Inspection route generation method and device, electronic equipment, chip and storage medium
By determining the observation points in the inspection route and adjusting the drone arrival time based on the historical speed sequence, the problem of detection of non-uniform rotary fans is solved, and no shutdown detection is achieved, which improves detection efficiency and safety of fan operation.
Patent Information
- Application Number
- CN202311624421.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-11-29
- Publication Date
- 2025-05-30
AI Technical Summary
The prior art is difficult to effectively detect fans that rotate non-uniformly at the fan, resulting in the need for fan shutdown for inspection, affecting power generation capacity and cumbersome operation.
The detection of variable-speed rotating fan is achieved by determining the location of the observation point in the patrol route and determining the time when the drone reaches each observation point based on the fan's historical speed sequence.
The inspection can be completed without the fan shutdown, which improves the detection efficiency and ensures the safety of fan operation and the stability of production capacity.
Smart Images
Figure CN120063260A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of UAV trajectory planning, and in particular to a method for generating an inspection route, an inspection route generation device, an electronic device, a chip, and a computer-readable storage medium. Background Art
[0002] For a running wind turbine, it is necessary to perform inspections to ensure its safe operation. In related technologies, the collected trajectories are for the overall operation image of the wind turbine, and can only detect wind turbines in a uniform speed state or a stationary state. However, in actual operation, wind turbines often do not rotate at a uniform speed. Therefore, it is often necessary to stop the wind turbine for inspection, which affects power generation capacity and is cumbersome to operate. Summary of the Invention
[0003] Embodiments of this application provide a method for generating an inspection route, an inspection route generation device, an electronic device, a chip, and a computer-readable storage medium.
[0004] The technical solution of the embodiments of this application is implemented as follows:
[0005] In a first aspect, embodiments of this application provide a method for generating an inspection route, including:
[0006] Determine N observation points, and the N observation points form the inspection route;
[0007] Obtain the historical rotation speed sequence of the wind turbine;
[0008] Based on the historical rotation speed sequence, determine the arrival time of the UAV at each of the N observation points; N is a positive integer.
[0009] In a second aspect, embodiments of this application provide an inspection route generation device, including:
[0010] A processing unit: configured to determine N observation points, and the N observation points form the inspection route;
[0011] An acquisition unit: configured to obtain the historical rotation speed sequence of the wind turbine;
[0012] The processing unit is further configured to determine the arrival time of the UAV at each of the N observation points based on the historical rotation speed sequence; N is a positive integer.
[0013] In a third aspect, this application provides an electronic device, including: a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute any one of the inspection route generation methods provided by the embodiments of this application.
[0014] Fourthly, this application provides a chip, including: a processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes any one of the inspection route generation methods provided by the embodiments of this application.
[0015] Fifthly, this application provides a computer-readable storage medium, configured to store a computer program, and the computer program enables a computer to execute any one of the inspection route generation methods provided by the embodiments of this application.
[0016] For the inspection route generation method provided by the embodiments of this application, the positions of the observation points in the inspection route are first determined, and then the time when the drone reaches each observation point is determined based on the historical rotation speed of the fan. It can detect the fan with variable-speed rotation and complete the detection without the fan stopping, ensuring production capacity. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 It is a schematic diagram of the inspection route provided by the embodiment of this application Figure 1 ;
[0018] Figure 2 It is a schematic diagram of the implementation process of the inspection route generation method provided by the embodiment of this application Figure 1 ;
[0019] Figure 3 It is a schematic diagram of the inspection route provided by the embodiment of this application Figure 2 ;
[0020] Figure 4 It is a schematic diagram of the inspection route provided by the embodiment of this application Figure 3 ;
[0021] Figure 5 It is a schematic diagram of the Fibonacci spiral provided by the embodiment of this application;
[0022] Figure 6 It is a schematic diagram of the frame difference processing flow provided by the embodiment of this application;
[0023] Figure 7 It is a schematic diagram of the image collected by the fan provided by the embodiment of this application;
[0024] Figure 8 It is a schematic diagram of the frame difference image provided by the embodiment of this application Figure 1 ;
[0025] Figure 9 It is a schematic diagram of the frame difference image provided by the embodiment of this application Figure 2 ;
[0026] Figure 10 It is a schematic diagram of the images of various parts of the paddle collected provided by the embodiment of this application;
[0027] Figure 11 Schematic diagram for identifying blade defects provided by an embodiment of the present application;
[0028] Figure 12 Schematic structural diagram of an inspection route generation device provided by an embodiment of the present application;
[0029] Figure 13 Schematic structural diagram of an electronic device provided by an embodiment of the present application;
[0030] Figure 14 Schematic structural diagram of a chip provided by an embodiment of the present application. Detailed implementation manners
[0031] Next, the technical solutions in the embodiments of the present application will be described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.
[0032] It should be noted that in the embodiments of the present application, the term "and / or" only describes the association relationship of associated objects and indicates that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the embodiments of the present application, the character " / " generally represents an "or" relationship between the associated objects before and after.
[0033] In the description of the embodiments of the present application, the term "corresponding" can represent a direct or indirect corresponding relationship between two, can also represent an association relationship between two, or can be an indication and being indicated, configuration and being configured, etc. relationships.
[0034] To facilitate the understanding of the technical solutions in the embodiments of the present application, the related technologies in the embodiments of the present application are described below. The following related technologies can be arbitrarily combined with the technical solutions in the embodiments of the present application as optional solutions, and they all fall within the protection scope of the embodiments of the present application.
[0035] Track planning TSP: Optimize and analyze with the aim of the shortest path of the observation point set, and finally obtain the track path with the shortest flight distance.
[0036] In the related technology, the overall image of the wind turbine is collected and analyzed, refer to Figure 1 , Figure 1 Schematic diagram of the inspection route provided by an embodiment of the present application Figure 1 , refer to Figure 1In the left and right figures, the flight path of the drone is to fly in a 360-degree spiral around the wind turbine from top to bottom (or from bottom to top) for collection. This method can only detect wind turbines in a uniform or stationary state, and it cannot collect details of the blades. Moreover, the state of the wind turbine is often judged based on whether there are abnormalities in the blades. Therefore, judging based on the images collected in this way will lead to inaccurate judgment results of the wind turbine state.
[0037] Figure 2 Schematic implementation process of the inspection route generation method provided by the embodiment of the present application Figure 1 As Figure 2 shown, the embodiment of the present application provides an inspection route generation method, and the method includes the following steps:
[0038] Step 201: Determine N observation points, and the N observation points form the inspection route.
[0039] In an alternative embodiment of the present application, the inspection route is a route for a single blade.
[0040] For the detection of a single blade, it is necessary to detect the front and back of the blade. Some of the observation points designed in the present application are on the front of the blade, and some are on the back of the blade; in actual application, observation points can also be set at the top of the blade to detect the top of the blade.
[0041] Refer to Figure 3 , Figure 3 Schematic diagram of the inspection route provided by the embodiment of the present application Figure 2 As Figure 3 shown, in this embodiment, the blade is in a stationary state, and the inspection route has 15 observation points, 7 are evenly distributed on the front of the blade, 1 is set at the top of the blade, and 7 are set on the back of the blade.
[0042] For a running wind turbine, the blade is in a rotating state, so the inspection route corresponding to Figure 3 shows a curved state in space, as Figure 4 shown, Figure 4 Schematic diagram of the inspection route provided by the embodiment of the present application Figure 3 , Figure 4 The left figure is the distribution diagram of the observation points on the front of the blade, Figure 4 The middle figure is the distribution diagram of the observation points on the front of the blade and the observation points at the top of the blade, Figure 4 The right figure is the distribution diagram of the observation points on the front of the blade, the observation points at the top of the blade, and the observation points on the back of the blade. Observation point 1 is located at a position close to the central axis of the wind turbine on the front of the blade, observation point 15 is located at a position close to the central axis of the wind turbine on the back of the blade, and observation point 8 is the measurement point at the top of the blade. It can be seen that for the inspection navigation with evenly distributed observation points, its inspection curve on the front is similar to the Fibonacci spiral. Refer toFigure 5 , Figure 5 This is a schematic diagram of the Fibonacci spiral provided by the embodiment of the present application. The inspection curve on its back is a curve with a gradually decreasing radius.
[0043] It can be understood that a fan generally has three blades. Therefore, three flight paths can be designed to measure the three blades respectively.
[0044] It should be noted that the observation points can be designed according to actual applications, can be designed according to the historical state of the fan, can also be designed according to the length of the blade, can be evenly distributed or unevenly distributed, and the present application does not limit this.
[0045] Step 202: Obtain the historical rotation speed sequence of the fan.
[0046] In an alternative embodiment of the present application, the obtaining of the historical rotation speed sequence of the fan includes:
[0047] Hover the drone directly in front of the fan;
[0048] Collect multiple front-view image frames of the fan within a preset time;
[0049] Based on the multiple front-view image frames, obtain the historical rotation speed sequence.
[0050] In actual application, when the drone identifies the fan target and the relative pose relationship, the hovering position of the drone can be adjusted according to the size of the fan blade. As a preferred embodiment of the present application, the drone can hover at a position 1.5 times the blade length directly in front of the fan to collect images of the fan.
[0051] In an alternative embodiment of the present application, the obtaining of the historical rotation speed sequence based on the multiple front-view image frames includes:
[0052] Perform frame difference processing on the multiple front-view image frames to obtain multiple frame difference images;
[0053] Based on the offset angles of the blades in the multiple frame difference images, obtain multiple historical rotation speeds; wherein, the multiple historical rotation speeds correspond to the multiple frame difference images one by one, and the multiple historical rotation speeds form the historical rotation speed sequence.
[0054] Refer to Figure 6 , Figure 6 This is a schematic diagram of the frame difference processing flow provided by the embodiment of the present application. As shown in Figure 6As shown in the figure, frame difference processing means performing comparison (subtracting the absolute value or performing an exclusive OR operation) between the image at the next moment and the image at the previous moment on a series of continuously acquired images according to the temporal relationship, so as to obtain a frame difference image, and then performing thresholding processing to retain the pixel changes caused by the rotation of the fan blades, thereby realizing the identification of the fan state and calculating the speed of the fan.
[0055] Reference Figure 7 , Figure 7 is a schematic diagram of the image acquired by the fan provided in the embodiment of the present application. The image enclosed by the rectangle in the figure is the fan image.
[0056] After using a neural network to perform target recognition on the image acquired by the drone and segmenting the drone, a corresponding binary image can be obtained.
[0057] Reference Figure 8 , Figure 8 is a schematic diagram of the frame difference image provided in the embodiment of the present application Figure 1 , such as Figure 8 shown, the three images in the first row correspond to the frame difference images of the fan in the stationary state, the three images in the second row correspond to the frame difference images of the fan in the low-speed rotation state, and the three images in the third row correspond to the frame difference images of the fan in the high-speed rotation state.
[0058] For a stationary fan, the fan in its adjacent frame images remains unchanged. For a rotating fan, different speeds will result in different angles between the blades. The convex hull detection method can be used to obtain the angle between the blades. At the same time, combined with the sampling frequency of the camera, the state of the fan corresponding to the current adjacent frame images can be calculated. Schematically, taking the frame difference image in the low-speed rotation state as an example, morphological filling of internal holes is performed on the frame difference image, and then convex hull detection is performed to obtain an image as shown in Figure 9 shown, Figure 9 is a schematic diagram of the frame difference image provided in the embodiment of the present application Figure 2 , combined with the connection line from the convex hull point to the center of the connected domain, the acute angle of rotation can be obtained. Combined with the sampling interval time of the camera, the fan rotation speed information corresponding to this frame difference image can be obtained through the following formula SV = JD / t, where JD is the average acute angle after convex hull detection of the three blades, and t represents the interval time between two frames of images.
[0059] For the offset of the blades in multiple frame difference images, a historical speed can be obtained for each frame difference image.
[0060] Step 203: Based on the historical rotation speed sequence, determine the arrival time of the drone at each of the N observation points; N is a positive integer.
[0061] In an optional implementation manner of the present application, the historical rotation speed sequence includes N - 1 historical rotation speeds; based on the historical rotation speed sequence, determining the arrival time of the UAV at each of the N observation points includes:
[0062] Determining the initial time when the UAV arrives at the first observation point;
[0063] Based on the initial time and the N - 1 historical rotation speeds, calculating the intermediate time when the UAV arrives at each of the second to Nth observation points; wherein, the N - 1 historical rotation speeds correspond one-to-one to the second to Nth observation points;
[0064] Based on the historical rotation speed sequence, adjusting the intermediate time of each of the second to Nth observation points to obtain the arrival time of each observation point.
[0065] In practical applications, in the inspection route, there are not only observation points, but also the time when the UAV arrives at each observation point needs to be determined in order to collect appropriate images.
[0066] Exemplarily, a historical rotation speed sequence SS = [SV1, SV2, SV3, SV4, …, SVN-1] including N - 1 historical rotation speeds can be obtained to determine the arrival time of the N observation points, because the time of the first observation point is the preset initial time St1.
[0067] Determining the angles between adjacent observation points. It should be noted that the angle here refers to the included angle between the line connecting the adjacent observation points and the central axis of the fan.
[0068] Exemplarily, for the case where the observation points are evenly distributed, if it is desired to collect a complete blade image when the blade rotates one week, then the angle pv between adjacent observation points = 360 / N. If the observation points are not evenly distributed, the angle pv between adjacent observation points can be calculated according to the actual situation, and the present application does not make any limitations.
[0069] Then the intermediate time St2 when the UAV arrives at the second observation point = St1 + pv1 / SV1, where pv1 represents the included angle between the line connecting the second observation point and the central axis of the fan and the line connecting the first observation point and the central axis of the fan.
[0070] The intermediate time St3 when the UAV arrives at the third observation point = St2 + pv2 / SV2, where pv2 represents the angle between the line connecting the third observation point and the central axis of the fan and the line connecting the second observation point and the central axis of the fan.
[0071] By analogy, the mid-time StN when the UAV reaches the Nth observation point is StN = StN-1 + pvN-1 / SVN-1, where pvN-1 represents the angle between the line connecting the Nth observation point and the central axis of the fan and the line connecting the (N-1)th observation point and the central axis of the fan.
[0072] In this way, the mid-time when the UAV reaches each of the N observation points is calculated.
[0073] Then, analyze the historical speed sequence SS to obtain the adjustment weight.
[0074] Schematically, the analysis and processing can be carried out in the following way. Calculate the evaluation speed YV = (SV1 + SV2 + … + SVN-1) / (N - 1) of all historical rotational speeds in the historical speed sequence SS, and calculate the time adjustment amount TL(i) = SV(i) - YV corresponding to each speed, where i ∈ (1, 2, 3…N - 1).
[0075] Calculate the occurrence probability P(i) = sl / (N - 1) corresponding to each time adjustment amount, where i ∈ (1, 2, 3…N - 1).
[0076] The occurrence probabilities of different adjustment amounts are different. The greater the probability, the greater the impact during adjustment.
[0077] Adjust each mid-time through the following formula: where Rt is the adjusted arrival time, St is the mid-time, I is the number of observation points the UAV has flown over, max[SV(i)] is the maximum speed value among SV1 to SV(i).
[0078] Based on this, in an alternative embodiment of the present application, adjusting the mid-time of each observation point based on the historical rotational speed sequence to obtain the arrival time of each observation point includes:
[0079] Calculate the average value of the N - 1 historical rotational speeds, and calculate the change amount of each rotational speed in the N - 1 historical rotational speeds relative to the average value;
[0080] Calculate the occurrence probability of the change amount of each rotational speed in the N - 1 historical rotational speeds relative to the average value;
[0081] Based on the change amount of each rotational speed in the N - 1 historical rotational speeds relative to the average value and its occurrence probability, calculate the time adjustment amount of each observation point from the second observation point to the Nth observation point;
[0082] Based on the time adjustment amount of each observation point from the second observation point to the Nth observation point, adjust the mid-time of each observation point to obtain the arrival time of each observation point.
[0083] The adjustment logic for the intermediate moment of the drone is that the faster the fan speed, the faster the drone needs to reach the observation point, and the smaller the interval value. If the drone arrives at the observation point in advance, no useful information will be collected. However, if it arrives a little later, useful information can be collected, although the quality may be poor at most. Therefore, a smaller interval is better as it can arrive earlier. Using a constant speed is more accurate for the earlier observation points, and for the later observation points, due to the speed change in the middle, more adjustments are needed.
[0084] After obtaining the optimal arrival time of the observation point for a single blade as described above, the observation points are connected and fitted into a curve, which is the optimal acquisition route. According to the corresponding time values of each optimal observation point, the speed of the drone is adjusted so that it flies to the corresponding position at the corresponding time to collect images, thus realizing the autonomous cruise acquisition of the drone in a variable-speed scenario. Schematically, referring to Figure 10 , Figure 10 is a schematic diagram of the images of various parts of the blade collected in the embodiment of the present application.
[0085] Using a neural network method to identify defects in the collected images, referring to Figure 11 , Figure 11 is a schematic diagram of blade defect identification provided in the embodiment of the present application. The input of the network is the collected fan image, and the output is the corresponding abnormal bounding box information and abnormal type information. The neural network is trained by a large number of images with manually labeled tags.
[0086] Through the technical solution of the present application, it can adapt to a fan rotating at a variable speed, adjust the flight parameters of the drone according to the different rotation speeds of the fan, and complete the detection of the fan without stopping the fan, improving the detection efficiency. Moreover, the solution of the present application performs acquisition for a single blade, making the quality of the collected blade images better, making the final analysis result more accurate, and ensuring the safe operation of the fan.
[0087] The embodiment of the present application also provides an inspection route generation device 1200, referring to Figure 12 , the inspection route generation device 1200 in this embodiment includes:
[0088] A processing unit 1210: used to determine N observation points, and the N observation points form the inspection route;
[0089] An acquisition unit 1220: used to acquire the historical rotation speed sequence of the fan;
[0090] The processing unit 1210 is further used to determine the arrival time of the drone at each of the N observation points based on the historical rotation speed sequence; N is a positive integer.
[0091] In the embodiments of the present application, the inspection route is a route for a single blade; among the N observation points, at least one observation point is located on the front of the blade to be detected, and at least one observation point is located on the back of the blade to be detected.
[0092] In the embodiments of the present application, the obtaining unit 1220: specifically used to hover the unmanned aerial vehicle directly in front of the wind turbine; collect a plurality of front-view image frames of the wind turbine within a preset time; based on the plurality of front-view image frames, obtain the historical rotation speed sequence.
[0093] In the embodiments of the present application, the obtaining unit 1220: specifically used to perform frame difference processing on the plurality of front-view image frames to obtain a plurality of frame difference images; based on the offset angles of the blades in the plurality of frame difference images, obtain a plurality of historical rotation speeds; wherein, the plurality of historical rotation speeds correspond to the plurality of frame difference images one by one, and the plurality of historical rotation speeds form the historical rotation speed sequence.
[0094] In the embodiments of the present application, the historical rotation speed sequence includes N - 1 historical rotation speeds; the processing unit 1210: specifically used to determine the initial moment when the unmanned aerial vehicle reaches the first observation point; based on the initial moment and the N - 1 historical rotation speeds, calculate the intermediate moments when the unmanned aerial vehicle reaches each of the second to Nth observation points; wherein, the N - 1 historical rotation speeds correspond to the second to Nth observation points one by one; based on the historical rotation speed sequence, adjust the intermediate moments of each of the second to Nth observation points to obtain the arrival moments of each observation point.
[0095] In the embodiments of the present application, the processing unit 1210: specifically used to calculate the average value of the N - 1 historical rotation speeds, and calculate the change amount of each rotation speed in the N - 1 historical rotation speeds relative to the average value; calculate the occurrence probability of the change amount of each rotation speed in the N - 1 historical rotation speeds relative to the average value; based on the change amount of each rotation speed in the N - 1 historical rotation speeds relative to the average value and its occurrence probability, calculate the moment adjustment amount of each of the second to Nth observation points; based on the moment adjustment amount of each of the second to Nth observation points, adjust the intermediate moments of each observation point to obtain the arrival moments of each observation point.
[0096] Those skilled in the art should understand, Figure 12 The implementation functions of the various units in the shown inspection route generation device 1200 can be understood with reference to the relevant descriptions of the foregoing method. Figure 12 The functions of the various units in the shown inspection route generation device 1200 can be implemented by a program running on a processor, or can also be implemented by specific logic circuits.
[0097] Figure 13 FIG. 1300 is a schematic structural diagram of an electronic device 1300 provided by an embodiment of the present application. Figure 13 As shown, the electronic device 1300 includes a processor 1310. The processor 1310 can call and run a computer program from a memory to implement the method in the embodiment of the present application.
[0098] Optionally, as Figure 13 shown, the electronic device 1300 may further include a memory 1320. Among them, the processor 1310 can call and run a computer program from the memory 1320 to implement the method in the embodiment of the present application.
[0099] Among them, the memory 1320 can be a separate device independent of the processor 1310 or integrated in the processor 1310.
[0100] Optionally, as Figure 13 shown, the electronic device 1300 may further include a transceiver 1330. The processor 1310 can control the transceiver 1330 to communicate with other devices. Specifically, it can send information or data to other devices or receive information or data sent by other devices.
[0101] Among them, the transceiver 1330 can include a transmitter and a receiver. The transceiver 1330 may further include an antenna, and the number of antennas can be one or more.
[0102] Specifically, the electronic device 1300 can be the inspection route generation device in the embodiment of the present application, and the electronic device 1300 can implement the corresponding processes implemented by the inspection route generation device in each method of the embodiment of the present application. For the sake of brevity, it will not be elaborated here.
[0103] Figure 14 FIG. 1400 is a schematic structural diagram of a chip according to an embodiment of the present application. Figure 14 As shown, the chip 1400 includes a processor 1410. The processor 1410 can call and run a computer program from a memory to implement the method in the embodiment of the present application.
[0104] Optionally, as Figure 14 shown, the chip 1400 may further include a memory 1420. Among them, the processor 1410 can call and run a computer program from the memory 1420 to implement the method in the embodiment of the present application.
[0105] Among them, the memory 1420 can be a separate device independent of the processor 1410 or integrated in the processor 1410.
[0106] Optionally, the chip 1400 may further include an input interface 1430. Among them, the processor 1410 may control the input interface 1430 to communicate with other devices or chips. Specifically, it may obtain information or data sent by other devices or chips.
[0107] Optionally, the chip 1400 may further include an output interface 1440. Among them, the processor 1410 may control the output interface 1440 to communicate with other devices or chips. Specifically, it may output information or data to other devices or chips.
[0108] The chip can be applied to the inspection route generation device in the embodiments of the present application, and the chip can implement the corresponding processes implemented by the inspection route generation device in each method of the embodiments of the present application. For the sake of brevity, it will not be elaborated here.
[0109] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip.
[0110] It should be understood that the processor in the embodiments of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiments may be completed by the integrated logic circuit in the hardware of the processor or instructions in software form. The above processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application may be directly embodied as being executed by the hardware decoding processor, or executed by a combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.
[0111] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include but not be limited to these and any other suitable types of memory.
[0112] It should be understood that the above-mentioned memory is by way of example but not limitation. For example, the memory in the embodiments of the present application can also be a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate SDRAM (DDR SDRAM), an enhanced SDRAM (ESDRAM), a synch link DRAM (SLDRAM), and a direct rambus random access memory (DR RAM), etc. That is to say, the memory in the embodiments of the present application is intended to include but not be limited to these and any other suitable types of memory.
[0113] An embodiment of the present application further provides a computer-readable storage medium for storing a computer program. The computer-readable storage medium can be applied to the inspection route generation device in the embodiment of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the inspection route generation device in each method of the embodiment of the present application. For the sake of brevity, it will not be elaborated here.
[0114] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.
[0115] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated here.
[0116] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in an electrical, mechanical, or other form.
[0117] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0118] In addition, the functional units in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.
[0119] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a patrol route generation device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.
[0120] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.
Claims
1. A method for generating an inspection route, characterized in that, it includes: Determine N observation points, and the N observation points form the inspection route; Obtain the historical rotational speed sequence of the wind turbine; Based on the historical rotational speed sequence, determine the arrival time of the UAV at each of the N observation points; N is a positive integer.
2. The inspection route generation method according to claim 1, characterized in that, The inspection route is a route for a single blade; among the N observation points, at least one observation point is located on the front of the blade to be detected, and at least one observation point is located on the back of the blade to be detected.
3. The inspection route generation method according to claim 2, characterized in that, The obtaining of the historical rotational speed sequence of the wind turbine includes: Hover the UAV directly in front of the wind turbine; Collect multiple front-view image frames of the wind turbine within a preset time; Based on the multiple front-view image frames, obtain the historical rotational speed sequence.
4. The inspection route generation method according to claim 3, characterized in that, The obtaining of the historical rotational speed sequence based on the multiple front-view image frames includes: Perform frame difference processing on the multiple front-view image frames to obtain multiple frame difference images; Based on the offset angles of the blades in the multiple frame difference images, obtain multiple historical rotational speeds; wherein, the multiple historical rotational speeds correspond to the multiple frame difference images one by one, and the multiple historical rotational speeds form the historical rotational speed sequence.
5. The inspection route generation method according to claim 1, characterized in that, The historical rotational speed sequence includes N - 1 historical rotational speeds; based on the historical rotational speed sequence, determining the arrival time of the UAV at each of the N observation points includes: Determine the initial time for the UAV to reach the first observation point; Based on the initial time and the N - 1 historical rotational speeds, calculate the intermediate times for the UAV to reach each of the second to Nth observation points; wherein, the N - 1 historical rotational speeds correspond to the second to Nth observation points one by one; Based on the historical rotational speed sequence, adjust the intermediate times for each of the second to Nth observation points to obtain the arrival time for each observation point.
6. The inspection route generation method according to claim 5, characterized in that, The adjusting of the intermediate time for each observation point based on the historical rotational speed sequence to obtain the arrival time for each observation point includes: Calculate the average value of the N - 1 historical rotational speeds, and calculate the change amount of each rotational speed in the N - 1 historical rotational speeds relative to the average value; Calculate the occurrence probability of the change amount of each rotational speed in the N - 1 historical rotational speeds relative to the average value; Based on the change amount of each rotational speed in the N - 1 historical rotational speeds relative to the average value and its occurrence probability, calculate the time adjustment amount for each of the second to Nth observation points; Based on the time adjustment amount for each of the second to Nth observation points, adjust the intermediate times of the respective observation points to obtain the arrival time for each observation point.
7. An inspection route generation device, It is characterized in that including a processing unit: configured to determine N observation points, and the N observation points form the inspection route an acquisition unit: configured to acquire the historical rotation speed sequence of the wind turbine the processing unit is further configured to determine the arrival time of the UAV at each of the N observation points based on the historical rotation speed sequence; N is a positive integer 8. An electronic device It is characterized in that including a processor and a memory, the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the inspection route generation method according to any one of claims 1-6 9. A chip It is characterized in that including a processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes the inspection route generation method according to any one of claims 1-6 10. A computer-readable storage medium It is characterized in that used to store a computer program, and the computer program causes a computer to execute the inspection route generation method according to any one of claims 1-6