9. The offshore wind turbine inspection method based on a drone hangar according to claim 8 is characterized in that: The evaluation of the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption includes the following sub-steps: Get the power of the drone when it takes off from the hangar, marked as take-off power, represented by the symbol PU, and get the landing power threshold of the drone. The landing power threshold is a preset value, represented by the symbol PD, which is used to ensure that the drone still has the landing power threshold after returning to the hangar. Even if there is a deviation during the flight, resulting in excessive power consumption, it can ensure that the drone can return to the hangar safely; Calculate PU-PD, mark the result as PH, and then calculate PH-EPU to get the total power consumption of shooting, represented by the symbol PK, where EPU is the estimated total power consumption; Substitute WP equal to the real-time wind force and θ = 90° into EPC = (a × e -b×WP )×(c×θ+d), and the calculated result is marked as the cruise power consumption efficiency, which is represented by the symbol EPD; Get the comprehensive moving speed of the UAV, marked as Q, calculate (PK / EPD) / Q, get the total time the UAV takes to surround the offshore wind turbines, marked as TAL, then get the number of offshore wind turbines, marked as V, calculate TAL / V, and get the inspection time that can be allocated to each offshore wind turbine.

10. An offshore wind turbine inspection system based on a drone hangar, used to implement an offshore wind turbine inspection method based on a drone hangar as described in any one of claims 1 to 9, characterized in that: It includes an impact analysis module, a layout acquisition module, an estimated power consumption calculation module and an inspection time calculation module; the layout acquisition module, the estimated power consumption calculation module and the inspection time calculation module are respectively connected to the impact analysis module data; The impact analysis module is used to test the relationship function between the power consumption of the drone during flight and the wind direction and wind force, which is named as the power consumption impact function; The layout acquisition module is used to acquire the layout diagram of the hangar and the offshore wind turbines, and construct a location distribution map through the location information in the layout diagram; The estimated power consumption calculation module is used to obtain the wind direction and wind force on the sea surface, control the drone to inspect according to the predetermined inspection route, and estimate the estimated total power consumption of the drone flying on the inspection route based on the location distribution map, wind direction and wind force and combined with the power consumption influence function; The inspection duration calculation module is used to evaluate the inspection duration that can be allocated to each offshore wind turbine based on the estimated total power consumption.

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