Substation UAV inspection multi-machine collaborative method and system

Abstract

The present invention provides a multi-machine collaborative method and system for UAV substation inspection. The implementation scheme is as follows: in the case of abnormal phase transformation of the main transformer, based on the temperature rise information, discharge interference information and vibration mutation information of each core component, the temperature rise propagation path, discharge interference propagation path and vibration propagation path of the main transformer in the substation are determined respectively; based on the temperature rise propagation path, discharge interference propagation path and vibration propagation path, the flight trajectory of the temperature detection UAV, the flight trajectory of the discharge detection UAV and the flight trajectory of the vibration detection UAV are optimized to obtain the target flight trajectory of the temperature detection UAV, the target flight trajectory of the discharge detection UAV and the target flight trajectory of the vibration detection UAV, and the temperature detection UAV, the discharge detection UAV and the vibration detection UAV are controlled respectively to perform flight inspection. The adoption of the present invention can improve the accuracy and efficiency of inspection.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and in particular to a multi-machine collaborative method and system for substation unmanned aerial vehicle inspection. Background Art

[0002] Transformers are important electrical equipment in power systems. The normal and stable operation of transformers is crucial to the safe production of power systems. Transformer failure can lead to severe economic losses and adverse consequences.

[0003] Currently, inspectors are widely using drones for substation inspections. If a phase-changing fault occurs in a substation's main transformer during commutation, this fault can also cause failures in other transformers. In this case, the drone's flight path needs to be adjusted to accurately detect substation faults. Furthermore, substations typically use multiple drones for inspections to improve efficiency. Therefore, coordinating the flight paths of these multiple drones is a technical challenge that needs to be addressed in this field. Summary of the Invention

[0004] The present invention provides a multi-machine collaborative method and system for substation drone inspection, which can solve at least one of the above technical problems.

[0005] According to one aspect of the present invention, a multi-machine collaborative method for substation inspection using drones is provided, comprising:

[0006] In the event of an abnormality during the phase change process of the main transformer of the substation, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation are determined based on the temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process;

[0007] Based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, the flight trajectory of the temperature detection drone, the flight trajectory of the discharge detection drone, and the flight trajectory of the vibration detection drone are optimized to obtain the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone;

[0008] Based on the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone, the temperature detection drone, the discharge detection drone, and the vibration detection drone are respectively controlled to perform flight inspections.

[0009] According to another aspect of the present invention, a multi-machine collaborative device for substation inspection using a drone is provided, comprising:

[0010] a propagation path determination module, which, when an abnormality occurs during the phase change process of the main transformer of the substation, determines the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation based on the temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process;

[0011] a flight trajectory determination module, configured to optimize the flight trajectory of the temperature detection UAV, the flight trajectory of the discharge detection UAV, and the flight trajectory of the vibration detection UAV based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, to obtain a target flight trajectory of the temperature detection UAV, a target flight trajectory of the discharge detection UAV, and a target flight trajectory of the vibration detection UAV;

[0012] The flight inspection control module is used to control the temperature detection drone, the discharge detection drone and the vibration detection drone to perform flight inspections based on the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone and the target flight trajectory of the vibration detection drone.

[0013] According to another aspect of the present invention, a multi-machine collaborative system for drone substation inspection is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in any embodiment of the present invention.

[0014] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute the method according to any embodiment of the present invention.

[0015] Using the technical solution of the present invention, when an abnormality occurs during the phase change process of the main transformer of the substation, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation are determined based on the temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process. In this way, the flight trajectory of the temperature detection drone, the discharge detection drone, and the vibration detection drone can be optimized based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path to obtain the target flight trajectory of the temperature detection drone, the discharge detection drone, and the vibration detection drone. Based on the target flight trajectory of the temperature detection drone, the discharge detection drone, and the vibration detection drone, the temperature detection drone, the discharge detection drone, and the vibration detection drone are controlled to perform flight inspections. Thus, by using the fault propagation paths of different types of faults to optimize the flight trajectories of the corresponding drones, not only can the synergistic effect of the coordinated work of the temperature detection drone, the discharge detection drone, and the vibration detection drone be improved, but also the accuracy and efficiency of the inspection can be improved.

[0016] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are provided for a better understanding of the present invention and do not constitute a limitation of the present invention.

[0018] Figure 1 This is a flow chart of a multi-machine collaborative method for UAV substation inspection according to an embodiment of the present invention;

[0019] Figure 2 This is a structural block diagram of a multi-machine collaborative device for substation inspection using a drone according to an embodiment of the present invention;

[0020] Figure 3 is a block diagram of an electronic device for implementing the method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, and various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0022] Figure 1This is a flow chart of a multi-machine collaborative method for UAV substation inspection according to an embodiment of the present invention.

[0023] like Figure 1 As shown, the multi-machine collaborative method for UAV substation inspection may include:

[0024] S110, when an abnormality occurs during a phase change process of a main transformer of the substation, determining the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path of the main transformer in the substation based on temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process;

[0025] S120: Optimizing the flight trajectory of the temperature detection UAV, the flight trajectory of the discharge detection UAV, and the flight trajectory of the vibration detection UAV based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path to obtain target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV;

[0026] S130 , based on the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone, respectively control the temperature detection drone, the discharge detection drone, and the vibration detection drone to perform flight inspections.

[0027] As you can understand, substations in power systems include multiple main transformers with heavy loads. If a transformer fails during phase conversion, it can potentially cause other transformers to fail as well. Therefore, rapid fault inspections are necessary to prevent the fault from spreading further.

[0028] Exemplarily, the core components of the transformer include an iron core, a primary winding, a secondary winding, a bushing, a voltage tap changer, and a heat sink.

[0029] Exemplarily, temperature rise information may include the temperature rise rate, temperature rise range, or a temperature rise curve over time. For example, temperature data of various components of the main transformer is collected using a thermistor probe. The temperature sampling period is typically 3 seconds. The raw temperature data is de-noised and smoothed to obtain filtered temperature data, from which temperature rise information is determined. For another example, the core and winding temperatures exceeding 75 degrees Celsius are recorded, the tap changer temperature exceeding 85 degrees Celsius is recorded, and the radiator temperature exceeding 65 degrees Celsius is recorded. Raw temperature data is significantly affected by environmental interference. A sliding average filter is used to process the temperature data, with a filter window length of 5 sampling points, to effectively eliminate random noise interference in the temperature data.

[0030] Exemplarily, the discharge interference information may include the electric field and magnetic field generated by the discharge interference. For example, electromagnetic sensors are used to detect the interference electric field and interference magnetic field to obtain corresponding electric field data and magnetic field data, and then noise removal and other operations are performed to obtain the final discharge interference information.

[0031] For example, the sudden vibration change information may include information such as the peak value and occurrence time of the sudden vibration change. For example, a vibration sensor is used to detect vibration information of a component to extract the sudden vibration change information.

[0032] For example, by utilizing the voltage transmission relationship between the abnormal main transformer and other transformers that change voltage, combined with the temperature rise information, discharge interference information, and vibration mutation information of each core component, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path can be derived. For example, as the voltage is transmitted, its temperature rise information affects the temperature rise information of other transformers, and the path transmission speed and transmission effect also vary with the original temperature rise information. Therefore, it is necessary to combine temperature rise information to deduce the fault propagation path.

[0033] For example, in the above step S120, the target flight trajectory of the temperature detection drone can be determined based on the temperature rise propagation path, the target flight trajectory of the discharge detection drone can be determined based on the discharge interference propagation path, and the target flight trajectory of the vibration detection drone can be determined based on the vibration propagation path.

[0034] For example, in the above step S120 , collision detection and simulation inspection may be performed on the trajectories determined in the previous example to optimize these trajectories and obtain the final target flight trajectory.

[0035] According to the above embodiment, if an abnormality occurs during the phase change process of the main transformer in the substation, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation are determined based on the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of each core component of the main transformer during the phase change process. In this way, the flight trajectories of the temperature detection drone, the discharge detection drone, and the vibration detection drone can be optimized based on the temperature rise propagation path, discharge interference propagation path, and vibration propagation path, obtaining the target flight trajectories of the temperature detection drone, the discharge detection drone, and the vibration detection drone. Based on the target flight trajectories of the temperature detection drone, the discharge detection drone, and the vibration detection drone, the temperature detection drone, the discharge detection drone, and the vibration detection drone are controlled to perform flight inspections. Thus, by optimizing the flight trajectories of the corresponding drones using the fault propagation paths of different types of faults, not only can the collaborative effect of the temperature detection drone, the discharge detection drone, and the vibration detection drone be improved, but also the accuracy and efficiency of the inspections can be improved.

[0036] In one embodiment, the flight trajectory of a temperature detection drone, the flight trajectory of a discharge detection drone, and the flight trajectory of a vibration detection drone are optimized based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path to obtain target flight trajectories of the temperature detection drone, the discharge detection drone, and the vibration detection drone, including: determining a first flight trajectory of the temperature detection drone based on temperature rise information and the temperature rise anomaly propagation path; determining a second flight trajectory of the discharge detection drone based on discharge interference information and the discharge interference propagation path; determining a third flight trajectory of the vibration detection drone based on vibration mutation information and the vibration propagation path; adjusting the first flight trajectory, the second flight trajectory, and the third flight path based on collision detection results of the first flight trajectory, the second flight trajectory, and the third flight path to obtain adjusted first flight trajectory, adjusted second flight trajectory, and adjusted third flight path; performing secondary adjustment on the adjusted first flight trajectory and the adjusted third flight path based on the discharge interference information of the main transformer and the discharge interference propagation path to obtain target flight trajectories of the temperature detection drone and the vibration detection drone; and determining the target flight trajectory of the vibration detection drone based on the adjusted second flight trajectory.

[0037] For example, based on the temperature rise rate and peak value of the main transformer's temperature rise information, as the temperature rise anomaly propagates along the path, the temperature rise time, temperature rise speed, and peak value of each transformer in the temperature rise anomaly propagation path can be estimated. This allows the temperature monitoring drone to plan its first flight trajectory based on the location, temperature rise time, temperature rise speed, and peak value of each transformer in the temperature rise anomaly propagation path.

[0038] For example, for the interference electric field strength and interference magnetic field strength in the discharge interference information of the main transformer, as the discharge interference propagation path propagates, the occurrence time and interference electric field strength, the occurrence time and interference magnetic field strength of each transformer in the discharge interference propagation path can be estimated. In this way, based on the location information, the occurrence time and interference electric field strength, the occurrence time and interference magnetic field strength of each transformer in the discharge interference propagation path, the second flight trajectory of the temperature detection drone is planned.

[0039] For example, based on the vibration mutation time and peak value in the main transformer's vibration mutation information, the vibration mutation time and peak value of each transformer along the vibration propagation path can be estimated as the vibration propagation path propagates. In this way, based on the location information, vibration mutation time and peak value of each transformer along the vibration propagation path, a third flight trajectory for the vibration detection drone can be planned.

[0040] Exemplarily, based on the collision point and collision time in the above collision results, the trajectories of the first flight trajectory, the second flight trajectory and the third flight path are adjusted, for example, the speed or position of the trajectory point corresponding to the collision point in any trajectory where the collision occurs is adjusted to avoid a collision.

[0041] Exemplarily, based on the discharge interference information of the main transformer and the discharge interference propagation path, the adjusted first flight trajectory and the adjusted third flight path are adjusted for the second time. For example, the discharge interference time in the discharge interference information generated by each transformer in the discharge interference propagation path after propagation, and the predicted flight time of each trajectory point in the trajectory, if the position and time coincide, the flight speed, flight time or position of the trajectory point can be adjusted to avoid interference of the transformer on the UAV and improve the detection accuracy of the UAV.

[0042] According to the above implementation, the propagation paths of each fault type are first used to determine the initial flight trajectory of each UAV for fault type detection. Then, collision detection is used to adjust the trajectory, and the trajectory is adjusted again to avoid discharge interference. This results in a final target flight trajectory for each UAV for each fault type detected. This improves multi-machine coordination efficiency and detection accuracy.

[0043] In one embodiment, based on the temperature rise propagation path, the discharge interference propagation path and the vibration propagation path, the flight trajectory of the temperature detection drone, the flight trajectory of the discharge detection drone and the flight trajectory of the vibration detection drone are optimized to obtain the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone and the target flight trajectory of the vibration detection drone, including: based on the temperature rise propagation path, the discharge interference propagation path and the vibration propagation path, respectively determining the first flight trajectory function, the second flight trajectory function and the third flight trajectory function; based on the first flight trajectory function, the second flight trajectory function and the third flight trajectory function, determining the first iterative population, wherein the first iterative population includes multiple particles, each particle corresponding to a candidate flight trajectory of the temperature detection drone, the candidate flight trajectory of the discharge detection drone and the candidate flight trajectory of the vibration detection drone; for each particle in the first iterative population, The corresponding candidate flight trajectories of the temperature detection UAV, the candidate flight trajectories of the discharge detection UAV and the candidate flight trajectories of the vibration detection UAV are subjected to collision detection, and based on the results of the collision detection, particles with collision risks are deleted in the first iterative population to obtain a second iterative population; a simulated inspection is performed on the candidate flight trajectories of the temperature detection UAV, the candidate flight trajectories of the discharge detection UAV and the candidate flight trajectories of the vibration detection UAV corresponding to each particle in the second iterative population to obtain the simulated inspection accuracy corresponding to each particle in the second iterative population; based on the simulated inspection accuracy corresponding to each particle in the second iterative population, the individual optimal fitness is updated; when the individual optimal fitness meets the preset fitness condition, the target flight trajectory of the temperature detection UAV, the target flight trajectory of the discharge detection UAV and the target flight trajectory of the vibration detection UAV are determined based on the particles corresponding to the individual optimal fitness.

[0044] Exemplarily, based on the position information of each transformer in the temperature rise propagation path, the temperature rise change time period and the temperature change range within the temperature rise change time period, a first flight trajectory function is determined, wherein the first flight trajectory function is used to describe the arrival time and arrival speed of each trajectory point, and the position information of each trajectory point corresponds to the position information of each transformer.

[0045] Exemplarily, a second flight trajectory function is determined based on the position information of each transformer in the discharge interference propagation path, the discharge interference time period, and the occurrence time corresponding to the maximum interference intensity within the discharge interference time period. The second flight trajectory function is used to describe the arrival time and arrival speed of each trajectory point, and the position information of each trajectory point corresponds to the position information of each transformer. The arrival time of each trajectory point is associated with the discharge interference time period and the occurrence time corresponding to the maximum interference intensity within the discharge interference time period. The allowable range of the arrival time is the discharge interference time period, and the arrival time is close to the occurrence time.

[0046] Exemplarily, a third flight trajectory function is determined based on the position information of each transformer in the vibration propagation path, the vibration occurrence time period, and the occurrence time corresponding to the maximum vibration intensity within the vibration occurrence time period. The third flight trajectory function is used to describe the arrival time and arrival speed of each trajectory point, and the position information of each trajectory point corresponds to the position information of each transformer. The arrival time of each trajectory is associated with the vibration occurrence time period and the occurrence time corresponding to the maximum vibration intensity within the vibration occurrence time period. The allowable range of the arrival time is the vibration occurrence time period, and the arrival time is close to the occurrence time.

[0047] Exemplarily, determining a first iterative population based on the first, second, and third flight trajectory functions includes determining candidate flight trajectories for a temperature detection drone, a discharge detection drone, and a vibration detection drone based on the first, second, and third flight trajectory functions, respectively, and using these three trajectories as parameters corresponding to a particle. A single trajectory function can determine multiple different candidate flight trajectories.

[0048] Exemplarily, updating the individual optimal fitness based on the simulated inspection accuracy corresponding to each particle in the second iteration population includes: when the maximum value of the simulated inspection accuracy corresponding to each particle in the second iteration population is greater than or equal to the individual optimal fitness, updating the individual optimal fitness with the maximum value; and when the maximum value of the simulated inspection accuracy corresponding to each particle in the second iteration population is less than the individual optimal fitness, the individual optimal fitness remains unchanged. It is understood that the value of the individual optimal fitness can be randomly initialized during the first iteration.

[0049] Exemplarily, based on the particles corresponding to the individual optimal fitness, the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone and the target flight trajectory of the vibration detection drone are determined, including: the candidate flight trajectory of the temperature detection drone, the candidate flight trajectory of the discharge detection drone and the candidate flight trajectory of the vibration detection drone corresponding to the particles corresponding to the individual optimal fitness are respectively determined as the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone and the target flight trajectory of the vibration detection drone.

[0050] Exemplarily, the fitness condition may be that the individual optimal fitness is greater than a preset fitness threshold.

[0051] According to the above implementation, a combined optimization method of particle swarm algorithm, collision detection and simulation inspection is used to optimize the flight trajectory of temperature detection drones, discharge detection drones and vibration detection drones, which can improve the multi-machine coordination efficiency and detection accuracy.

[0052] In one embodiment, it also includes: when the individual optimal fitness does not meet the preset fitness condition, the first iterative population is updated, and the following steps are continued based on the updated first iterative population: collision detection is performed on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the first iterative population, and based on the results of the collision detection, particles with collision risks are deleted from the first iterative population to obtain a second iterative population; simulation inspection is performed on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population to obtain the simulation inspection accuracy corresponding to each particle in the second iterative population; based on the simulation inspection accuracy corresponding to each particle in the second iterative population, the individual optimal fitness is updated.

[0053] Exemplarily, the first iterative population is updated based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function.

[0054] According to the above implementation, a combined optimization method of particle swarm algorithm, collision detection and simulation inspection is used to optimize the flight trajectory of temperature detection drones, discharge detection drones and vibration detection drones, which can improve the multi-machine coordination efficiency and detection accuracy.

[0055] In one embodiment, a simulated inspection is performed on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population to obtain the simulated inspection accuracy corresponding to each particle in the second iterative population, including: based on the temperature rise information and the temperature rise propagation path of the main transformer, a simulated inspection is performed on the candidate flight trajectories of the temperature detection drone corresponding to each particle in the second iterative population to obtain the temperature detection accuracy corresponding to each particle in the second iterative population; based on the discharge interference information and the discharge interference propagation path of the main transformer, a simulated inspection is performed on the candidate flight trajectories of the discharge detection drone corresponding to each particle in the second iterative population to obtain the discharge detection accuracy corresponding to each particle in the second iterative population; based on the vibration mutation information and the vibration propagation path of the main transformer, a simulated inspection is performed on the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population to obtain the vibration detection accuracy corresponding to each particle in the second iterative population; and based on the temperature detection accuracy, discharge detection accuracy, and vibration detection accuracy corresponding to each particle in the second iterative population, the simulated inspection accuracy corresponding to each particle in the second iterative population is determined.

[0056] Exemplarily, based on the temperature rise information and temperature rise propagation path of the main transformer, the simulation models corresponding to each transformer in the temperature rise propagation path are controlled to perform temperature rise. At the same time, the simulation model corresponding to the temperature detection drone is controlled to perform simulated inspections according to the candidate flight trajectory of the temperature detection drone corresponding to the particle. Based on the detection results of the temperature rise changes of each transformer in the path by the simulation model corresponding to the temperature detection drone, the temperature detection accuracy of the particle is determined.

[0057] Exemplarily, based on the discharge interference information and the discharge interference propagation path of the main transformer, the simulation models corresponding to each transformer in the discharge interference propagation path are controlled to perform corresponding discharge interference. At the same time, the simulation model corresponding to the discharge detection drone is controlled to perform simulated inspections according to the candidate flight trajectory of the discharge detection drone corresponding to the particle. Based on the detection results of the discharge interference intensity of each transformer in the path by the simulation model corresponding to the discharge detection drone, the discharge detection accuracy corresponding to the particle is determined.

[0058] Exemplarily, based on the vibration mutation information and vibration propagation path of the main transformer, the simulation models corresponding to each transformer in the vibration propagation path are controlled to vibrate accordingly. At the same time, the simulation model corresponding to the vibration detection drone is controlled to perform simulated inspections according to the candidate flight trajectory of the vibration detection drone corresponding to the particle. Based on the detection results of the vibration mutation conditions of each transformer in the path by the simulation model corresponding to the vibration detection drone, the vibration detection accuracy of the particle is determined.

[0059] For example, if any one of the temperature detection accuracy, the discharge detection accuracy, and the vibration detection accuracy is lower than its corresponding accuracy threshold, the accuracy is used as the simulation inspection accuracy.

[0060] For example, if the temperature detection accuracy, discharge detection accuracy, and vibration detection accuracy are all higher than their corresponding accuracy thresholds, the temperature detection accuracy, discharge detection accuracy, and vibration detection accuracy are weighted and summed to obtain the simulation inspection accuracy corresponding to each particle.

[0061] According to the above implementation, the simulation inspection accuracy corresponding to each particle in the population can be accurately calculated.

[0062] Figure 2 This is a structural block diagram of a multi-machine collaborative device for substation inspection using a drone according to an embodiment of the present invention.

[0063] like Figure 2 As shown in the figure, the multi-machine collaborative device for substation inspection by drones includes:

[0064] The propagation path determination module 210 determines, when an abnormality occurs during the phase change process of the main transformer of the substation, the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path of the main transformer in the substation based on the temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process;

[0065] a flight trajectory determination module 220 for optimizing the flight trajectory of the temperature detection UAV, the flight trajectory of the discharge detection UAV, and the flight trajectory of the vibration detection UAV based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, to obtain target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV;

[0066] The flight inspection control module 230 is used to control the temperature detection drone, the discharge detection drone and the vibration detection drone to perform flight inspections based on the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone and the target flight trajectory of the vibration detection drone.

[0067] In one embodiment, the flight trajectory determination module 220 includes:

[0068] a first trajectory determining unit, configured to determine a first flight trajectory of the temperature detection drone based on the temperature rise information and the temperature rise anomaly propagation path;

[0069] a second trajectory determining unit, configured to determine a second flight trajectory of the discharge detection UAV based on the discharge interference information and the discharge interference propagation path;

[0070] a third trajectory determining unit, configured to determine a third flight trajectory of the vibration detection UAV based on the discharge interference information and the vibration propagation path;

[0071] a first trajectory adjustment unit, configured to perform trajectory adjustments on the first flight trajectory, the second flight trajectory, and the third flight path based on collision detection results of the first flight trajectory, the second flight trajectory, and the third flight path, to obtain adjusted first flight trajectory, adjusted second flight trajectory, and adjusted third flight path;

[0072] a second trajectory adjustment unit, configured to perform secondary adjustments on the adjusted first flight trajectory and the adjusted third flight path based on the discharge interference information of the main transformer and the discharge interference propagation path, to obtain a target flight trajectory of the temperature detection UAV and a target flight trajectory of the vibration detection UAV;

[0073] The third trajectory adjustment unit is configured to determine a target flight trajectory of the vibration detection UAV based on the adjusted second flight trajectory.

[0074] In one embodiment, the flight trajectory determination module includes:

[0075] a trajectory function determining unit, configured to respectively determine a first flight trajectory function, a second flight trajectory function, and a third flight trajectory function based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path;

[0076] A first population determination unit is configured to determine a first iterative population based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function, wherein the first iterative population includes a plurality of particles, and each particle corresponds to a candidate flight trajectory of the temperature detection UAV, a candidate flight trajectory of the discharge detection UAV, and a candidate flight trajectory of the vibration detection UAV;

[0077] a second population determination unit, configured to perform collision detection on candidate flight trajectories of the temperature detection drone, the discharge detection drone, and the vibration detection drone corresponding to each particle in the first iterative population, and based on the collision detection results, delete particles with collision risks from the first iterative population to obtain a second iterative population;

[0078] a simulation inspection unit, configured to perform simulation inspections on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population, to obtain a simulation inspection accuracy corresponding to each particle in the second iterative population;

[0079] a fitness updating unit, configured to update the individual optimal fitness based on the simulation inspection accuracy corresponding to each particle in the second iterative population;

[0080] A target trajectory determination unit is configured to determine the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone based on the particles corresponding to the individual optimal fitness when the individual optimal fitness meets the preset fitness condition.

[0081] In one embodiment, it further includes:

[0082] The population update cycle module is used to update the first iterative population when the individual optimal fitness does not meet the preset fitness condition, and based on the updated first iterative population, adopt the second population determination unit, the simulation inspection unit and the fitness update unit to continue to execute the corresponding steps.

[0083] In one embodiment, the simulation inspection unit is specifically used to:

[0084] Based on the temperature rise information of the main transformer and the temperature rise propagation path, simulate and inspect the candidate flight trajectories of the temperature detection drone corresponding to each particle in the second iterative population to obtain the temperature detection accuracy corresponding to each particle in the second iterative population;

[0085] Based on the discharge interference information of the main transformer and the discharge interference propagation path, a simulated inspection is performed on the candidate flight trajectory of the discharge detection drone corresponding to each particle in the second iterative population to obtain the discharge detection accuracy corresponding to each particle in the second iterative population;

[0086] Based on the vibration mutation information of the main transformer and the vibration propagation path, a simulated inspection is performed on the candidate flight trajectory of the vibration detection drone corresponding to each particle in the second iterative population to obtain the vibration detection accuracy corresponding to each particle in the second iterative population;

[0087] The simulation inspection accuracy corresponding to each particle in the second iterative population is determined based on the temperature detection accuracy, the discharge detection accuracy, and the vibration detection accuracy corresponding to each particle in the second iterative population.

[0088] For the description of specific functions and examples of each module and submodule of the system in the embodiment of the present invention, please refer to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0089] In the technical solution of the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0090] According to an embodiment of the present invention, the present invention further provides a system and a readable storage medium.

[0091] Figure 3A schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0092] like Figure 3 As shown, device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. RAM 803 may also store various programs and data required for the operation of device 800. Computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to bus 804.

[0093] Various components in device 800 are connected to I / O interface 805, including an input unit 806, such as a keyboard, mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0094] The computing unit 801 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above, such as the multi-machine collaborative method for drone substation inspection. For example, in some embodiments, the multi-machine collaborative method for drone substation inspection can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the multi-machine collaborative method for drone substation inspection described above can be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to execute the multi-machine collaborative method for drone substation inspection by any other appropriate means (e.g., by means of firmware).

[0095] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0097] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0098] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0099] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0100] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0101] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved. This is not limited herein.

[0102] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A multi-machine collaborative method for UAV substation inspection, characterized by: include: In the event of an abnormality during the phase change process of the main transformer of the substation, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation are determined based on the temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process; Based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, the flight trajectory of the temperature detection drone, the flight trajectory of the discharge detection drone, and the flight trajectory of the vibration detection drone are optimized to obtain the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone, including: determining a first flight trajectory of the temperature detection drone based on the temperature rise information and the temperature rise anomaly propagation path; Based on the discharge interference information and the discharge interference propagation path, the second flight trajectory of the discharge detection drone is determined; based on the vibration mutation information and the vibration propagation path, the third flight trajectory of the vibration detection drone is determined; based on the collision detection results of the first flight trajectory, the second flight trajectory and the third flight trajectory, the first flight trajectory, the second flight trajectory and the third flight trajectory are adjusted to obtain the adjusted first flight trajectory, the adjusted second flight trajectory and the adjusted third flight trajectory; based on the discharge interference information of the main transformer and the discharge interference propagation path, the adjusted first flight trajectory and the adjusted third flight trajectory are adjusted for the second time to obtain the target flight trajectory of the temperature detection drone and the target flight trajectory of the vibration detection drone; based on the adjusted second flight trajectory, the target flight trajectory of the discharge detection drone is determined; Based on the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone, the temperature detection drone, the discharge detection drone, and the vibration detection drone are respectively controlled to perform flight inspections.

2. The method according to claim 1, characterized in that The method optimizes the flight trajectory of the temperature detection drone, the flight trajectory of the discharge detection drone, and the flight trajectory of the vibration detection drone based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path to obtain the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone, including: determining a first flight trajectory function, a second flight trajectory function, and a third flight trajectory function based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, respectively; Determine a first iterative population based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function, wherein the first iterative population includes a plurality of particles, and each particle corresponds to a candidate flight trajectory of the temperature detection drone, a candidate flight trajectory of the discharge detection drone, and a candidate flight trajectory of the vibration detection drone; performing collision detection on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the first iterative population, and based on the results of the collision detection, deleting particles with collision risks from the first iterative population to obtain a second iterative population; Performing simulated inspections on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population to obtain the simulated inspection accuracy corresponding to each particle in the second iterative population; Based on the simulation inspection accuracy corresponding to each particle in the second iterative population, updating the individual optimal fitness; When the individual optimal fitness meets the preset fitness condition, the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone are determined based on the particles corresponding to the individual optimal fitness.

3. The method according to claim 2, characterized in that Also includes: When the individual optimal fitness does not meet the preset fitness condition, the first iterative population is updated, and the following steps are continued based on the updated first iterative population: performing collision detection on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the first iterative population, and based on the results of the collision detection, deleting particles with collision risks from the first iterative population to obtain a second iterative population; Performing simulated inspections on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population to obtain the simulated inspection accuracy corresponding to each particle in the second iterative population; Based on the simulation inspection accuracy corresponding to each particle in the second iterative population, the individual optimal fitness is updated.

4. The method according to claim 2 or 3, characterized in that The simulated inspection of the candidate flight trajectory of the temperature detection drone, the candidate flight trajectory of the discharge detection drone, and the candidate flight trajectory of the vibration detection drone corresponding to each particle in the second iterative population is performed to obtain the simulated inspection accuracy corresponding to each particle in the second iterative population, including: Based on the temperature rise information of the main transformer and the temperature rise propagation path, simulate and inspect the candidate flight trajectories of the temperature detection drone corresponding to each particle in the second iterative population to obtain the temperature detection accuracy corresponding to each particle in the second iterative population; Based on the discharge interference information of the main transformer and the discharge interference propagation path, a simulated inspection is performed on the candidate flight trajectory of the discharge detection drone corresponding to each particle in the second iterative population to obtain the discharge detection accuracy corresponding to each particle in the second iterative population; Based on the vibration mutation information of the main transformer and the vibration propagation path, a simulated inspection is performed on the candidate flight trajectory of the vibration detection drone corresponding to each particle in the second iterative population to obtain the vibration detection accuracy corresponding to each particle in the second iterative population; The simulation inspection accuracy corresponding to each particle in the second iterative population is determined based on the temperature detection accuracy, the discharge detection accuracy, and the vibration detection accuracy corresponding to each particle in the second iterative population.

5. A multi-machine collaborative device for substation inspection by drone, characterized in that: include: a propagation path determination module, which, when an abnormality occurs during the phase change process of the main transformer of the substation, determines the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation based on the temperature rise information, discharge interference information, and vibration mutation information of each core component of the main transformer during the phase change process; a flight trajectory determination module, configured to optimize the flight trajectory of the temperature detection UAV, the flight trajectory of the discharge detection UAV, and the flight trajectory of the vibration detection UAV based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, to obtain a target flight trajectory of the temperature detection UAV, a target flight trajectory of the discharge detection UAV, and a target flight trajectory of the vibration detection UAV; a flight inspection control module, configured to control the temperature detection drone, the discharge detection drone, and the vibration detection drone to perform flight inspections based on the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone; Wherein, the flight trajectory determination module includes: a first trajectory determining unit, configured to determine a first flight trajectory of the temperature detection drone based on the temperature rise information and the temperature rise anomaly propagation path; a second trajectory determining unit, configured to determine a second flight trajectory of the discharge detection UAV based on the discharge interference information and the discharge interference propagation path; a third trajectory determining unit, configured to determine a third flight trajectory of the vibration detection UAV based on the vibration mutation information and the vibration propagation path; a first trajectory adjustment unit, configured to perform trajectory adjustments on the first flight trajectory, the second flight trajectory, and the third flight trajectory based on collision detection results of the first flight trajectory, the second flight trajectory, and the third flight trajectory, to obtain adjusted first flight trajectory, adjusted second flight trajectory, and adjusted third flight trajectory; a second trajectory adjustment unit, configured to perform secondary adjustments on the adjusted first flight trajectory and the adjusted third flight trajectory based on the discharge interference information of the main transformer and the discharge interference propagation path, to obtain a target flight trajectory of the temperature detection UAV and a target flight trajectory of the vibration detection UAV; The third trajectory adjustment unit is configured to determine a target flight trajectory of the discharge detection UAV based on the adjusted second flight trajectory.

6. The device according to claim 5, characterized in that The flight trajectory determination module includes: a trajectory function determining unit, configured to respectively determine a first flight trajectory function, a second flight trajectory function, and a third flight trajectory function based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path; A first population determination unit is configured to determine a first iterative population based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function, wherein the first iterative population includes a plurality of particles, and each particle corresponds to a candidate flight trajectory of the temperature detection UAV, a candidate flight trajectory of the discharge detection UAV, and a candidate flight trajectory of the vibration detection UAV; a second population determination unit, configured to perform collision detection on candidate flight trajectories of the temperature detection drone, the discharge detection drone, and the vibration detection drone corresponding to each particle in the first iterative population, and based on the collision detection results, delete particles with collision risks from the first iterative population to obtain a second iterative population; a simulation inspection unit, configured to perform simulation inspections on the candidate flight trajectories of the temperature detection drone, the candidate flight trajectories of the discharge detection drone, and the candidate flight trajectories of the vibration detection drone corresponding to each particle in the second iterative population, to obtain a simulation inspection accuracy corresponding to each particle in the second iterative population; a fitness updating unit, configured to update the individual optimal fitness based on the simulation inspection accuracy corresponding to each particle in the second iterative population; A target trajectory determination unit is configured to determine the target flight trajectory of the temperature detection drone, the target flight trajectory of the discharge detection drone, and the target flight trajectory of the vibration detection drone based on the particles corresponding to the individual optimal fitness when the individual optimal fitness meets the preset fitness condition.

7. A multi-machine collaborative system for UAV substation inspection, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 4.

8. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-4.

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