Multi-unmanned-aerial-vehicle cooperation method and system for transformer substation unmanned aerial vehicle inspection

Abstract

The invention provides an unmanned aerial vehicle transformer substation inspection multi-machine cooperation method and system. According to the implementation scheme, under the condition of abnormal phase change of the main transformer, a temperature rise propagation path, a discharge interference propagation path and a vibration propagation path of the main transformer in the transformer substation are determined respectively based on temperature rise information, discharge interference information and vibration sudden change information of each core component; based on the temperature rise propagation path, the discharge interference propagation path and the vibration propagation path, the flight path of the temperature detection unmanned aerial vehicle, the flight path of the discharge detection unmanned aerial vehicle and the flight path of the vibration detection unmanned aerial vehicle are optimized; obtaining a target flight path of the temperature detection unmanned aerial vehicle, a target flight path of the discharge detection unmanned aerial vehicle and a target flight path of the vibration detection unmanned aerial vehicle, and respectively controlling the temperature detection unmanned aerial vehicle, the discharge detection unmanned aerial vehicle and the vibration detection unmanned aerial vehicle to carry out flight inspection. According to the invention, the inspection accuracy and efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and particularly to a multi-aircraft cooperation method and system for unmanned aerial vehicle (UAV) inspection of substations. Background Art

[0002] A transformer is one of the important electrical devices in a power system. The normal and stable operation of a transformer is of great significance for the safe production of the power system. If a transformer is damaged, it will cause serious economic losses and adverse consequences.

[0003] Currently, inspectors widely apply UAVs to the inspection work of substations. During the phase conversion process of the main transformer in a substation, if a phase conversion fault occurs in the main transformer, this fault condition will also cause faults in other transformers in the substation. At this time, the flight path of the UAV inspection needs to be adjusted to accurately detect the fault condition of the substation. Moreover, multiple UAVs are generally used for inspection in a substation to improve efficiency. Then, coordinating and adjusting the flight paths of these multiple UAVs is also a technical problem to be solved in this field. Summary of the Invention

[0004] The present invention provides a multi-aircraft cooperation method and system for UAV inspection of substations, which can solve at least one of the above technical problems.

[0005] According to one aspect of the present invention, there is provided a multi-aircraft cooperation method for UAV inspection of a substation, including: In the case of an abnormality occurring during the phase conversion process of the main transformer in a 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 conversion process, respectively determine 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 propagation path, the discharge interference propagation path, and the vibration propagation path, optimize the flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV to obtain the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV; Based on the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV, respectively control the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV to perform flight inspections.

[0006] According to another aspect of the present invention, there is provided a multi-aircraft cooperation device for UAV inspection of a substation, including: A propagation path determination module, in the case of an abnormality occurring during the phase conversion process of the main transformer in a substation, determines 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, the discharge interference information, and the vibration mutation information of each core component of the main transformer during the phase conversion process, respectively; A flight trajectory determination module, configured to optimize the flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, to obtain the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV; A flight inspection control module, configured to control the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV to perform flight inspections respectively based on the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV.

[0007] According to another aspect of the present invention, there is provided a multi-UAV collaborative system for substation inspection, including: 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 to enable the at least one processor to execute the method according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method according to any embodiment of the present invention.

[0009] Adopting the technical solution of the present invention, in the case of anomalies occurring during the phase conversion process of the main transformer in a substation, based on the temperature rise information, discharge interference information, and vibration mutation information of each core component during the phase conversion process of the main transformer, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation are respectively determined. In this way, based on the temperature rise propagation path, discharge interference propagation path, and vibration propagation path, the flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV can be optimized to obtain the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV, and based on the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV, the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV are controlled to perform flight inspections. Thus, using the fault propagation paths of different types of faults to optimize the flight trajectories of the corresponding UAVs can not only improve the collaborative effect of the collaborative work of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV, but also improve the inspection accuracy and efficiency.

[0010] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings are used to better understand the solution and do not constitute a limitation to the present invention. Among them: Figure 1 is a flowchart of a multi-UAV collaborative method for substation inspection of the present invention in one embodiment; Figure 2 is a structural block diagram of a multi-UAV collaborative device for substation inspection of the present invention in one embodiment; Figure 3 is a block diagram of an electronic device for implementing the method of the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] The following describes exemplary embodiments of the present invention in conjunction with the drawings. Various details of the embodiments of the present invention are included to assist in understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can 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.

[0013] Figure 1 is a flowchart of a multi-UAV collaborative method for substation inspection of the present invention in one embodiment.

[0014] As Figure 1 shown, the multi - drone collaborative method for substation inspection by drones may include: S110. When an abnormality occurs during the phase - change process 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, respectively determine the temperature - rise propagation path, discharge - interference propagation path, and vibration propagation path of the main transformer in the substation; S120. Based on the temperature - rise propagation path, discharge - interference propagation path, and vibration propagation path, optimize the flight trajectories of the temperature - detection drone, the discharge - detection drone, and the vibration - detection drone to obtain the target flight trajectories of the temperature - detection drone, the discharge - detection drone, and the vibration - detection drone; S130. Based on the target flight trajectories of the temperature - detection drone, the discharge - detection drone, and the vibration - detection drone, respectively control the temperature - detection drone, the discharge - detection drone, and the vibration - detection drone to perform flight inspections.

[0015] It can be understood that in a substation in a power system, there are multiple main transformers with large loads. When a certain transformer undergoes a phase - change, if a fault occurs in this transformer, it may cause faults in other transformers. Therefore, it is necessary to perform rapid fault inspections to avoid the expansion of the fault range.

[0016] Exemplarily, the core components of a transformer include an iron core, a primary winding, a secondary winding, bushings, a tap - changer, and a radiator, etc.

[0017] Exemplarily, the temperature - rise information may include the temperature - rise rate, the temperature - rise range, or the curve of temperature rise over time, etc. For example, temperature data of each component of the main transformer is collected through a thermistor probe. The temperature sampling period is usually 3 seconds. By denoising and smoothing the original temperature data, the filtered temperature data can be obtained, and the temperature - rise information is determined from the filtered temperature data. Also, for example, when the temperature of the iron core and winding exceeds 75 degrees, it is recorded; when the temperature of the tap - changer exceeds 85 degrees, it is recorded; when the temperature of the radiator exceeds 65 degrees, it is recorded. The original temperature data is greatly affected by environmental interference. The sliding - average filtering method is used to process the temperature data, and the length of the filtering window is selected as 5 sampling points, which can effectively eliminate the random noise interference in the temperature data.

[0018] Exemplarily, the discharge - interference information may include the electric field and magnetic field formed by the discharge interference. For example, an electromagnetic inductor is used to detect the interference electric field and interference magnetic field to obtain the corresponding electric - field data and magnetic - field data, and operations such as denoising are performed to obtain the final discharge - interference information.

[0019] Exemplarily, the vibration mutation information may include information such as the peak value and occurrence time of the vibration mutation. For example, a vibration sensor is used to detect the vibration information of the component to extract the vibration mutation information.

[0020] Exemplarily, by utilizing the voltage transmission relationship between the abnormal main transformer and other transformers with voltage transformation, and combining 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 obtained. For example, as the voltage is conducted, its temperature rise information affects the temperature rise information of other transformers, and the path conduction speed and conduction effect also vary with the change of the original temperature rise information. Therefore, it is necessary to combine the temperature rise information to deduce the fault propagation path.

[0021] Exemplarily, in the above step S120, based on the temperature rise propagation path, the target flight trajectory of the temperature detection unmanned aerial vehicle (UAV) can be determined; based on the discharge interference propagation path, the target flight trajectory of the discharge detection UAV can be determined; and based on the vibration propagation path, the target flight trajectory of the vibration detection UAV can be determined.

[0022] Exemplarily, in the above step S120, collision detection and simulation inspection can also be performed on the determined trajectories in the previous example to optimize these trajectories, and the final target flight trajectories can be obtained.

[0023] According to the above embodiments, in the case of an abnormality occurring during the phase conversion process 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 conversion process, the temperature rise propagation path, discharge interference propagation path, and vibration propagation path of the main transformer in the substation are respectively determined. In this way, the flight trajectories of the temperature detection UAV, discharge detection UAV, and vibration detection UAV can be optimized by using the temperature rise propagation path, discharge interference propagation path, and vibration propagation path, and the target flight trajectories of the temperature detection UAV, discharge detection UAV, and vibration detection UAV can be obtained. Based on the target flight trajectories of the temperature detection UAV, discharge detection UAV, and vibration detection UAV, the temperature detection UAV, discharge detection UAV, and vibration detection UAV 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 UAVs, not only can the cooperation effect of the collaborative work of the temperature detection UAV, discharge detection UAV, and vibration detection UAV be improved, but also the inspection accuracy and efficiency can be improved.

[0024] In one embodiment, based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, the flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV are optimized to obtain the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV, including: determining the first flight trajectory of the temperature detection UAV based on the temperature rise information and the temperature rise anomaly propagation path; determining the second flight trajectory of the discharge detection UAV based on the discharge interference information and the discharge interference propagation path; determining the third flight trajectory of the vibration detection UAV based on the vibration mutation information and the vibration propagation path; adjusting the first flight trajectory, the second flight trajectory, and the third flight path based on the collision detection results of the first flight trajectory, the second flight trajectory, and the third flight trajectory to obtain the adjusted first flight trajectory, the adjusted second flight trajectory, and the 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 the target flight trajectory of the temperature detection UAV and the target flight trajectory of the vibration detection UAV; and determining the target flight trajectory of the vibration detection UAV based on the adjusted second flight trajectory.

[0025] Exemplarily, for the temperature rise rate and peak value in the temperature rise information of the main transformer, as the temperature rise anomaly propagation path propagates, the temperature rise time, temperature rise speed, and peak value of each transformer in the temperature rise anomaly propagation path can be estimated. Thus, based on the position information, temperature rise time, temperature rise speed, and peak value of each transformer in the temperature rise anomaly propagation path, the first flight trajectory of the temperature detection UAV is planned.

[0026] Exemplarily, for the interference electric field intensity and interference magnetic field intensity in the discharge interference information of the main transformer, as the discharge interference propagation path propagates, the interference electric field occurrence time and interference electric field intensity, and the interference magnetic field occurrence time and interference magnetic field intensity of each transformer in the discharge interference propagation path can be estimated. Thus, based on the position information, interference electric field occurrence time and interference electric field intensity, and interference magnetic field occurrence time and interference magnetic field intensity of each transformer in the discharge interference propagation path, the second flight trajectory of the discharge detection UAV is planned.

[0027] Exemplarily, for the vibration mutation time and vibration peak value in the vibration mutation information of the main transformer, as the vibration propagation path propagates, the vibration mutation time and vibration peak value of each transformer in the vibration propagation path can be estimated. Thus, based on the position information, vibration mutation time, and vibration peak value of each transformer in the vibration propagation path, the third flight trajectory of the vibration detection UAV is planned.

[0028] Exemplarily, based on the collision point and collision time in the above collision result, the first flight trajectory, the second flight trajectory, and the third flight path are adjusted. For example, the trajectory points corresponding to the collision point in any trajectory where a collision occurs are adjusted in terms of speed or position to avoid collisions.

[0029] 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 secondarily adjusted. For example, the discharge interference time in the discharge interference information generated after the propagation of each transformer in the discharge interference propagation path, 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 this trajectory point can be adjusted, etc., to avoid the transformer from interfering with the drone and improve the detection accuracy of the drone.

[0030] According to the above embodiments, first, the initial flight trajectories of the drones for detecting each fault type are respectively determined by using the propagation paths of each fault type, then the trajectories are adjusted by using collision detection, and then the discharge interference is avoided to secondarily adjust the trajectories, so as to obtain the final target flight trajectory of the drone for detecting one fault type. In this way, the multi-aircraft cooperation efficiency and the detection accuracy can be improved.

[0031] In one embodiment, based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path, the flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV are optimized to obtain the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV, including: determining a first flight trajectory function, a second flight trajectory function, and a third flight trajectory function respectively based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path; determining a first iteration population based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function, where the first iteration population includes multiple particles, and 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; performing collision detection 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 first iteration population, and deleting the particles with collision risks in the first iteration population based on the results of the collision detection to obtain a second iteration population; performing simulation inspection 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 iteration population to obtain the simulation inspection accuracy corresponding to each particle in the second iteration population; updating the individual optimal fitness based on the simulation inspection accuracy corresponding to each particle in the second iteration population; and determining the target flight trajectories of the temperature detection UAV, the target flight trajectories of the discharge detection UAV, and the target flight trajectories of the vibration detection UAV based on the particles corresponding to the individual optimal fitness when the individual optimal fitness meets the preset fitness conditions.

[0032] 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, where 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.

[0033] Exemplarily, 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, a second flight trajectory function is determined, where 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.

[0034] Exemplarily, 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, a third flight trajectory function is determined, where 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 this arrival time is the vibration occurrence time period, and this arrival time is close to this occurrence time.

[0035] Exemplarily, based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function, a first iteration population is determined, including: based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function, 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 are respectively determined, and these three trajectories are used as the parameters corresponding to a particle. One trajectory function can determine multiple different candidate flight trajectories.

[0036] Exemplarily, based on the simulation inspection accuracy corresponding to each particle in the second iteration population, the individual optimal fitness is updated, including: when the maximum value among the simulation inspection accuracies corresponding to each particle in the second iteration population is greater than or equal to the individual optimal fitness, the individual optimal fitness is updated with this maximum value; when the maximum value among the simulation inspection accuracies corresponding to each particle in the second iteration population is less than the individual optimal fitness, the individual optimal fitness remains unchanged. It can be understood that in the first iteration, the value of the individual optimal fitness can be randomly initialized.

[0037] Exemplarily, based on the particle corresponding to the individual optimal fitness, the target flight trajectories of the temperature detection UAV, the target flight trajectories of the discharge detection UAV, and the target flight trajectories of the vibration detection UAV are determined, including: taking 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 the particle corresponding to the individual optimal fitness, and respectively determining them as the target flight trajectories of the temperature detection UAV, the target flight trajectories of the discharge detection UAV, and the target flight trajectories of the vibration detection UAV.

[0038] Exemplarily, the fitness condition can be that the individual optimal fitness is greater than a preset fitness threshold.

[0039] According to the above embodiments, by adopting a combined optimization method of the particle swarm algorithm, collision detection, and simulation inspection to optimize the flight trajectories of the temperature detection UAV, the flight trajectories of the discharge detection UAV, and the flight trajectories of the vibration detection UAV, the multi-aircraft cooperation efficiency and detection accuracy can be improved.

[0040] In one embodiment, it further includes: when the individual optimal fitness does not meet the preset fitness condition, updating the first iteration population, and based on the updated first iteration population, continuing to execute the following steps: performing collision detection on the candidate flight trajectories of the temperature detection drones, the candidate flight trajectories of the discharge detection drones, and the candidate flight trajectories of the vibration detection drones corresponding to each particle in the first iteration population, and based on the results of the collision detection, deleting the particles with collision risks in the first iteration population to obtain a second iteration population; performing simulation patrol inspections on the candidate flight trajectories of the temperature detection drones, the candidate flight trajectories of the discharge detection drones, and the candidate flight trajectories of the vibration detection drones corresponding to each particle in the second iteration population to obtain the simulation patrol inspection accuracy corresponding to each particle in the second iteration population; updating the individual optimal fitness based on the simulation patrol inspection accuracy corresponding to each particle in the second iteration population.

[0041] Exemplarily, the first iteration population is updated based on the first flight trajectory function, the second flight trajectory function, and the third flight trajectory function.

[0042] According to the above embodiment, by adopting a combined optimization method of particle swarm algorithm, collision detection, and simulation patrol inspection to optimize the flight trajectories of the temperature detection drones, the flight trajectories of the discharge detection drones, and the flight trajectories of the vibration detection drones, the multi-aircraft cooperation efficiency and detection accuracy can be improved.

[0043] In one embodiment, performing simulation patrol inspections on the candidate flight trajectories of the temperature detection drones, the candidate flight trajectories of the discharge detection drones, and the candidate flight trajectories of the vibration detection drones corresponding to each particle in the second iteration population to obtain the simulation patrol inspection accuracy corresponding to each particle in the second iteration population includes: based on the temperature rise information of the main transformer and the temperature rise propagation path, performing simulation patrol inspections on the candidate flight trajectories of the temperature detection drones corresponding to each particle in the second iteration population to obtain the temperature detection accuracy corresponding to each particle in the second iteration population; based on the discharge interference information of the main transformer and the discharge interference propagation path, performing simulation patrol inspections on the candidate flight trajectories of the discharge detection drones corresponding to each particle in the second iteration population to obtain the discharge detection accuracy corresponding to each particle in the second iteration population; based on the vibration mutation information of the main transformer and the vibration propagation path, performing simulation patrol inspections on the candidate flight trajectories of the vibration detection drones corresponding to each particle in the second iteration population to obtain the vibration detection accuracy corresponding to each particle in the second iteration population; determining the simulation patrol inspection accuracy corresponding to each particle in the second iteration population based on the temperature detection accuracy, the discharge detection accuracy, and the vibration detection accuracy corresponding to each particle in the second iteration population.

[0044] Exemplarily, based on the temperature rise information of the main transformer and the temperature rise propagation path, control the simulation models corresponding to each transformer in the temperature rise propagation path to perform temperature rise, and at the same time, control the simulation model corresponding to the temperature detection UAV to perform simulation patrol according to the candidate flight trajectory of the temperature detection UAV corresponding to the particle. Based on the detection results of the temperature rise changes of each transformer in this path by the simulation model corresponding to the temperature detection UAV, determine the temperature detection accuracy of the particle.

[0045] Exemplarily, based on the discharge interference information of the main transformer and the discharge interference propagation path, control the simulation models corresponding to each transformer in the discharge interference propagation path to perform corresponding discharge interference, and at the same time, control the simulation model corresponding to the discharge detection UAV to perform simulation patrol according to the candidate flight trajectory of the discharge detection UAV corresponding to the particle. Based on the detection results of the discharge interference intensity of each transformer in this path by the simulation model corresponding to the discharge detection UAV, determine the discharge detection accuracy corresponding to the particle.

[0046] Exemplarily, based on the vibration mutation information of the main transformer and the vibration propagation path, control the simulation models corresponding to each transformer in the vibration propagation path to perform corresponding vibration, and at the same time, control the simulation model corresponding to the vibration detection UAV to perform simulation patrol according to the candidate flight trajectory of the vibration detection UAV corresponding to the particle. Based on the detection results of the vibration mutation conditions of each transformer in this path by the simulation model corresponding to the vibration detection UAV, determine the vibration detection accuracy of the particle.

[0047] Exemplarily, if any one of the temperature detection accuracy, discharge detection accuracy, and vibration detection accuracy is lower than its corresponding accuracy threshold, use this item of accuracy as the simulation patrol accuracy.

[0048] Exemplarily, if the temperature detection accuracy, discharge detection accuracy, and vibration detection accuracy are all higher than their corresponding accuracy thresholds, perform weighted summation on the temperature detection accuracy, discharge detection accuracy, and vibration detection accuracy to obtain the simulation patrol accuracy corresponding to each particle.

[0049] According to the above embodiments, the simulation patrol accuracy corresponding to each particle in the population can be accurately calculated.

[0050] Figure 2 It is the structural block diagram of the multi - UAV collaborative device for substation patrol in an embodiment of the present invention.

[0051] As Figure 2 shown, the multi - UAV collaborative device for substation patrol includes: The propagation path determination module 210 determines 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, the discharge interference information, and the vibration mutation information of each core component during the phase conversion process of the main transformer in the substation when an abnormality occurs during the phase conversion process of the main transformer; The flight trajectory determination module 220 is used to optimize the flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV based on the temperature rise propagation path, the discharge interference propagation path, and the vibration propagation path to obtain the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV; The flight inspection control module 230 is used to control the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV to perform flight inspections respectively based on the target flight trajectories of the temperature detection UAV, the discharge detection UAV, and the vibration detection UAV.

[0052] In one implementation, the flight trajectory determination module 220 includes: The first trajectory determination unit is used to determine the first flight trajectory of the temperature detection UAV based on the temperature rise information and the temperature rise abnormal propagation path; The second trajectory determination unit is used to determine the second flight trajectory of the discharge detection UAV based on the discharge interference information and the discharge interference propagation path; The third trajectory determination unit is used to determine the third flight trajectory of the vibration detection UAV based on the discharge interference information and the vibration propagation path; The first trajectory adjustment unit is used to perform trajectory adjustment on the first flight trajectory, the second flight trajectory, and the third flight path based on the collision detection results of the first flight trajectory, the second flight trajectory, and the third flight trajectory to obtain the adjusted first flight trajectory, the adjusted second flight trajectory, and the adjusted third flight path; The second trajectory adjustment unit is used to perform 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 the target flight trajectory of the temperature detection UAV and the target flight trajectory of the vibration detection UAV; The third trajectory adjustment unit is used to determine the target flight trajectory of the vibration detection UAV based on the adjusted second flight trajectory.

[0053] In one implementation, the flight trajectory determination module includes: A trajectory function determination 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, 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, where the first iterative population includes a plurality of particles, and 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; A second population determination unit, configured to perform collision detection 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 first iterative population, and delete the particles with collision risks in the first iterative population based on the results of the collision detection to obtain a second iterative population; A simulation inspection unit, configured to perform simulation inspections 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 simulation inspection accuracies corresponding to each particle in the second iterative population; A fitness update unit, configured to update the individual optimal fitness based on the simulation inspection accuracies corresponding to each particle in the second iterative population; A target trajectory determination unit, configured to determine 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 based on the particles corresponding to the individual optimal fitness when the individual optimal fitness meets the preset fitness conditions.

[0054] In one implementation manner, it further includes: A population update loop module, configured to update the first iterative population when the individual optimal fitness does not meet the preset fitness conditions, and continue to execute the corresponding steps by using the second population determination unit, the simulation inspection unit, and the fitness update unit based on the updated first iterative population.

[0055] In one implementation manner, the simulation inspection unit is specifically configured to: Based on the temperature rise information of the main transformer and the temperature rise propagation path, perform simulation inspections on the candidate flight trajectories of the temperature detection UAV corresponding to each particle in the second iterative population to obtain the temperature detection accuracies 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, perform simulation inspections on the candidate flight trajectories of the discharge detection drones corresponding to each particle in the second iteration population, and obtain the discharge detection accuracies corresponding to each particle in the second iteration population; Based on the vibration mutation information of the main transformer and the vibration propagation path, perform simulation inspections on the candidate flight trajectories of the vibration detection drones corresponding to each particle in the second iteration population, and obtain the vibration detection accuracies corresponding to each particle in the second iteration population; Based on the temperature detection accuracies, discharge detection accuracies, and vibration detection accuracies corresponding to each particle in the second iteration population, determine the simulation inspection accuracies corresponding to each particle in the second iteration population.

[0056] For the specific functions and example descriptions of the various modules and sub-modules of the system according to the embodiments of the present invention, reference may be made to the relevant descriptions of the corresponding steps in the above method embodiments, which will not be elaborated herein.

[0057] In the technical solution of the present invention, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0058] According to the embodiments of the present invention, the present invention also provides a system and a readable storage medium.

[0059] Figure 3 FIG. shows a schematic block diagram of an exemplary electronic device 800 that can be used to implement the embodiments of the present invention. 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, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0060] As Figure 3 shown, the device 800 includes a computing unit 801, which can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 802 or the computer program loaded from the storage unit 808 into the random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other through a bus 804. The input / output (I / O) interface 805 is also connected to the bus 804.

[0061] Multiple components in device 800 are connected to I / O interface 805, including: input unit 806, such as a keyboard, mouse, etc.; output unit 807, such as various types of displays, speakers, etc.; storage unit 808, such as a disk, optical disc, etc.; and communication unit 809, such as a network card, modem, wireless communication transceiver, etc. 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.

[0062] Computing unit 801 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of computing unit 801 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated 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. Computing unit 801 executes the various methods and processes described above, such as the multi-drone collaborative method for substation inspection. For example, in some embodiments, the multi-drone collaborative method for substation inspection can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 800 via ROM 802 and / or communication unit 809. When the computer program is loaded into RAM 803 and executed by computing unit 801, one or more steps of the multi-drone collaborative method for substation inspection described above can be executed. Alternatively, in other embodiments, computing unit 801 can be configured to execute the multi-drone collaborative method for substation inspection in any other suitable manner (e.g., by means of firmware).

[0063] Various embodiments of the systems and techniques described above 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), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0064] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0065] In the context of the present invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would 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), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0066] In order 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 a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the computer. Other kinds 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, speech input, or tactile input).

[0067] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0068] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

[0069] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added, or deleted. For example, the steps recited in the present invention can be executed 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, and no limitations are imposed herein.

[0070] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-machine collaborative method for substation inspection by unmanned aerial vehicles, characterized in that: include: In the event of an abnormality in the phase change process of the main transformer of 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, 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, the discharge interference propagation path and the 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; 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 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 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, including: Determining a first flight trajectory of the temperature detection drone based on the temperature rise information and the temperature rise anomaly propagation path; Determining a second flight trajectory of the discharge detection UAV based on the discharge interference information and the discharge interference propagation path; Determining a third flight trajectory of the vibration detection UAV based on the vibration mutation information and the vibration propagation path; Based on the collision detection results of the first flight trajectory, the second flight trajectory and the third flight trajectory, adjusting the first flight trajectory, the second flight trajectory and the third flight trajectory to obtain the adjusted first flight trajectory, the adjusted second flight trajectory and the adjusted third flight path; 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 to obtain the target flight trajectory of the temperature detection UAV and the target flight trajectory of the vibration detection UAV; Based on the adjusted second flight trajectory, a target flight trajectory of the vibration detection UAV is determined.

3. The method according to claim 1, characterized in that The method optimizes 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 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, including: Based on the temperature rise propagation path, the discharge interference propagation path and the vibration propagation path, respectively determine a first flight trajectory function, a second flight trajectory function and a third flight trajectory function; Based on the first flight trajectory function, the second flight trajectory function and the third flight trajectory function, determining a first iterative population, wherein the first iterative population includes a plurality of particles, each particle corresponding 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; 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 result of the collision detection, deleting particles with collision risks in the first iterative population to obtain a second iterative population; Performing 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, and obtaining 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, 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.

4. The method according to claim 3, 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 result of the collision detection, deleting particles with collision risks in the first iterative population to obtain a second iterative population; Performing 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, and obtaining 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.

5. The method according to claim 3 or 4, 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 to obtain the simulated inspection accuracy corresponding to each particle in the second iterative population includes: Based on the temperature rise information of the main transformer and the temperature rise propagation path, a simulated inspection is performed on the candidate flight trajectory 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; Based on the temperature detection accuracy, discharge detection accuracy, and 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.

6. A multi-machine collaborative device for substation inspection by drone, characterized in that: include: A propagation path determination module, in the event that an abnormality occurs during the phase change process of the main transformer of 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, respectively determines the temperature rise propagation path, discharge interference propagation path and vibration propagation path of the main transformer in the substation; A flight trajectory determination module, used 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 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; 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.

7. The device according to claim 6, characterized in that The flight trajectory determination module comprises: A first trajectory determination unit, configured to determine a first flight trajectory of the temperature detection UAV 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 adjustment 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 an adjusted first flight trajectory, an adjusted second flight trajectory, and an adjusted third flight path; a second trajectory adjustment unit, configured to perform 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, so as 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 used to determine the target flight trajectory of the vibration detection UAV based on the adjusted second flight trajectory.

8. The device according to claim 6, characterized in that The flight trajectory determination module comprises: 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, each particle corresponding 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 is used to perform collision detection 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 first iterative population, and based on the result of the collision detection, delete particles with collision risks in the first iterative population to obtain a second iterative population; A simulation inspection unit, used to perform simulation inspections 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 simulation inspection accuracy corresponding to each particle in the second iterative population; A fitness updating unit, used for updating the individual optimal fitness based on the simulation inspection accuracy corresponding to each particle in the second iterative population; The target trajectory determination unit is used 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.

9. A UAV substation inspection multi-machine collaborative system, 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 5.

10. 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 1-5.

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