Method, device, processor and readable storage medium for assigning inspection tasks

Abstract

The application discloses a kind of distribution methods, device, processor and readable storage medium of inspection task, wherein the method includes: obtaining the inspection task information of multiple inspection equipment;Based on the inspection task information of each initial inspection task, establish communication network, wherein, communication network is used to share the inspection task information of each inspection equipment;Based on inspection task information and communication network, determine the inspection performance index of each inspection equipment, wherein, inspection performance index is used to indicate the importance degree and the performance of processing task in initial inspection task of each inspection equipment;Based on inspection performance index, determine the target inspection task of each inspection equipment, wherein, target inspection task is used to indicate the inspection content and / or inspection path of inspection equipment;Target inspection task is distributed to corresponding inspection equipment.The application solves the technical problem of low efficiency of inspection task distribution.

Description

Technical Field

[0001] This invention relates to the field of power grid inspection technology, and more specifically, to a method, apparatus, processor, and readable storage medium for allocating inspection tasks. Background Technology

[0002] Currently, with the growth of global electricity demand and the increasing complexity of power systems, the reliability and security of power grids have received increasing attention. Routine inspections of key facilities such as power transmission lines and substations have become one of the fundamental tasks for ensuring the safe and stable operation of the power system.

[0003] In related technologies, traditional power grid inspection methods mainly rely on manual labor, typically employing ground inspectors or helicopters for aerial inspections. These methods are not only costly but also suffer from numerous problems such as low inspection efficiency, high personnel safety risks, and blind spots. Therefore, there is a technical problem of inefficient allocation of inspection tasks.

[0004] There is currently no effective solution to the technical problem of low efficiency in the allocation of inspection tasks mentioned above. Summary of the Invention

[0005] This invention provides a method, apparatus, processor, and readable storage medium for allocating inspection tasks, in order to at least solve the technical problem of low efficiency in allocating inspection tasks.

[0006] According to one aspect of the present invention, a method for allocating inspection tasks is provided. The method may include: acquiring inspection task information of multiple inspection devices, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection devices; establishing a communication network based on the inspection task information of each initial inspection task, wherein the communication network is used to share the inspection task information of each inspection device; determining inspection performance indicators for each inspection device based on the inspection task information and the communication network, wherein the inspection performance indicators are used to indicate the importance and task performance of each inspection device in the initial inspection task; determining the target inspection task for each inspection device based on the inspection performance indicators, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device; and allocating the target inspection task to the corresponding inspection device.

[0007] Optionally, based on the inspection task information and the communication network, the inspection performance indicators of each inspection device are determined, including: based on the inspection task information, determining the role performance indicators of each inspection device, wherein the role performance indicators are used to indicate the importance of the inspection device in the inspection task; based on the communication network, determining the execution performance indicators of each inspection device, wherein the execution performance indicators are used to indicate the performance of the inspection device in handling the inspection task; and based on the role performance indicators and the execution performance indicators, determining the inspection performance indicators of each inspection device.

[0008] Optionally, based on the inspection task information, the role performance indicators of each inspection device are determined, including: establishing role nodes for each inspection device based on the inspection task information, wherein the role nodes are used to represent the inspection devices; and determining the role performance indicators of each inspection device based on the role nodes.

[0009] Optionally, based on role nodes, the role performance indicators of each inspection device are determined, including: establishing a role graph according to the connection relationship between role nodes, wherein the role graph is used to represent the importance of each inspection device in the initial inspection task; determining the interaction relationship between inspection devices based on the role graph; and determining the role performance indicators of inspection devices based on the interaction relationship.

[0010] Optionally, based on role performance indicators and execution performance indicators, the inspection performance indicators of each inspection device are determined, including: fusing the performance parameters of role performance indicators and execution performance indicators to obtain the inspection performance indicators of each inspection device.

[0011] Optionally, the method for allocating inspection tasks may further include: determining the priority of inspection equipment corresponding to inspection performance indicators, wherein the priority is used to indicate the order in which inspection equipment performs target inspection tasks; and determining the target inspection tasks of the inspection equipment according to the priority.

[0012] According to another aspect of the present invention, an apparatus for allocating inspection tasks is also provided. The apparatus may include: an acquisition unit, configured to acquire inspection task information of multiple inspection devices, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection devices; an establishment unit, configured to establish a communication network based on the inspection task information of each initial inspection task, wherein the communication network is used to share the inspection task information of each inspection device; a first determination unit, configured to determine the inspection performance index of each inspection device based on the inspection task information and the communication network, wherein the inspection performance index is used to indicate the importance and task performance of each inspection device in the initial inspection task; a second determination unit, configured to determine the target inspection task of each inspection device based on the inspection performance index, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device; and an allocation unit, configured to allocate the target inspection task to the corresponding inspection device.

[0013] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is run by a processor, it controls the device where the storage medium is located to execute the inspection task allocation method of the present invention.

[0014] According to another aspect of the present invention, a processor is also provided. The processor is used to run a program, wherein the program executes the inspection task allocation method of the embodiments of the present invention during runtime.

[0015] According to another aspect of the present invention, a computer program product is also provided. The program product includes computer instructions that, when executed by a processor, implement the inspection task allocation method in the embodiments of the present invention.

[0016] In this embodiment of the invention, inspection task information of multiple inspection devices is acquired, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection devices; based on the inspection task information of each initial inspection task, a communication network is established, wherein the communication network is used to share the inspection task information of each inspection device; based on the inspection task information and the communication network, the inspection performance index of each inspection device is determined, wherein the inspection performance index is used to indicate the importance of each inspection device in the initial inspection task and the performance of the task processing; based on the inspection performance index, the target inspection task of each inspection device is determined, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device; and the target inspection task is assigned to the corresponding inspection device. In other words, this invention obtains the inspection task information of the inspection equipment, establishes a communication network, and thus determines the inspection performance indicators of each inspection equipment. Based on the inspection performance indicators, the target inspection task of the inspection equipment is determined. Since this invention can determine the target inspection task based on the specific inspection performance indicators of the inspection equipment, that is, it flexibly allocates inspection tasks according to the inspection capabilities of the inspection equipment, thus solving the technical problem of low efficiency in the allocation of inspection tasks and achieving the technical effect of improving the efficiency of the allocation of inspection tasks. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of a method for allocating inspection tasks according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of a power grid inspection system architecture based on UAV swarm collaborative scheduling according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of a graph diffusion network according to an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram illustrating the role of a drone in an inspection mission according to an embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of a process for analyzing role importance according to an embodiment of the present invention;

[0023] Figure 6 This is a schematic diagram of an inspection task allocation device according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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 scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, functional component, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, functional components, or devices.

[0026] According to an embodiment of the present invention, an embodiment of a method for allocating inspection tasks is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] Figure 1 This is a flowchart of a method for allocating inspection tasks according to an embodiment of the present invention, such as... Figure 1 As shown, the method may include the following steps:

[0028] Step S101: Obtain inspection task information for multiple inspection devices.

[0029] In the technical solution provided by step S101 of the present invention, the inspection task information is used to indicate the initial inspection task performed by the inspection equipment.

[0030] In this embodiment, inspection task information of multiple inspection devices is obtained. The inspection devices may be drones; this is merely an example and does not limit the specific content of the inspection devices.

[0031] For example, based on the needs of power grid inspection, the drone's endurance, and geographical location, initial inspection tasks are assigned to each drone. These tasks can be initially allocated based on factors such as the layout of power grid lines and the importance of equipment.

[0032] Step S102: Establish a communication network based on the inspection task information of each initial inspection task.

[0033] In the technical solution provided by step S102 of the present invention, the communication network is used to share the inspection task information of each inspection device.

[0034] In this embodiment, after obtaining the inspection task information of multiple inspection devices in step S101, a communication network is established based on the inspection task information of each initial inspection task. This communication network can also be called a Graph Diffusion Network (GDN).

[0035] For example, the communication and mission execution between drones can be mapped to the relationships between network nodes, thereby constructing a graph diffusion network.

[0036] Step S103: Based on the inspection task information and communication network, determine the inspection performance indicators of each inspection device.

[0037] In the technical solution provided in step S103 of the present invention, the inspection performance index is used to indicate the importance of each inspection device in the initial inspection task and the performance of the task processing. The inspection performance index can also be referred to as the comprehensive task score.

[0038] In this embodiment, after establishing the communication network in step S102, the inspection performance indicators of each inspection device are determined based on the inspection task information and the communication network.

[0039] Optionally, based on the inspection task information, the role performance index of each inspection device is determined. The role performance index is used to indicate the importance of the inspection device in the inspection task. The role performance index can also be called the role importance score.

[0040] For example, based on the inspection task information, role nodes are established for each inspection device, where role nodes represent inspection devices; a role graph is established according to the connection relationships between role nodes, where the role graph represents the importance of each inspection device in the initial inspection task; the interaction relationships between inspection devices are determined based on the role graph; and the role performance indicators of inspection devices are determined based on the interaction relationships.

[0041] For another example, based on the complexity and importance of the drone's mission and the characteristics of the surrounding power grid facilities, each drone is divided into different roles. Each role corresponds to a different level of mission difficulty and importance. A role graph is created for the drone swarm, and based on the topology of the role graph, the relative importance of the drones in power grid inspection is analyzed, generating a role importance score.

[0042] Optionally, based on the communication network, the execution performance indicators of each inspection device are determined, wherein the execution performance indicators are used to indicate the ability of the inspection device to handle inspection tasks; thereby, the performance parameters of the role performance indicators and the performance parameters of the execution performance indicators are fused to obtain the inspection performance indicators of each inspection device.

[0043] For example, the diffusion capability score is fused with the role importance score. The fusion process is accomplished using a multilayer perceptron (MLP) model, ultimately generating a comprehensive mission score for each drone.

[0044] Step S104: Based on the inspection performance indicators, determine the target inspection tasks for each inspection device.

[0045] In the technical solution provided by step S104 of the present invention, the target inspection task is used to indicate the inspection content and / or inspection path of the inspection equipment.

[0046] In this embodiment, after determining the inspection performance indicators of each inspection device in step S103, the target inspection task of each inspection device is determined based on the inspection performance indicators.

[0047] Optionally, by determining target inspection tasks through inspection performance indicators, the system can intelligently schedule inspection equipment clusters, optimize inspection paths, and ensure efficient and accurate power grid inspections. By assessing the diffusion capabilities and role importance of each inspection device, reasonable inspection tasks are assigned to the devices. Furthermore, through a scoring and fusion mechanism, the system can dynamically adjust inspection tasks to maximize inspection efficiency.

[0048] Step S105: Assign the target inspection task to the corresponding inspection equipment.

[0049] In the technical solution provided by step S105 of the present invention, after determining the target inspection task of each inspection device in step S104, the target inspection task is assigned to the corresponding inspection device.

[0050] In this embodiment, the target inspection task is assigned to the corresponding inspection equipment, so that the inspection equipment completes the inspection task according to the inspection path in the target inspection task.

[0051] It should be noted that the above embodiments can be executed using a power grid inspection system based on UAV swarm collaborative scheduling.

[0052] In steps S101 to S105 of the present invention, inspection task information of multiple inspection devices is obtained, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection devices; a communication network is established based on the inspection task information of each initial inspection task, wherein the communication network is used to share the inspection task information of each inspection device; based on the inspection task information and the communication network, the inspection performance index of each inspection device is determined, wherein the inspection performance index is used to indicate the importance of each inspection device in the initial inspection task and the performance of the task processing; based on the inspection performance index, the target inspection task of each inspection device is determined, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device; and the target inspection task is assigned to the corresponding inspection device. In other words, this invention obtains the inspection task information of the inspection equipment, establishes a communication network, and thus determines the inspection performance indicators of each inspection equipment. Based on the inspection performance indicators, the target inspection task of the inspection equipment is determined. Since this invention can determine the target inspection task based on the specific inspection performance indicators of the inspection equipment, that is, it flexibly allocates inspection tasks according to the inspection capabilities of the inspection equipment, thus solving the technical problem of low efficiency in the allocation of inspection tasks and achieving the technical effect of improving the efficiency of the allocation of inspection tasks.

[0053] The method described in this embodiment will be further described below.

[0054] As an optional implementation method, the inspection performance indicators of each inspection device are determined based on the inspection task information and the communication network, including: determining the role performance indicators of each inspection device based on the inspection task information, wherein the role performance indicators are used to indicate the importance of the inspection device in the inspection task; determining the execution performance indicators of each inspection device based on the communication network, wherein the execution performance indicators are used to indicate the performance of the inspection device in handling the inspection task; and determining the inspection performance indicators of each inspection device based on the role performance indicators and the execution performance indicators.

[0055] In this embodiment, the role performance indicators of each inspection device are determined based on the inspection task information; the execution performance indicators of each inspection device are determined based on the communication network; and the inspection performance indicators of each inspection device are determined based on the role performance indicators and the execution performance indicators.

[0056] Alternatively, in contrast to traditional single-machine inspections or static task assignments, this invention can flexibly adjust the inspection tasks of drones through a dual scoring mechanism of diffusion capability and role importance, and prioritize key areas to ensure comprehensive coverage and high efficiency of power grid inspections.

[0057] As an optional implementation method, the role performance indicators of each inspection device are determined based on the inspection task information, including: establishing role nodes for each inspection device based on the inspection task information, wherein the role nodes are used to represent the inspection devices; and determining the role performance indicators of each inspection device based on the role nodes.

[0058] In this embodiment, role nodes for each inspection device are established based on the inspection task information; and role performance indicators for each inspection device are determined based on the role nodes.

[0059] For example, the Role Extraction using Interest eXtraction (ROIX) algorithm can be used to automatically extract the role of a drone in an inspection mission. The ROIX algorithm analyzes the functional role of a drone based on the inspection area it is in and the importance of nearby equipment. This algorithm categorizes drones into different roles by analyzing information such as the number of power grid devices covered, mission complexity, and location. For instance, some drones may be responsible for inspecting critical transmission lines, while others may be responsible for supplementary inspections or monitoring of secondary areas.

[0060] As an optional implementation method, the role performance indicators of each inspection device are determined based on role nodes, including: establishing a role graph according to the connection relationship between role nodes, wherein the role graph is used to represent the importance of each inspection device in the initial inspection task; determining the interaction relationship between inspection devices based on the role graph; and determining the role performance indicators of inspection devices based on the interaction relationship.

[0061] In this embodiment, the connection relationships between multiple role nodes are obtained, and the multiple role nodes are established into a role graph through the connection relationships. Based on the role graph, the interaction relationships between inspection devices are determined. This can be done by using the ROIX algorithm to extract role information, which is used to represent the role information. The role information can be processed to obtain the result, and the result can be used to construct a role graph. This is only an example and does not limit the specific method of constructing the role graph.

[0062] For example, based on the role information extracted by the ROIX algorithm, the system constructs a role graph to describe the task relationships and importance among drones. Based on the interaction relationships between role nodes, i.e., the connection relationships, a role graph is constructed; that is, the role information can be used to represent the topology, where each node represents a vertex and each connection represents an edge. The role graph can demonstrate the functional roles and importance of different drones in the power grid inspection network.

[0063] Optionally, the role performance indicators of the inspection equipment can be determined based on the interaction relationships. For example, a topological sort can be performed on a directed graph, that is, a linear ordering of the nodes can be determined such that if there is a path from node A to node B, then node A appears before node B in the ordering, and so on, to determine the role performance indicators of the inspection equipment. This is only an example and does not limit the specific method for determining the role performance indicators of the inspection equipment.

[0064] As an optional implementation method, the inspection performance index of each inspection device is determined based on the role performance index and the execution performance index, including: fusing the performance parameters of the role performance index and the performance parameters of the execution performance index to obtain the inspection performance index of each inspection device.

[0065] In this embodiment, the performance parameters of the role performance index and the performance parameters of the execution performance index are fused to obtain the inspection performance index of each inspection device. The inspection performance index can also be referred to as a comprehensive score.

[0066] Optionally, a comprehensive score for the drone can be generated by combining execution performance indicators and role performance indicators, which can be used for dynamic adjustment of tasks and path optimization to ensure that inspection tasks are completed efficiently.

[0067] As an optional embodiment, the method for allocating inspection tasks further includes: determining the priority of inspection equipment corresponding to inspection performance indicators, wherein the priority is used to indicate the order in which inspection equipment performs target inspection tasks; and determining the target inspection tasks of the inspection equipment according to the priority.

[0068] In this embodiment, the priority of the inspection equipment corresponding to the inspection performance index is determined; according to the priority, the target inspection task of the inspection equipment is determined.

[0069] Optionally, the target inspection tasks for the inspection equipment can be determined according to priority, so as to achieve dynamic adjustment of tasks and path optimization, and ensure that the inspection tasks are completed efficiently.

[0070] It should be noted that the above embodiments can be executed using a power grid inspection system based on UAV swarm collaborative scheduling.

[0071] In this embodiment, inspection task information of multiple inspection devices is acquired, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection devices; based on the inspection task information of each initial inspection task, a communication network is established, wherein the communication network is used to share the inspection task information of each inspection device; based on the inspection task information and the communication network, the inspection performance index of each inspection device is determined, wherein the inspection performance index is used to indicate the importance of each inspection device in the initial inspection task and the performance of the task processing; based on the inspection performance index, the target inspection task of each inspection device is determined, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device; and the target inspection task is assigned to the corresponding inspection device. In other words, this invention obtains the inspection task information of the inspection equipment, establishes a communication network, and thus determines the inspection performance indicators of each inspection equipment. Based on the inspection performance indicators, the target inspection task of the inspection equipment is determined. Since this invention can determine the target inspection task based on the specific inspection performance indicators of the inspection equipment, that is, it flexibly allocates inspection tasks according to the inspection capabilities of the inspection equipment, thus solving the technical problem of low efficiency in the allocation of inspection tasks and achieving the technical effect of improving the efficiency of the allocation of inspection tasks.

[0072] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0073] Currently, with the growth of global electricity demand and the increasing complexity of power systems, the reliability and security of power grids have received increasing attention. Routine inspections of key facilities such as power transmission lines and substations have become one of the fundamental tasks for ensuring the safe and stable operation of the power system.

[0074] In related technologies, traditional power grid inspection methods mainly rely on manual labor, typically employing ground inspectors or helicopters for aerial inspections. These methods are not only costly but also suffer from numerous problems such as low inspection efficiency, high personnel safety risks, and blind spots. Therefore, there is a technical problem of inefficient allocation of inspection tasks. Currently, no effective solution has been proposed to address this issue of inefficient allocation of inspection tasks.

[0075] However, this invention proposes a power grid inspection method based on UAV swarm collaborative scheduling. This method assigns initial inspection tasks to each UAV based on its endurance, task complexity, and current task progress. A communication network is established between UAVs, and through information sharing, the diffusion capability (i.e., the ability to process and transmit tasks throughout the mission) of each UAV is calculated. Based on communication and collaboration among UAVs, task allocation is dynamically adjusted to ensure effective distribution of inspection tasks throughout the power grid area, minimizing redundant inspections. This solves the technical problem of low efficiency in task allocation and achieves the technical effect of improving the efficiency of task allocation.

[0076] The embodiments of the present invention will be further described below.

[0077] Figure 2 This is a schematic diagram of a power grid inspection system architecture based on UAV swarm collaborative scheduling according to an embodiment of the present invention, as shown below. Figure 2 As shown in the figure, circles 1 to 10 represent nodes in the network. That is, each drone's technical architecture does not involve complex hardware module design. The core lies in intelligent task allocation, path optimization, and inspection data processing through the Diffusion Competence and Role Significance Model (DCRSM) algorithm.

[0078] In this embodiment, the power grid inspection system architecture based on UAV swarm collaborative scheduling includes encoding node diffusion competence, encoding node role significance, encoding node diffusion competence, encoding node role significance, and scoring and fusion.

[0079] Optionally, this invention focuses on improving the efficiency and accuracy of power grid inspection through the scheduling of drone swarms and optimization using the DCRSM (Diffusion Competence and Role Significance Model) algorithm. This technical architecture does not involve complex hardware module design; its core lies in intelligent task allocation, path optimization, and inspection data processing through the DCRSM algorithm. The system implementation can be divided into three key parts: the ability to propagate encoded nodes, the importance of encoded node roles, and scoring and fusion.

[0080] Optionally, in power grid inspection tasks, the node diffusion capability is used to evaluate each drone's ability to transmit information and execute tasks during the inspection process. In practical applications, diffusion capability can be calculated and optimized through the following steps:

[0081] Optionally, task initialization: assign initial inspection tasks to each UAV based on the UAV's endurance, task complexity, and current task progress.

[0082] Optionally, diffusion network construction: establish a communication network between drones and other drones, and calculate the diffusion capability of each drone (i.e., its ability to process and deliver tasks throughout the mission) through mutual information sharing.

[0083] Optionally, diffusion optimization involves dynamically adjusting task allocation based on communication and collaboration among UAVs to ensure effective distribution of inspection tasks throughout the power grid area, minimizing redundant inspections and improving inspection efficiency. This process is implemented using a graph diffusion network model, combining the diffusion capabilities of each UAV in specific tasks to optimize the inspection coverage.

[0084] Optionally, node role importance can be encoded: Node role importance is identified by analyzing the functional role of each drone in the inspection mission, thus identifying critical nodes (i.e., more important task points). Based on the inspection needs of the power grid facilities, some drones may be assigned to more critical power grid nodes for priority inspection. The role importance of a node reflects the degree of mission criticality of that drone in the overall power grid inspection.

[0085] Optionally, role classification: Based on the complexity and importance of the drone's mission and the characteristics of the surrounding power grid facilities, the system classifies each drone into different roles. Each role corresponds to a different level of mission difficulty and importance.

[0086] Optionally, role graph construction: The system builds a role graph for the drone swarm, and based on the topology of the role graph, analyzes the relative importance of drones in power grid inspection to ensure that inspection tasks of key nodes are prioritized.

[0087] Optionally, role-based task allocation: Based on the importance of node roles, the system assigns suitable inspection tasks to drones with different roles, ensuring that critical areas and important power grid equipment are inspected first. This process is implemented using the ROIX algorithm and Graph Convolutional Network (GCN) to evaluate the criticality of each drone in the inspection task. The role of each drone in power grid inspection is determined based on the importance of its task and the criticality of the power grid equipment within its coverage area.

[0088] Optionally, scoring and fusion: Scoring and fusion is the core part of the entire DCRSM algorithm. It derives each drone's final mission score by comprehensively evaluating its dissemination capabilities and role importance throughout the mission. The scoring model considers not only the drone's information transmission capabilities in the mission but also comprehensively evaluates its role at key mission points.

[0089] Optionally, diffusion capability score: Calculate the diffusion capability score of each UAV based on the diffusion network to evaluate its ability to transmit information and perform tasks.

[0090] Optionally, role importance scoring: Based on role graph analysis, the task importance of each drone in power grid inspection is analyzed, and corresponding role scores are generated.

[0091] Optionally, score fusion: By fusing diffusion capability and role importance scores, a comprehensive mission score is generated for each drone, ensuring that more critical drones undertake more complex and important inspection tasks. This scoring and fusion part is implemented through a multilayer perceptron (MLP), and the final score is used to optimize task allocation and inspection paths, ensuring that the drone swarm collaborates efficiently to complete power grid inspections.

[0092] Optionally, the core of the system is the design and implementation of the DCRSM algorithm. By encoding and optimizing the diffusion capability and role importance of drones, and combining scoring and fusion mechanisms, the intelligent scheduling and optimization of power grid inspection tasks are finally realized, ensuring that the drone swarm can complete power grid inspections collaboratively and efficiently.

[0093] Optionally, the core technology of this invention, the DCRSM algorithm, is used to optimize task allocation, path planning, and data processing of UAV swarms in power grid inspection. This algorithm achieves intelligent UAV scheduling by evaluating the task execution capability of each UAV and its role importance in the inspection network. To enable those skilled in the art to easily implement this invention, the three core components of the technical solution are described in detail below: node diffusion capability encoding, node role importance encoding, and scoring and fusion.

[0094] Optionally, Figure 3This is a schematic diagram of a graph diffusion network according to an embodiment of the present invention, such as... Figure 3 As shown, node diffusion capability is encoded as follows: In power grid inspection tasks, each drone is equivalent to a node in the inspection network. Node diffusion capability refers to the drone's ability to transmit information and perform tasks throughout the entire mission. By evaluating diffusion capability, the system can optimize the mission range and path of each drone, ensuring efficient mission execution.

[0095] Optionally, task initialization: The system first assigns preliminary inspection tasks to each drone based on the needs of power grid inspection, the drone's endurance, and geographical location. These tasks can be initially assigned based on factors such as the layout of power grid lines and the importance of equipment.

[0096] Optionally, the diffusion network is constructed as follows: A graph diffusion network is built to map the communication and mission execution between UAVs to the relationships between network nodes. The GDN model calculates the diffusion capability of each UAV by simulating the information flow transmission of UAVs in the power grid. The diffusion capability is calculated by measuring the mission coordination of the UAV with other UAVs, combined with its mission complexity, flight path rationality, and mission completion progress, ultimately generating a diffusion score for the UAV.

[0097] Optionally, drones can share task information through real-time communication, and the system continuously optimizes task allocation and flight paths based on the drones' dispersal capabilities. By adaptively adjusting inspection paths, the system can avoid task overlap, reduce inspection blind spots, and ensure comprehensive coverage of the entire power grid inspection task.

[0098] Optionally, node role importance is implemented using the ROIX algorithm and graph convolutional networks, primarily to evaluate the importance of each drone in the overall power grid inspection mission. Different power grid equipment and inspection tasks have different importance in the network; some drones may undertake more critical inspection tasks, therefore role importance needs to be evaluated on a targeted basis.

[0099] Optionally, Figure 4 This is a schematic diagram illustrating the role of a drone in an inspection mission according to an embodiment of the present invention, such as... Figure 4 As shown, role extraction (ROIX algorithm): The system uses the ROIX algorithm to automatically extract the role of the UAV in the inspection task. The ROIX algorithm is based on the inspection area where the UAV is located and the importance of nearby equipment (…). Figure 4 The algorithm analyzes the functional roles of drones at various points (within the network). It categorizes drones into different roles by analyzing information such as the number of power grid devices covered, task complexity, and location. For example, some drones may be responsible for inspecting critical transmission lines, while others may be responsible for supplementary inspections or monitoring of secondary areas.

[0100] Optionally, role graph construction: Based on the role information extracted by the ROIX algorithm, the system constructs a role graph to describe the task relationships and importance among drones. The role graph can show the functional roles and importance of different drones in the power grid inspection network. The system further analyzes the position and role of drones in inspection tasks through the role graph to ensure that key areas and equipment are prioritized for inspection.

[0101] Optionally, Figure 5 This is a schematic diagram of a process for analyzing role importance according to an embodiment of the present invention, such as... Figure 5 As shown, role importance assessment (GCN implementation): After the role graph is constructed, the system further analyzes the role importance of nodes using a Graph Convolutional Network (GCN). Important roles are analyzed through the input layer, hidden layer, and output layer. Figure 5 In this model, X1, X2, X3, and X4 indicate the individual input nodes, while Z1, Z2, Z3, and Z4 indicate the nodes after processing each input node in the hidden layer. A Graph Convolutional Network (GCN) model is used to learn node representations. GCN learns node representations by performing convolution operations on a graph structure, aggregating the feature information of a node with the feature information of its neighbors. Figure 5 A scatter plot represents each node and the distances between nodes.

[0102] Optionally, the GCN model calculates the importance of each drone in power grid inspection by learning the local and global network structure within the drone swarm. GCN can generate role importance scores based on the relationships between drones and the complexity of their inspection tasks, ensuring that important tasks are prioritized.

[0103] Optionally, scoring and fusion are core components of the DCRSM algorithm, responsible for comprehensively evaluating the diffusion capabilities and role importance of each UAV to generate a final mission score. This score is used to guide the dynamic adjustment and optimization of UAV missions.

[0104] Optionally, diffusion capability scoring: The system first generates a diffusion capability score for each UAV based on the analysis results of the diffusion network. The diffusion capability score reflects the efficiency of information transmission and task allocation during mission execution. For example, UAVs with high diffusion capability scores can cooperate efficiently and cover a larger inspection area.

[0105] Optionally, a role importance score: The system will also generate a role importance score for each drone based on the role importance analyzed by GCN. This score reflects whether the drone plays a critical role in the inspection mission and assesses its priority in performing tasks within the inspection network.

[0106] Optionally, score fusion: To ultimately determine the mission priority of each drone, the system fuses the diffusion capability score with the role importance score. The fusion process is completed through a multilayer perceptron (MLP) model, ultimately generating a comprehensive mission score for each drone. Drones with higher scores will be prioritized to perform critical missions, while drones with lower scores will perform secondary missions or serve as supplementary inspections.

[0107] Optionally, through the detailed implementation of the above three steps, this invention can intelligently schedule drone swarms, optimize inspection paths, and ensure efficient and accurate power grid inspections. The DCRSM algorithm assigns reasonable inspection tasks to drones by evaluating the diffusion capability and role importance of each drone, and ensures that the system can dynamically adjust inspection tasks through a scoring and fusion mechanism to maximize inspection efficiency.

[0108] Optionally, compared with existing UAV power grid inspection technologies, this invention achieves intelligent scheduling and efficient task allocation of UAV swarms through the DCRSM algorithm (Diffusion Capability and Role Importance Model), overcoming problems such as low inspection efficiency, task duplication, and insufficient path optimization in existing technologies. Most existing technologies rely on single UAVs or simple swarm collaborative scheduling, which cannot effectively handle complex power grid inspection tasks. This invention, however, dynamically evaluates the diffusion capability of UAVs and combines it with role importance analysis to achieve adaptive task allocation and optimization, thereby significantly improving inspection efficiency and task completion accuracy.

[0109] Optionally, compared to traditional single-machine inspections or static task allocation, this invention can flexibly adjust the inspection tasks of UAVs through a dual scoring mechanism of diffusion capability and role importance, prioritizing key areas to ensure comprehensive coverage and efficiency of power grid inspections. This intelligent scheduling and task optimization method enables this invention to complete large-scale power grid inspection tasks more efficiently, while reducing the risk of task overlap and omissions, ensuring the quality and safety of inspections.

[0110] In this embodiment, preliminary inspection tasks are assigned to each UAV based on its endurance, task complexity, and current task progress. A communication network is established between UAVs, and through information sharing, the diffusion capability of each UAV (i.e., its ability to process and transmit tasks throughout the mission) is calculated. Based on communication and collaboration between UAVs, the task allocation is dynamically adjusted to ensure effective distribution of inspection tasks throughout the power grid area, minimize duplicate inspections, solve the technical problem of low efficiency in the allocation of inspection tasks, and achieve the technical effect of improving the efficiency of inspection task allocation.

[0111] According to embodiments of the present invention, an inspection task allocation device is also provided. It should be noted that this inspection task allocation device can be used to execute the inspection task allocation method in the method embodiments.

[0112] Figure 6 This is a schematic diagram of an inspection task allocation device according to an embodiment of the present invention. Figure 6 As shown, the inspection task allocation device 600 may include: an acquisition unit 601, an establishment unit 602, a first determination unit 603, a second determination unit 604, and an allocation unit 605.

[0113] The acquisition unit 601 is used to acquire inspection task information of multiple inspection devices, wherein the inspection task information is used to indicate the initial inspection task to be performed by the inspection device.

[0114] Establishment unit 602 is used to establish a communication network based on the inspection task information of each initial inspection task, wherein the communication network is used to share the inspection task information of each inspection device.

[0115] The first determining unit 603 is used to determine the inspection performance indicators of each inspection device based on the inspection task information and the communication network. The inspection performance indicators are used to indicate the importance of each inspection device in the initial inspection task and the performance of the task.

[0116] The second determining unit 604 is used to determine the target inspection task of each inspection device based on the inspection performance index, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device.

[0117] The allocation unit 605 is used to allocate the target inspection task to the corresponding inspection equipment.

[0118] Optionally, the first determining unit 603 may include: a first determining module, configured to determine the role performance index of each inspection device based on the inspection task information, wherein the role performance index is used to indicate the importance of the inspection device in the inspection task; a second determining module, configured to determine the execution performance index of each inspection device based on the communication network, wherein the execution performance index is used to indicate the performance of the inspection device in handling the inspection task; and a third determining module, configured to determine the inspection performance index of each inspection device based on the role performance index and the execution performance index.

[0119] Optionally, the first determining module may include: an establishing submodule, used to establish role nodes for each inspection device based on inspection task information, wherein the role nodes are used to represent inspection devices; and a determining submodule, used to determine the role performance indicators of each inspection device based on the role nodes.

[0120] Optionally, the determination submodule can also be used to establish a role graph according to the connection relationship between role nodes, wherein the role graph is used to represent the importance of each inspection device in the initial inspection task; based on the role graph, determine the interaction relationship between inspection devices; and based on the interaction relationship, determine the role performance index of the inspection devices.

[0121] Optionally, the second determining module may include: a fusion submodule, used to fuse the performance parameters of the role performance index and the performance parameters of the execution performance index to obtain the inspection performance index of each inspection device.

[0122] Optionally, the inspection task allocation device 600 may further include: a third determining unit, used to determine the priority of the inspection equipment corresponding to the inspection performance index, wherein the priority is used to indicate the order in which the inspection equipment performs the target inspection task; and a fourth determining unit, used to determine the target inspection task of the inspection equipment according to the priority.

[0123] In this embodiment, inspection task information of multiple inspection devices is acquired, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection devices; based on the inspection task information of each initial inspection task, a communication network is established, wherein the communication network is used to share the inspection task information of each inspection device; based on the inspection task information and the communication network, the inspection performance index of each inspection device is determined, wherein the inspection performance index is used to indicate the importance of each inspection device in the initial inspection task and the performance of the task processing; based on the inspection performance index, the target inspection task of each inspection device is determined, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device; and the target inspection task is assigned to the corresponding inspection device. In other words, this invention obtains the inspection task information of the inspection equipment, establishes a communication network, and thus determines the inspection performance indicators of each inspection equipment. Based on the inspection performance indicators, the target inspection task of the inspection equipment is determined. Since this invention can determine the target inspection task based on the specific inspection performance indicators of the inspection equipment, that is, it flexibly allocates inspection tasks according to the inspection capabilities of the inspection equipment, thus solving the technical problem of low efficiency in the allocation of inspection tasks and achieving the technical effect of improving the efficiency of the allocation of inspection tasks.

[0124] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein the program execution method embodiment includes a method for allocating inspection tasks.

[0125] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the inspection task allocation method in the method embodiment during runtime.

[0126] According to an embodiment of the present invention, a computer program product is also provided, the computer program product including computer instructions, which, when executed by a processor, implement the inspection task allocation method in the method embodiment.

[0127] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0128] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0129] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0132] If the integrated unit is implemented as a software functional unit and sold or used as an independent functional component, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software functional component. This computer software functional component is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0133] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for allocating inspection tasks, characterized in that, include: Obtain inspection task information of multiple inspection devices, wherein the inspection task information is used to indicate the initial inspection task to be performed by the inspection device, and the inspection device is a drone; Based on the inspection task information of each initial inspection task, the communication and task execution status between the inspection devices are mapped to the relationship between network nodes to establish a communication network. The communication network is used to share the inspection task information of each inspection device. The communication network is a graph diffusion network. The communication network is also used to simulate the information flow transmission of the inspection devices in the power grid. Based on the inspection task information and the communication network, the inspection performance index of each of the inspection devices is determined, wherein the inspection performance index is used to indicate the importance of each of the inspection devices in the initial inspection task and the performance of the task processing. Based on the inspection performance indicators, the target inspection tasks of each of the inspection devices are determined, wherein the target inspection tasks are used to indicate the inspection content and / or inspection path of the inspection devices. The target inspection task is assigned to the corresponding inspection equipment; The step of determining the inspection performance indicators of each inspection device based on the inspection task information and the communication network includes: extracting the role of each inspection device in the initial inspection task using a role extraction algorithm based on the inspection task information, and establishing role nodes for each inspection device, wherein the role nodes represent the inspection devices; determining the role performance indicators of each inspection device based on the role nodes; determining the execution performance indicators of each inspection device based on the communication network, wherein the execution performance indicators indicate the performance of the inspection devices in processing the inspection task; and determining the inspection performance indicators of each inspection device based on the role performance indicators and the execution performance indicators. Based on the role nodes, the role performance indicators of each inspection device are determined, including: establishing a role graph according to the connection relationship between the role nodes, wherein the role graph is used to represent the importance of each inspection device in the initial inspection task; determining the interaction relationship between the inspection devices based on the role graph; determining the linear order of the role nodes based on the interaction relationship; and determining the role performance indicators of the inspection devices based on the linear order. Based on the role performance index and the execution performance index, the inspection performance index of each of the inspection devices is determined, including: fusing the performance parameters of the role performance index and the performance parameters of the execution performance index through a multilayer sensor to obtain the inspection performance index of each of the inspection devices.

2. The method according to claim 1, characterized in that, The method further includes: Determine the priority of the inspection equipment corresponding to the inspection performance index, wherein the priority is used to indicate the order in which the inspection equipment performs the target inspection task; The target inspection task of the inspection equipment is determined according to the priority.

3. A device for allocating inspection tasks, characterized in that, include: An acquisition unit is used to acquire inspection task information of multiple inspection devices, wherein the inspection task information is used to indicate the initial inspection task performed by the inspection device, and the inspection device is a drone; The establishment unit is used to map the communication and task execution status between the inspection devices to the relationship between network nodes based on the inspection task information of each initial inspection task, and establish a communication network. The communication network is used to share the inspection task information of each inspection device. The communication network is a graph diffusion network. The communication network is also used to simulate the information flow transmission of the inspection devices in the power grid. The first determining unit is used to determine the inspection performance index of each of the inspection devices based on the inspection task information and the communication network, wherein the inspection performance index is used to indicate the importance of each of the inspection devices in the initial inspection task and the performance of the task processing. The second determining unit is used to determine the target inspection task of each of the inspection devices based on the inspection performance indicators, wherein the target inspection task is used to indicate the inspection content and / or inspection path of the inspection device. An allocation unit is used to allocate the target inspection task to the corresponding inspection equipment; The first determining unit is further configured to, based on the inspection task information, use a role extraction algorithm to extract the role of the inspection equipment in the initial inspection task, and establish role nodes for each inspection equipment, wherein the role nodes are used to represent the inspection equipment; determine the role performance index of each inspection equipment based on the role nodes; determine the execution performance index of each inspection equipment based on the communication network, wherein the execution performance index is used to indicate the performance of the inspection equipment in processing the inspection task; and determine the inspection performance index of each inspection equipment based on the role performance index and the execution performance index. The first determining unit is further configured to establish a role graph according to the connection relationship between the role nodes, wherein the role graph is used to represent the importance of each of the inspection devices in the initial inspection task; determine the interaction relationship between the inspection devices based on the role graph; determine the linear order of the role nodes based on the interaction relationship; and determine the role performance index of the inspection devices based on the linear order. The first determining unit is further configured to fuse the performance parameters of the role performance index and the performance parameters of the execution performance index through a multilayer sensor to obtain the inspection performance index of each of the inspection devices.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program is run by a processor, it controls the device in which the storage medium is located to perform the method according to any one of claims 1 to 2.

5. A processor, characterized in that, The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 2 when it runs.

6. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed by a processor, implement the method described in any one of claims 1 to 2.

Images