Method and system for automatically generating inspection points for substation robots and unmanned aerial vehicles

Abstract

This invention discloses a method and system for automatically generating joint inspection points using substation robots and drones. The method includes: establishing a general spatial point shooting potential model and a spatial relationship model for both intelligent equipment based on substation structural data; designing a point selection method with joint shooting quality and inspection efficiency as optimization objectives based on the models and combined with shooting quality constraints and spatial constraints to obtain the optimal joint inspection points; and testing and verifying the optimal joint inspection points. The algorithm was validated in a virtual substation experimental platform. Results show that the proposed method can flexibly, quickly, and automatically generate high-quality inspection points suitable for intelligent equipment. Compared with other methods, the proposed joint inspection strategy using multiple intelligent equipment significantly improves shooting quality and inspection efficiency.

Description

Technical Field

[0001] This invention relates to the field of substation inspection technology, and in particular to a method and system for automatically generating inspection points by combining substation robots and drones. Background Technology

[0002] In recent years, scholars both domestically and internationally have conducted extensive research on the application of intelligent inspection equipment for power line inspection and photography, achieving considerable results. However, their focus is on reducing the energy consumption of intelligent equipment by using fewer inspection points and shorter inspection routes. This involves generating inspection points based on the spatial relationship between the intelligent equipment and power equipment to avoid obstruction and backlighting during shooting, and using ant colony algorithms to reduce the number of inspection points. UAV aerial image quality enhancement technologies are primarily aimed at high-altitude aerial photography and are not applicable to close-range shooting points of power equipment. For intelligent agent-based joint inspection, various intelligent equipment, including track-mounted and wheeled robots and fixed cameras, are used to construct a three-dimensional inspection system, but specific methods for the placement of inspection points have not been provided.

[0003] Current research on the automatic generation of high-quality inspection points for intelligent equipment in substations faces the following challenges: First, while the aim of setting inspection points for intelligent equipment is to obtain high-quality inspection images, image quality assessment is typically qualitative rather than quantitative, making it difficult to evaluate the quality of inspection points. Second, substations have a wide variety and large number of electrical devices, with complex electrical connections between them, resulting in highly complex spatial relationships between intelligent equipment and leading to high computational complexity and difficulty in solving the problem. Finally, the different constraints of various intelligent equipment, and the need to balance low energy consumption and high image quality in the setting of inspection points and imaging schemes, further complicate the solution to the joint inspection problem. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a method and system for automatically generating joint inspection points of substation robots and drones, which can solve problems such as insufficient shooting quality and high shooting energy consumption.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a method and system for automatically generating joint inspection points using substation robots and drones, comprising:

[0008] Based on the substation structural data, a general spatial point shooting potential model and spatial relationship model for dual intelligent equipment are established.

[0009] Based on the model and considering both shooting quality and spatial constraints, a point selection method is designed with the optimization objectives of combined shooting quality and inspection efficiency to obtain the optimal combined inspection point.

[0010] The optimal joint inspection points were tested and verified.

[0011] As a preferred embodiment of the automatic generation method and system for joint inspection points of dual intelligent equipment in substations according to the present invention, the shooting quality constraints include:

[0012]

[0013] Among them, X b This represents the point in space with the highest potential for image capture when the device surface is the only potential source. Let X be the point b The spatial relationship between intelligent equipment and equipment surfaces at a given point. For point Y a The spatial relationship between the intelligent equipment and the equipment surface at a given point, wherein the spatial relationship is either visible or invisible. When the device surface is used as the sole potential source for shooting, point X... b The shooting posture, When the device surface is used as the sole potential source point Y, a The shooting momentum, i is the number of substation equipment, j is the number of spatial grids, and t is the selection threshold;

[0014] when If the condition is not met, it means that the device cannot find a shooting point in the space that satisfies the spatial relationship constraint, that is, the line of sight is not blocked, and therefore no inspection point is generated for that surface.

[0015] As a preferred embodiment of the automatic generation method and system for joint inspection points of dual intelligent equipment in substations according to the present invention, the spatial constraints include:

[0016] Road constraints include,

[0017]

[0018] Among them, S road Let S represent the set of road points. robot S represents the robot's inspection point. UAV R indicates the inspection point of the drone. F This provides a viable space for intelligent equipment. This is the minimum flight altitude for drones.

[0019] As a preferred embodiment of the automatic generation method and system for joint inspection points of dual intelligent equipment in substations described in this invention, the spatial constraints also include line-of-sight constraints and safety constraints. The imaging device carried by the intelligent equipment has a maximum line-of-sight limit, and the intelligent equipment does not photograph equipment beyond the maximum line-of-sight at the inspection point.

[0020] When intelligent equipment is subjected to strong magnetic and electric fields in a substation, to ensure the safety of the power equipment and the intelligent equipment itself, constraints are set on the equipment surfaces to be inspected at the inspection points. These constraints can be expressed as follows:

[0021]

[0022] Among them, O ij The center of the device face. and These are the maximum line-of-sight distances for robots and drones, respectively. and The safe distances between power equipment and robots and drones are S, respectively. robot S represents the robot's inspection point. UAV This indicates the inspection point for the drone.

[0023] As a preferred embodiment of the automatic generation method and system for joint inspection points of dual intelligent equipment in substations according to the present invention, the optimization objectives include:

[0024] The objective function expression is as follows:

[0025] G3 = max(t) robot ,t UAV )·m-(t robot m robot +t UAV m UAV )

[0026] G = u1w1G1 + u2w2G3

[0027] Among them, G1 represents the first optimization of the target inspection image quality, and G3 represents the second optimization of the target inspection time positiveization result. robot and t UAV m represents the time spent by the robot and the drone capturing images of a single device surface, respectively. robot and m UAV N represents the number of equipment surfaces inspected by robots and drones, respectively. robot and N UAV denoted by , respectively, the number of inspection points performed by robots and drones, m is the surface of the equipment to be inspected covered by all inspection points, u1 and u2 are normalization factors, w1 and w2 are weighting factors added with different emphases on different optimization objectives, and G is the final objective function.

[0028] As a preferred embodiment of the automatic generation method and system for joint inspection points of dual intelligent equipment in substations described in this invention, it further includes:

[0029] Select the candidate point set and the inspection point set, and determine whether the candidate point set is empty;

[0030] If the candidate set is empty, the inspection ends directly;

[0031] If the candidate set is not empty, then determine the point with the largest objective function value in the candidate set, and use the simulated annealing algorithm to determine the current temperature and the termination temperature of each point;

[0032] If the current temperature is lower than the termination temperature, the point with the maximum objective function will be selected into the inspection point set.

[0033] If the current temperature is higher than the termination temperature, the simulated annealing algorithm is used, and an inspection point is selected based on the acceptance probability.

[0034] Remove the selected point from the candidate point set, update the state of the remaining candidate points, and repeatedly check whether the candidate set is empty.

[0035] As a preferred embodiment of the automatic generation method and system for joint inspection points of dual intelligent equipment in substations according to the present invention, the testing and verification includes:

[0036]

[0037] in, For drone inspection solutions, For drone inspection solutions, S Equ This shows the inspection status of each piece of equipment.

[0038] An automatic generation system for joint inspection points of dual intelligent equipment in substations is characterized by comprising a model building module, an optimal inspection point acquisition module, and a verification module.

[0039] The model building module is used to build a general spatial point shooting potential model and a spatial relationship model of dual intelligent equipment based on the substation structural data.

[0040] The optimal inspection point acquisition module is used to design a point selection method with joint shooting quality and inspection efficiency as optimization objectives based on the model and combining shooting quality constraints and spatial constraints, so as to obtain the optimal joint inspection point.

[0041] The verification module is used to test and verify the optimal joint inspection point.

[0042] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the method described above.

[0043] A computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method described above.

[0044] The beneficial effects of this invention are as follows: This invention proposes a method and system for automatically generating inspection points jointly by substation robots and drones. This invention studies the problem of intelligent inspection by intelligent equipment in substations and proposes an autonomous method for generating high-quality inspection points based on shooting potential and multi-objective optimization algorithms. The algorithm of this invention was verified in a virtual substation experimental platform. The results show that the proposed method can flexibly, quickly, and automatically generate high-quality inspection points suitable for intelligent equipment. Compared with other methods, the proposed joint inspection strategy of multiple intelligent equipment can significantly improve shooting quality and inspection efficiency. Simulation results of this invention demonstrate that the joint inspection mode has the characteristics of flexible point selection and high shooting quality in substation inspection shooting, and can fully leverage the advantages of various intelligent equipment to achieve full coverage and high-efficiency inspection of the inspection task. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0046] Figure 1 This is a flowchart of a method and system for automatically generating joint inspection points of substation robots and drones according to an embodiment of the present invention;

[0047] Figure 2 This invention provides an intelligent equipment joint inspection point autonomous generation strategy for a method and system for automatically generating joint inspection points of substation robots and drones, as an embodiment of the present invention.

[0048] Figure 3 This is an internal structural diagram of the computer equipment used in an embodiment of the present invention to provide a method and system for automatically generating joint inspection points of substation robots and drones. Detailed Implementation

[0049] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0050] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0052] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0053] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0054] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0055] Example 1

[0056] Reference Figure 1-3This is the first embodiment of the present invention, which provides a method and system for automatically generating joint inspection points of substation robots and drones, including:

[0057] Step 102: Based on the substation structure data, establish a general spatial point shooting potential model and spatial relationship model for dual intelligent equipment;

[0058] The process begins by rasterizing the three-dimensional space of the substation, dividing the entire substation space into two parts: a restricted space for intelligent equipment (including the space where electrical equipment is located and restricted spaces created by maintaining a safe distance from intelligent equipment) and a feasible space for intelligent equipment (including spatial grid points and ground road points). The final generated inspection point set should consist entirely of points located within the feasible space of the intelligent equipment.

[0059] Specifically, most components of power equipment in substations are rectangular or cylindrical. Inspection photography focuses on the surface features of the equipment. Therefore, to preserve these surface features, this invention proposes a rectangular model to represent the components of power equipment. In this way, various power devices in a substation will be represented as a combination of rectangular prisms. The inspection target of joint inspection is the rectangular surface of each rectangular component of the equipment to be inspected.

[0060] Step 104: Based on the model and combining shooting quality constraints and spatial constraints, design a point selection method with joint shooting quality and inspection efficiency as optimization objectives to obtain the optimal joint inspection point;

[0061] The shooting quality constraints include,

[0062]

[0063] Among them, X b This represents the point in space with the highest potential for image capture when the device surface is the only potential source. Let X be the point b The spatial relationship between intelligent equipment and equipment surfaces at a given point. For point Y a The spatial relationship between the intelligent equipment and the equipment surface at a given point, wherein the spatial relationship is either visible or invisible. When the device surface is used as the sole potential source for shooting, point X... b The shooting posture, When the device surface is used as the sole potential source point Y, a The shooting momentum is defined as follows: i represents the number of substation devices, j represents the number of spatial grids, and t represents the selection threshold.

[0064] It should be noted that, for the selection threshold t, since the relative shooting potential is used to measure the shooting quality of the candidate points, the determination of the threshold will vary with the substation scenario, inspection task, and evaluation indicators. This invention uses multiple sets of inspection points generated under different threshold conditions as multiple selection schemes, and adopts the TOPSIS-entropy weight method to determine the optimal selection scheme. First, the evaluation indicators are objectively weighted by the entropy weight method. Then, the optimal selection scheme is determined according to the TOPSIS method for the selection schemes under different threshold conditions. The threshold corresponding to this scheme is used as the shooting quality threshold t of this selection strategy.

[0065] It should be noted that when If the condition is not met, it means that the device cannot find a shooting point in the space that satisfies the spatial relationship constraint, that is, the line of sight is not blocked, and therefore no inspection point is generated for that surface.

[0066] Furthermore, the spatial constraints include,

[0067] Furthermore, road constraints include,

[0068]

[0069] Among them, S road Let S represent the set of road points. robot S represents the robot's inspection point. UAV R indicates the inspection point of the drone. F This provides a viable space for intelligent equipment. This is the minimum flight altitude for drones.

[0070] It should be noted that the spatial constraints also include line-of-sight constraints and safety constraints. The imaging equipment on the intelligent equipment has a maximum line-of-sight limit, and the intelligent equipment will not photograph equipment beyond the maximum line-of-sight at the inspection point.

[0071] Furthermore, when intelligent equipment is subjected to strong magnetic and electric fields in a substation, to ensure the safety of both the electrical equipment and the intelligent equipment itself, constraints are set on the equipment surfaces to be inspected at the inspection points. These constraints can be expressed as follows:

[0072]

[0073] Among them, O ij The center of the device face. and These are the maximum line-of-sight distances for robots and drones, respectively. and The safe distances between power equipment and robots and drones are S, respectively. robot S represents the robot's inspection point. UAV This indicates the inspection point for the drone.

[0074] It should be noted that the optimization objective includes the objective function expression as follows:

[0075]

[0076] G2=t robot m robot +t UAV m UAV +t adj (N robot +N UAV )

[0077]

[0078] u2 = 1 / [max(t) robot ,t UAV )·m+t adj ·N]

[0079] G3 = max(t) robot ,t UAV )·m-(t robot m robot +t UAV m UAV )

[0080] G = u1w1G1 + u2w2G3

[0081] Wherein, G1 represents the image quality of the first optimized target inspection, G2 represents the inspection time of the second optimized target, G3 represents the positive result of the inspection time of the second optimized target, and t robot and t UAV t represents the time spent by the robot and the drone capturing images of a single device surface, respectively. adj The time it takes for intelligent equipment to adjust its posture at the inspection point, m robot and m UAV N represents the number of equipment surfaces inspected by robots and drones, respectively. robot and N UAV represents the number of inspection points performed by robots and drones respectively, m is the surface of the equipment to be inspected covered by all inspection points, u1 and u2 are normalization factors, w1 and w2 are weighting factors added with different emphases on different optimization objectives, G is the final objective function, N is the total number of inspection points, and K is the number of spatial grids.

[0082] It should be noted that the process of generating inspection points is a continuous process of selecting optimal candidate points: continuously selecting points with the largest objective function values ​​from the candidate points to add to the inspection point set, and removing selected points from the candidate set. This is a greedy process. To avoid obtaining a local optimum rather than a global optimum during the solution process, this invention uses a simulated annealing algorithm to determine the selection of the next inspection point, thereby enhancing the global optimization capability of the point selection strategy. Furthermore, the set with the largest sum of objective function values ​​for all points is selected from the multiple generated inspection point sets as the final generated inspection point set. Each inspection point includes the corresponding inspection equipment surface and zoom level.

[0083] Furthermore, a candidate point set and an inspection point set are selected, and it is determined whether the candidate point set is empty;

[0084] Furthermore, if the candidate set is empty, the inspection will end directly.

[0085] Furthermore, if the candidate set is not empty, the point with the largest objective function value in the candidate set is determined, and the simulated annealing algorithm is used to determine the difference between the current temperature and the termination temperature of each point.

[0086] Furthermore, if the current temperature is lower than the termination temperature, the point where the objective function is maximized will be selected into the inspection point set.

[0087] Furthermore, if the current temperature is higher than the termination temperature, the simulated annealing algorithm is used, and an inspection point is selected based on the acceptance probability.

[0088] Furthermore, the selected point is removed from the candidate point set, the state of the remaining candidate points is updated, and the candidate set is repeatedly checked to see if it is empty.

[0089] Step 106: Test and verify the optimal joint inspection point.

[0090] The test verification includes,

[0091]

[0092] in, For drone inspection solutions, For drone inspection solutions, S Equ This shows the inspection status of each piece of equipment.

[0093] It should be noted that this invention studies the problem of intelligent inspection by intelligent equipment in substations, and proposes an autonomous method for generating high-quality inspection points based on shooting potential and multi-objective optimization algorithms. The algorithm was validated in a virtual substation experimental platform. The results show that the proposed method can flexibly, quickly, and automatically generate high-quality inspection points suitable for intelligent equipment. Compared with other methods, the proposed joint inspection strategy using multiple intelligent equipment can significantly improve shooting quality and inspection efficiency.

[0094] The simulation results of this invention demonstrate that the joint inspection mode has the advantages of flexible point selection and high shooting quality in substation inspection and shooting. It can also give full play to the advantages of various intelligent equipment to achieve full coverage and high-efficiency inspection of inspection tasks.

[0095] An automatic generation system for joint inspection points of dual intelligent equipment in substations is characterized by comprising a model building module, an optimal inspection point acquisition module, and a verification module.

[0096] The model building module is used to build a general spatial point shooting potential model and a spatial relationship model of dual intelligent equipment based on the substation structural data.

[0097] The optimal inspection point acquisition module is used to design a point selection method with joint shooting quality and inspection efficiency as optimization objectives based on the model and combining shooting quality constraints and spatial constraints, so as to obtain the optimal joint inspection point.

[0098] The verification module is used to test and verify the optimal joint inspection point.

[0099] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or independent of it, or they can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0100] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a method for automatically generating joint inspection points for substation robots and drones. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0101] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0102] Based on the substation structural data, a general spatial point shooting potential model and spatial relationship model for dual intelligent equipment are established.

[0103] Based on the model and considering both shooting quality and spatial constraints, a point selection method is designed with the optimization objectives of combined shooting quality and inspection efficiency to obtain the optimal combined inspection point.

[0104] The optimal joint inspection points were tested and verified.

[0105] Example 2

[0106] Reference Figure 1-3 As an embodiment of the present invention, a method and system for automatically generating joint inspection points of substation robots and drones are provided. In order to verify the beneficial effects of the present invention, comparative experiments are conducted for scientific demonstration.

[0107] Table 1. Number of inspection targets and average inspection time per target for different inspection point sets.

[0108]

[0109] Table 1 shows the number of targets inspected by the intelligent equipment at different inspection points and the average time τ for each target. It can be seen that joint inspection can achieve 100% coverage of inspection tasks, while drones cannot complete about 8% of inspection tasks, and robots cannot complete about 27% of inspection tasks. This is due to the inherent limitations of drones and robots. For example, robots cannot inspect the top surfaces of equipment or some high-positioned equipment, while drones cannot navigate through dense equipment clusters due to safety concerns. The joint inspection mode can effectively leverage the advantages of intelligent equipment, meet inspection needs in various situations, and achieve full coverage of inspection tasks.

[0110] In terms of inspection efficiency, the joint inspection mode significantly reduces the inspection time compared to independent inspections by drones and robots. It saves 439.6 seconds compared to drones and 541.1 seconds compared to robots. On average, the inspection time per target is 2.90 seconds faster than drones and 7.92 seconds faster than robots. This is attributed to the slower movement speed of robots and their need to backtrack due to road limitations. Drones, on the other hand, spend more time adjusting their own position and gimbal posture when inspection points are scattered, in order to avoid collisions. The joint inspection mode, with its multi-agent cooperation and optimized objective function (including the time spent on inspection points), results in shorter total inspection time and shorter average time per target, demonstrating its high efficiency.

[0111] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0112] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0113] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0114] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0115] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0116] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0117] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for automatically generating joint inspection points of substation robots and drones, characterized in that: include, Based on the substation structural data, a general spatial point shooting potential model and spatial relationship model for dual intelligent equipment are established. Based on the model and considering both shooting quality and spatial constraints, a point selection method is designed with the optimization objectives of combined shooting quality and inspection efficiency to obtain the optimal combined inspection point. The optimal joint inspection points were tested and verified. The shooting quality constraints include, Among them, X b This represents the point in space with the highest potential for image capture when the device surface is the only potential source. Let X be the point b The spatial relationship between intelligent equipment and equipment surfaces at a given point. For point Y a The spatial relationship between the intelligent equipment and the equipment surface at a given point, wherein the spatial relationship is either visible or invisible. When the device surface is used as the sole potential source for shooting, point X... b The shooting posture, When the device surface is used as the sole potential source point Y, a The shooting momentum, i is the number of substation equipment, j is the number of spatial grids, and t is the selection threshold; when If the condition is not met, it means that the device cannot find a shooting point in the space that satisfies the spatial relationship constraint, that is, the line of sight is not blocked, and therefore no inspection point is generated for that surface. The spatial constraints include, Road constraints include, Among them, S road Let S represent the set of road points. robot S represents the robot's inspection point. UAV R indicates the inspection point of the drone. F This provides a viable space for intelligent equipment. This is the minimum flight altitude for drones; The spatial constraints also include line-of-sight constraints and safety constraints. The imaging equipment on the intelligent equipment has a maximum line-of-sight limit, and the intelligent equipment will not photograph equipment beyond the maximum line-of-sight at the inspection point. When intelligent equipment is subjected to strong magnetic and electric fields in a substation, to ensure the safety of the power equipment and the intelligent equipment itself, constraints are set on the equipment surfaces to be inspected at the inspection points. These constraints can be expressed as follows: Among them, O ij The center of the device face. and These are the maximum line-of-sight distances for robots and drones, respectively. and The safe distances between power equipment and robots and drones are S, respectively. robot S represents the robot's inspection point. UAV Indicates the inspection points for drones; The optimization objectives include, The objective function expression is as follows: G3 = max(t robot ,t UAV )·m-(t robot m robot +t UAV m UAV ) G = u1w1G1 + u2w2G3 Among them, G1 represents the first optimization of the target inspection image quality, and G3 represents the second optimization of the target inspection time positiveization result. robot and t UAV m represents the time spent by the robot and the drone capturing images of a single device surface, respectively. robot and m UAV N represents the number of equipment surfaces inspected by robots and drones, respectively. robot and N UAV denoted by , respectively, the number of inspection points performed by robots and drones, m is the surface of the equipment to be inspected covered by all inspection points, u1 and u2 are normalization factors, w1 and w2 are weighting factors added with different emphases on different optimization objectives, and G is the final objective function.

2. The method for automatically generating joint inspection points of substation robots and drones as described in claim 1, characterized in that: It also includes, Select the candidate point set and the inspection point set, and determine whether the candidate point set is empty; If the candidate set is empty, the inspection ends directly; If the candidate set is not empty, then determine the point with the largest objective function value in the candidate set, and use the simulated annealing algorithm to determine the current temperature and the termination temperature of each point; If the current temperature is lower than the termination temperature, the point with the maximum objective function will be selected into the inspection point set. If the current temperature is higher than the termination temperature, the simulated annealing algorithm is used, and an inspection point is selected based on the acceptance probability. Remove the selected point from the candidate point set, update the state of the remaining candidate points, and repeatedly check whether the candidate set is empty.

3. The method for automatically generating joint inspection points of substation robots and drones as described in claim 2, characterized in that: The test verification includes, in, For drone inspection solutions, For drone inspection solutions, S Equ This shows the inspection status of each piece of equipment.

4. A substation dual intelligent equipment joint inspection point automatic generation system applying the method described in claim 1, characterized in that: It includes a model building module, an optimal inspection point acquisition module, and a verification module. The model building module is used to build a general spatial point shooting potential model and a spatial relationship model of dual intelligent equipment based on the substation structural data. The optimal inspection point acquisition module is used to design a point selection method with joint shooting quality and inspection efficiency as optimization objectives based on the model and combining shooting quality constraints and spatial constraints, so as to obtain the optimal joint inspection point. The verification module is used to test and verify the optimal joint inspection point.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

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