An offshore wind turbine inspection system and method based on drone hangar

Abstract

The present invention discloses an offshore wind turbine inspection system and method based on a drone hangar, which relates to the technical field of drone offshore inspection, and comprises the following steps: testing a relationship function between the power consumption of a drone during flight and wind direction and wind force, which is named 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 the position information in the layout diagram; estimating the estimated total power consumption of the drone flying on the inspection route based on the position distribution diagram, wind direction and wind force and in combination with the power consumption influence function; and evaluating the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption. The present invention is used 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.

Description

Technical Field

[0001] The present invention relates to the technical field of drone offshore inspection, and in particular to an offshore wind turbine inspection system and method based on a drone 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 area. 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 inspections, 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 technology at sea usually completes inspections through manual remote control or automatic flight along a predetermined route. During the inspection process, since drones cannot generate energy on their own, they 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 technology at sea usually only links to flight mileage when evaluating power consumption. Drones are affected by wind when running. They can save power when the wind is blowing, but save power when the wind is blowing against them. More electricity is consumed when flying, and the wind on the sea is usually stronger, 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 drone power. As a result, the drone cannot adjust 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 insufficiently precise power planning, which leads to 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 drones under different wind environments, recording 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 at the same time obtaining the wind direction and wind force on the sea surface, controlling the drone to perform inspections 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 combined 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 drone during flight and the wind direction and wind force is named the power consumption impact 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 wind direction and 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 force, and the power consumption impact function;

[0009] Assess 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. This function is named the power consumption impact 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 flight tests are conducted on the drone in different wind environments. Recording the test data includes the following sub-steps:

[0015] An open area is selected, where the open area is a plain terrain and has 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 use the starting wind speed to the maximum wind speed as a range, named wind speed range;

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

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

[0019] Set the first test number of wind test experimental groups, 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, second angle, third angle, fourth angle, fifth angle, sixth angle and seventh angle. The flight angle is the angle between the flight direction of the drone and the wind direction. The flight angle increases in sequence, where the first angle is 0° and 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 groups are tested based on the flight angle and the test data are recorded.

[0022] Furthermore, testing different wind force test groups based on flight angles and recording 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 drone 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. The flight distance is the first test distance. After the flight is completed, the tester brings the drone back to the starting position and performs the flight again. Each flight angle performs the first number of flights.

[0024] For each flight angle, record the power consumed by the drone from the start to the end of the test, marked as the 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;

[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 Corresponding W n And the unit power consumption is entered into the wind power consumption relationship diagram;

[0029] Calculate T(n,θ) / L, and mark the result as power consumption per unit angle, represented by the symbol EO, where θ does not include the seventh angle. Calculate EO / E, and mark the result as power consumption ratio, represented by the 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 an 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 UAV'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 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 the 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 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 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 the format of PCO=f×WP+g, where 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 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, and after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angular 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 drone's flight direction 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] Furthermore, 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 hangar's longitude and latitude 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 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. The offshore wind turbines are marked on the location distribution map according to the relative angle and relative distance.

[0042] Furthermore, obtaining the wind direction and wind force on the sea surface, controlling the drone to perform inspections along a 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 include 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 inspections along a predetermined inspection route, marking the inspection route on the location distribution map, wherein the inspection route is composed of a first number of straight lines, and naming each straight line as an inspection sub-route;

[0045] Number the inspection sub-routes and use 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, which is indicated by the symbol A. i Indicates that R is obtained i The length of the route is marked by the symbol D i Indicates that the size of the route angle is determined to be the same as the flight angle;

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

[0047] Calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i Perform analysis and then calculate the sum of the estimated sub-power consumption 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] Obtain the drone's battery level when it takes off from the hangar, marked as takeoff power and represented by the symbol PU. Obtain the drone's landing power threshold. The landing power threshold is a preset value, represented by the symbol PD. This ensures that the drone still has enough power to return to the hangar after returning to the hangar. Even if there is a deviation during flight, resulting in excessive power consumption, the drone can still return to the hangar safely.

[0050] Calculate PU-PD and mark the result as PH. Then calculate PH-EPU to get the total power consumption of the 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), the calculated result is marked as the cruise power consumption efficiency, represented by the symbol EPD;

[0052] The comprehensive moving speed of the drone is obtained, marked as Q, and (PK / EPD) / Q is calculated to obtain the total time the drone spends circling the offshore wind turbines, marked as TAL. The number of offshore wind turbines is then obtained, marked as V, and TAL / V is calculated to obtain 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, comprising 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 the power consumption impact function;

[0055] The layout acquisition module is used to obtain a layout diagram of the hangar and the offshore wind turbines, and to construct a location distribution map based on 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 perform inspections along a predetermined inspection route, and estimate the estimated 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;

[0057] 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.

[0058] Beneficial effects of the present invention: The present invention selects an open area and conducts flight tests on a drone under different wind environments, records the 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. Then, 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. The advantage is that the influence of wind force and wind direction on the drone's power consumption can be obtained. 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 the hangar and offshore wind turbines, constructs a position distribution map based on the position information in the layout diagram, and simultaneously obtains the wind direction and wind force on the sea surface, controls the UAV to perform inspections along a predetermined inspection route, and estimates the estimated total power consumption of the UAV flying on the inspection route based on the position distribution diagram, wind direction and wind force and in combination with the 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 UAV 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 UAV offshore wind turbine inspection. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0061] Figure 2 Schematic diagram of the determination of the relative angle of the present invention;

[0062] Figure 3 This is a graph showing the relationship between wind power consumption and the power consumption of the present invention;

[0063] Figure 4 This is a diagram showing the relationship between the power consumption ratios according to the present invention;

[0064] Figure 5 PCV1 to PCV of the present invention 10 Schematic diagram of;

[0065] Figure 6 is the lowest proportion distribution diagram of the present invention;

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

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

[0068] Figure 9 Flow chart of the steps of the method of the present invention. DETAILED DESCRIPTION

[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts 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 drone during flight and the wind direction and wind force, which is named the power consumption impact function. The impact analysis module includes a flight test unit, a relationship graph 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 drone 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 use 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 areas far away from cities. 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 the 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 spaces, and calm and windless conditions are extremely rare. However, there must be wind on the sea, and the wind force on the sea is usually larger. Therefore, a starting wind force is set to reduce the analysis process of meaningless low wind forces and speed up the test efficiency. In this embodiment, the starting wind force is set to 2m / s, and the wind force range is [2m / s, 15m / s].

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

[0078] In practical applications, the first test quantity is set to refine the wind speed range 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-ranges, 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], [ 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 extreme wind force that the drone can withstand. It is usually not recommended to fly drones in extreme wind forces to avoid accidents. Therefore, the situation of 15m / s is not considered.

[0079] The test wind forces are numbered in the order of small to large in the wind force range, and the symbol W is used to identify the wind forces. nDenotes, where n∈Z+ and n is the sequence 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, through 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 speed test groups are set up to obtain the wind speeds from F1 to F2. 10 , the corresponding test wind forces are W1 to W 10 In actual testing, the wind speed at the test site does not need to be strictly in accordance with the test wind speed. It only needs to ensure that the deviation between the wind speed and the test wind speed corresponding to the wind test experimental group does not exceed 0.5m / s. The actual test wind speed can be uploaded during specific analysis. For example, for F1, the test wind speed is W1 = 2m / s. In actual testing, the wind speed at the test site can be between [1.5m / s, 2.5m / s]. Assuming that the wind speed 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, 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°, 180° represents that the flight direction of the drone and the wind direction are opposite, which is the headwind direction, and 0° represents that the flight direction of the drone is the same as the wind direction, which is the downwind direction;

[0083] In actual application, 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 the relative angle. The relative angle is determined 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 the 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 drone 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. The flight distance is the first test distance. After the flight is completed, the tester brings the drone back to the starting position and performs the flight again. Each flight angle performs the first number of flights.

[0086] For each flight angle, record the power consumed by the drone from the start to the end of the test, marked as the 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;

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

[0088] In actual application, the wind direction and wind force are monitored in real time. When the wind force is W 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 setting of the first flight number is to increase the power consumption of the drone so as to perform a more accurate analysis. The first flight number is set to 8 times. There is no fixed value for the first flight number. Usually, it is sufficient to make the power consumption of the drone reach more than 10%. For F3, 8 flights are performed with the relative angle as the first angle. After the 8 flights, the test power consumption is recorded as T(3,0°). Similarly, 8 flights are 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°) are obtained. The test power consumption of other wind force test experimental groups is analyzed in the same way. Since N1=2km and N2=8, the calculated flight distance is 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 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 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 rounded to four decimal places, and the wind power consumption relationship diagram is constructed as shown below. Figure 3 As shown, since the wind speed of F3 is 4.9m / s, the coordinates of F3 are (4.9, 1.375);

[0094] Calculate T(n,θ) / L, and mark the result as power consumption per unit angle, represented by the symbol EO, where θ does not include the seventh angle. Calculate EO / E, and mark the result as power consumption ratio, represented by the 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 when the drone is completely against the wind. However, in this embodiment, the relative angle between the drone's flight direction 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. 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 is rounded to four decimal places. The calculation of the remaining H(n,θ) is the same as that of 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 flying with the wind and against the wind. That is, the greater the wind force, the smaller the angular power consumption ratio of the drone, and the smaller the relative angle, the smaller the angular 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 influence function of the UAV'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;

[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 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;

[0101] In actual application, it is observed that Figure 3 The coordinate points in the graph conform to the exponential distribution, so the exponential regression method is used for regression analysis, 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 actual application, the greater the wind force, the greater the difference in power consumption between the drone 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 was found that the n-th coordinate point in the same wind test experimental group showed a linear distribution, so they were subjected to linear regression to obtain 10 angle power consumption proportional equations, corresponding to PCV1 to PCV 10 ,like Figure 5 As shown, Figure 5 The straight lines from top to bottom represent PCV1 to PCV 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. The angle power consumption ratio equation shows a linear distribution. If one point (180°, 1) is known, we only need to determine the other point to obtain 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 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, the PCV in different wind speeds 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. The lowest ratio distribution diagram is constructed as follows Figure 6 As shown, through Figure 6 It was found that the coordinate points also showed a linear distribution, so a linear regression analysis was performed on them, and the lowest proportion distribution equation was 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 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, and after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angular power consumption ratio;

[0108] In practical applications, by substituting the wind force WP into PCO = -0.0257×WP+1.0446, the angular power consumption ratio of the drone when the wind force is WP and the relative angle between the drone and the wind direction is 0° can be solved, and the coordinate point (0°, PCO), PCV n =c×θ+d. There are many different situations. 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. The calculation result is rounded to four decimal places. Substitute (0°, 0.9110) and (180°, 1) into PCV n =c×θ+d, solving for c=0.0005, d=0.911, and retaining 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 drone's flight direction and the wind direction. It 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 offshore wind turbines, 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 a layout diagram of the hangar and offshore wind turbines, including the longitude and latitude of the hangar and 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 hangar are calculated to obtain the relative angle and relative distance. The offshore wind turbines are 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 is not specifically demonstrated in this embodiment. Only the final position distribution map is 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 is not specifically demonstrated. 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 speed on the sea surface, control the drone to conduct inspections along the predetermined inspection route, and estimate the estimated total power consumption of the drone flying along the inspection route based on the location distribution map, wind direction and wind speed, 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 UAV is controlled to perform inspections along a predetermined inspection route, and the inspection route is marked on the location 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 a patrol 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] Number the inspection sub-routes and use 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, which is indicated by the symbol A. i Indicates that R is obtained i The length of the route is marked by the symbol Di Indicates that the route angle is determined in the same way as the flight angle.

[0123] In actual application, 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 UAV. 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. The route angles 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 , set WP equal to the real-time wind force and θ = A i Substitute into EPC = (a × e -b×WP )×(c×θ+d), calculate EPC;

[0125] Calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i Perform analysis and 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). Since 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 based on 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 other inspection sub-routes is 6.8m / s. When calculating R5, set WP 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 the calculation result to four decimal places, and then calculate EPC×D1=0.9153×15=13.7295. The result is rounded to four decimal places, indicating that the drone 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 consumption of R2 to R9 is 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 rounded 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 drone's battery level when it takes off from the hangar, marked as takeoff power and represented by the symbol PU. Get the drone's landing power threshold. The landing power threshold is a preset value, represented by the symbol PD. This is used to ensure that the drone still has enough power to return to the hangar after returning to the hangar. Even if there is a deviation during flight, resulting in excessive power consumption, it can still ensure that the drone can return to the hangar safely.

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

[0131] In actual application, the takeoff power PU is obtained as 85%, the landing power threshold PD is 20%, and the calculated PH = 65%. Further calculation shows that the total shooting power PK is 28%, that is, 28% of the drone's total power is 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), the calculated result is marked as the cruise power consumption efficiency, represented by the symbol EPD;

[0133] Get the comprehensive moving speed of the drone, marked as Q, and calculate (PK / EPD) / Q to get the total time the drone spends circling the offshore wind turbines, marked as TAL. Then get the number of offshore wind turbines, marked as V, and calculate TAL / V to get the inspection time allocated to each offshore wind turbine.

[0134] In practical applications, the reason for using the calculation result of θ = 90° as the cruise power consumption efficiency is that when a drone takes pictures of an offshore wind turbine, it often needs to take a 360° full-scale picture around the offshore wind turbine. At this time, no matter how the wind direction changes, the drone can approximately make a circular motion around the offshore wind turbine. The angle between the motion trajectory and the wind direction at this time has values ​​between 0° and 180°, and the time is relatively close. Therefore, it can be approximately considered that the drone is flying in a direction perpendicular to the wind direction, and neither consumes more power due to headwind nor consumes 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, and the comprehensive moving speed of the UAV is obtained to be 42km / h. The comprehensive moving speed represents the average moving speed of the UAV when performing a surround shooting and inspection task on the offshore wind turbines, 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 is rounded to two decimal places, and the number of offshore wind turbines V is obtained to be 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 Figure 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 impact function; Step S1 includes the following sub-steps:

[0137] Step S101: select an open area and perform flight tests on the UAV in different wind environments, and record the test data;

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

[0139] Step S1011: selecting an open area, which is a plain terrain with an open area having a diameter of a first test distance;

[0140] Step S1012: Obtain the maximum wind speed that the drone can withstand, set the starting wind speed, and define the range from the starting wind speed to the maximum wind speed as a wind speed interval.

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

[0142] Step S1014: number the test wind speeds in ascending order within the wind speed range, using the symbol W n Denotes, where n∈Z+ and n is the sequence number of W, Z+ represents a positive integer, and the maximum value of n is the first test quantity;

[0143] Step S1015, set the first number of wind test experimental groups, through the 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, which is a headwind direction. 180° means that the flight direction of the drone and the wind direction are the same, which is a downwind direction.

[0145] Step S1017, testing different wind force test 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 drone 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. The flight distance is the first test distance. After the flight is completed, the tester brings the drone back to the starting position and performs the flight again. 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 start to the end of the test, marked as 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;

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

[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 the 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 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 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;

[0155] Step S1024: Establish a plane rectangular coordinate system with θ as the horizontal axis and H(n,θ) as the vertical axis, and name it "angle power consumption ratio relationship diagram." 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 UAV'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;

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

[0158] Step S1031, perform regression analysis on the wind power consumption relationship diagram, and regress the wind power consumption relationship diagram by exponential regression to obtain the 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;

[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, obtain all PCVs when θ=0° n and marked as PCO n , get PCO n 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 minimum proportion distribution equation has the format of 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 proportional distribution equation 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, and after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angular power consumption ratio;

[0163] Step S1036, WPC is the wind power consumption efficiency in the headwind direction. Multiplying it with PCR can estimate the wind power consumption efficiency of the drone during flight based on the angle between the drone's flight direction and the wind direction. It 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);

[0164] Step S2: Obtain a layout diagram of the hangar and the offshore wind turbines, and construct 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, the layout diagram including the longitude and latitude of the hangar and the longitude and latitude of the wind turbine;

[0166] Step S202: Establish a plane rectangular coordinate system with the hangar's longitude and latitude as the origin, due east as the X-axis, and due north as the Y-axis, and name it a location distribution map;

[0167] Step S203: Calculate 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 relative distance, and mark the offshore wind turbine on 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 UAV to perform inspections along the predetermined inspection route, and estimating the total power consumption of the UAV 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, which are marked as real-time wind direction and real-time wind force respectively;

[0170] Step S302: Control the drone to perform inspections along a predetermined inspection route, and mark the inspection route on the location distribution map. The inspection route is composed of a first number of straight lines, and each straight line is named 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, which is indicated by the symbol A. i Indicates that R is obtained i The length of the route is marked by the symbol D i Indicates that the route angle is determined in the same way as the flight angle.

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

[0173] Step S305, calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i Perform analysis and 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: Obtain the power level of the drone when it takes off from the hangar, marked as takeoff power and represented by the symbol PU. Obtain the landing power threshold of the drone. The landing power threshold is a preset value, represented by the symbol PD. It is used to ensure that the drone still has enough power to reach the landing power threshold after returning to the hangar. Even if there is a deviation during flight, resulting in excessive power consumption, the drone can still return to the hangar safely.

[0176] Step S402: Calculate PU-PD, mark the result as PH, and then calculate PH-EPU to obtain the total power consumption of the shooting, 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), the calculated result is marked as the cruise power consumption efficiency, represented by the symbol EPD;

[0178] In step S404, the comprehensive moving speed of the drone is obtained, marked as Q, and (PK / EPD) / Q is calculated to obtain the total time the drone spends circumnavigating the offshore wind turbines, marked as TAL. The number of offshore wind turbines is then obtained, marked as V, and TAL / V is calculated to obtain the inspection time that can be allocated to each offshore wind turbine.

[0179] In 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 via 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 a method for inspecting offshore wind turbines based on a drone hangar are executed to achieve the following functions: testing 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; obtaining a layout diagram of the hangar and the offshore wind turbine, and constructing a position distribution diagram based on the position information in the layout diagram; estimating the estimated total power consumption of the drone flying on the inspection route based on the position distribution diagram, wind direction and wind force and in combination with the power consumption influence function; and evaluating the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption.

[0180] In addition, the logical instructions in the above-mentioned memory can be implemented in the form of a software functional unit 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, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute 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 magnetic disk or an optical disk.

[0181] Example 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-mentioned 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 position distribution map through the position information in the layout diagram; estimate 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 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 embodiments, the embodiments of the present invention can be provided as methods, systems or computer program products. Based on this understanding, the above technical solutions, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of 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 certain parts of the embodiment.

[0183] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. 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 them. 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 drone during flight and the wind direction and wind force is named the power consumption impact 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 wind direction and 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 force, and the power consumption impact function; Assess the inspection time that can be allocated to each offshore wind turbine based on the estimated total power consumption; The relationship between the power consumption of the drone during flight and the wind direction and wind force is called the power consumption impact function, which includes the following sub-steps: Select an open area and conduct 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; Analyzing the influence function of the drone's power consumption on wind force and wind direction based on the wind power consumption relationship diagram and the angle power consumption ratio 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 the 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 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 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 the format of PCO=f×WP+g, where 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 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, and after solving for the values ​​of c and d, we get PCR=c×θ+d, where PCR is the angular 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 drone's flight direction 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).

2. The offshore wind turbine inspection method based on a drone hangar according to claim 1 is characterized in that: Select an open area and conduct 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 has 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 use the starting wind speed to the maximum wind speed as a range, named wind speed range; The wind speed interval is evenly divided into a first test number of subintervals, which are named wind speed subintervals. The interval between two adjacent wind speed subintervals is marked as a test wind speed, and the starting wind speed is also marked as a test wind speed. The test wind forces are numbered in the order of small to large in the wind force range, and the symbol W is used to identify the wind forces. n Denotes, where n∈Z+ and n is the sequence number of W, Z+ represents a positive integer, and the maximum value of n is the first test quantity; Set the first test number of wind test experimental groups, 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, second angle, third angle, fourth angle, fifth angle, sixth angle and seventh angle. The flight angle is the angle between the flight direction of the drone and the wind direction. The flight angle increases in sequence, where the first angle is 0° and 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 groups are tested based on the flight angle and the test data are recorded.

3. The offshore wind turbine inspection method based on a drone hangar according to claim 2 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 drone 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. The flight distance is the first test distance. After the flight is completed, the tester brings the drone back to the starting position and performs the flight again. Each flight angle performs the first number of flights. For each flight angle, record the power consumed by the drone from the start to the end of the test, marked as the 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; 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.

4. The offshore wind turbine inspection method based on a drone hangar according to claim 3 is characterized in that: Calculating and constructing a wind power consumption relationship diagram and an angle power consumption ratio relationship diagram based on 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 Corresponding W n And the unit power consumption is entered into the wind power consumption relationship diagram; Calculate T(n,θ) / L, and mark the result as power consumption per unit angle, represented by the symbol EO, where θ does not include the seventh angle. Calculate EO / E, and mark the result as power consumption ratio, represented by the 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 an angle power consumption proportional relationship diagram. H(n,θ) is entered into the angle power consumption proportional relationship diagram according to the corresponding θ.

5. The offshore wind turbine inspection method based on a drone hangar according to claim 4 is characterized in that: Obtaining a layout diagram of the hangar and 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 hangar's longitude and latitude 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 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. The offshore wind turbines are marked on the location distribution map according to the relative angle and relative distance.

6. The offshore wind turbine inspection method based on a drone hangar according to claim 5 is characterized in that: Obtaining the wind direction and 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 force, and the power consumption impact 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 inspections along a predetermined inspection route, marking the inspection route on the location distribution map, wherein the inspection route is composed of a first number of straight lines, and naming each straight line as an inspection sub-route; Number the inspection sub-routes and use 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, which is indicated by the symbol A. i Indicates that R is obtained i The length of the route is marked by the symbol D i Indicates that the size of the route angle is determined to be the same as the flight angle; For R i , set WP equal to the real-time wind force and θ = A i Substitute into EPC = (a × e -b×WP )×(c×θ+d), calculate EPC; Calculate EPC×D i , mark the calculated result as the estimated sub-power consumption, for all R i Perform analysis and then calculate the sum of the estimated sub-power consumption to obtain the estimated total power consumption.

7. The offshore wind turbine inspection method based on a drone hangar according to claim 6 is characterized in that: Evaluating the inspection time allotted to each offshore wind turbine based on the estimated total power consumption includes the following sub-steps: Obtain the drone's battery level when it takes off from the hangar, marked as takeoff power and represented by the symbol PU. Obtain the drone's landing power threshold. The landing power threshold is a preset value, represented by the symbol PD. This ensures that the drone still has enough power to return to the hangar after returning to the hangar. Even if there is a deviation during flight, resulting in excessive power consumption, the drone can still return to the hangar safely. Calculate PU-PD and mark the result as PH. Then calculate PH-EPU to get the total power consumption of the 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), the calculated result is marked as the cruise power consumption efficiency, represented by the symbol EPD; The comprehensive moving speed of the drone is obtained, marked as Q, and (PK / EPD) / Q is calculated to obtain the total time the drone spends circling the offshore wind turbines, marked as TAL. The number of offshore wind turbines is then obtained, marked as V, and TAL / V is calculated to obtain the inspection time that can be allocated to each offshore wind turbine.

8. 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 according to any one of claims 1 to 7, 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 the power consumption impact function; The layout acquisition module is used to obtain a layout diagram of the hangar and the offshore wind turbines, and to construct a location distribution map based on 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 perform inspections along a predetermined inspection route, and estimate the estimated 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; 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.

Images