CN115454128A - Power transmission line inspection method and storage medium based on digital twin and Beidou grids - Google Patents
Power transmission line inspection method and storage medium based on digital twin and Beidou grids Download PDFInfo
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Abstract
The application provides a power transmission line inspection method and a storage medium based on digital twin and Beidou grids, wherein the inspection method comprises the following steps: constructing a system which consists of an enhanced unmanned aerial vehicle and an unmanned aerial vehicle cluster and is used for inspecting the power transmission line; carrying out grid coding positioning conversion on an electric tower and a power distribution network line of an inspection line based on Beidou grid codes, dividing the inspection line into Beidou grids, and associating multi-source data of the inspection line to generate a digital twin line diagram; and based on the digital twin line diagram, controlling the unmanned aerial vehicle cluster to carry out routing inspection through the enhanced unmanned aerial vehicle. The power transmission line inspection method and the storage medium based on the digital twin and the Beidou grids are associated by using the position information of the Beidou grid codes, so that the purpose of quickly positioning and accurately inspecting is achieved, and the advantages of improving detection efficiency, accuracy and safety and the like are achieved.
Description
Technical Field
The application relates to the technical field of power distribution network inspection, in particular to a power transmission line inspection method and a storage medium based on digital twin and Beidou grids.
Background
The distribution network is an important component of an electric power system and is responsible for receiving electric energy from a transmission network or a regional power plant and distributing the electric energy to various users on site or step by step according to voltage through distribution facilities. Therefore, the safe and stable operation of the distribution line plays an important role in the safety of the whole power supply system, and is the basis of social stability and daily life of common people. Traditional distribution network line needs the operation and maintenance personnel to patrol and examine regularly, looks up the observation closely, ensures the normal operation of circuit. When the equipment is in the eminence, the operation and maintenance personnel can not directly observe, and have the defects of poor safety coefficient of routing inspection, low efficiency and the like. Along with the development of unmanned aerial vehicle technique, unmanned aerial vehicle has widely been used in the electric power inspection business activity as novel platform of patrolling and examining owing to characteristics such as nimble, light, can reach personnel can't reach or inconvenient place that reachs. Can patrol and examine joining in marriage the fine-tuning of net twine way through unmanned aerial vehicle, the difficult defect of finding in artifical patrolling and examining such as fastener fracture, bolt looseness, damper off-position and conductor spacer pine is surveyable in unmanned aerial vehicle's high definition image. Unmanned aerial vehicle can accomplish the distribution network task of patrolling and examining safely more high-efficiently, liberates the personnel of patrolling and examining from the physical labor of high strength, high risk, repeatability.
In the course of conceiving and implementing the present application, the applicant found that at least the following problems exist: when the unmanned aerial vehicle is used for power distribution network inspection, the shooting tower and lines are mainly controlled manually by inspection personnel, so that the requirement on the inspection personnel is high; because the unmanned aerial vehicle is restrained by the cruising ability, the single flight can only patrol and examine partial poles and towers, but all poles and towers need to be regularly patrolled and examined to guarantee the normal operating of key component.
Disclosure of Invention
In order to alleviate the above problems, the present application provides a power transmission line inspection method and a storage medium based on digital twins and Beidou grids.
In one aspect, the application provides a power transmission line inspection method based on digital twins and Beidou grids, specifically, includes:
constructing a system which consists of an enhanced unmanned aerial vehicle and an unmanned aerial vehicle cluster and is used for inspecting the power transmission line;
based on Beidou grid codes, carrying out grid coding positioning conversion on an electric tower and a power distribution network line of an inspection line, dividing the inspection line into Beidou grids, and associating multi-source data of the inspection line to generate a digital twin line diagram;
and based on the digital twin line diagram, controlling the unmanned aerial vehicle cluster to patrol by the enhanced unmanned aerial vehicle.
Optionally, the step of dividing the patrol route into the beidou grids in the transmission line patrol method based on the digital twin and beidou grids comprises:
carrying out grid coding positioning conversion on the electric tower and the power distribution network line to form a grid position database, wherein the grid position database is used for storing line positioning data, and the line positioning data comprises grid codes, ultra-wideband position data and video data;
and generating the Beidou grid according to the grid position database.
Optionally, the step of generating the digital twin line diagram in the power line inspection method based on the digital twin and Beidou grids comprises:
and constructing a three-dimensional grid graph of the inspection line based on the Beidou grid, and dynamically associating the multi-source data to generate a digital twin line graph, wherein the digital twin line graph comprises CAD data, three-dimensional data, an electronic map and a remote sensing image.
Optionally, the step of generating the digital twin line diagram in the power line inspection method based on the digital twin and Beidou grids further includes:
and the remote sensing image is respectively in data association with the CAD data, the three-dimensional data and the electronic map.
Optionally, the step of generating the digital twin line diagram in the power line inspection method based on the digital twin and Beidou grids further includes:
according to the Beidou grid, acquiring distribution line geographic data, electric tower positions, enhanced unmanned aerial vehicle routing inspection line data, unmanned aerial vehicle cluster basic data, unmanned aerial vehicle cluster flight control data and distribution line surrounding environment data;
according to a digital twin technology, after a distribution line three-dimensional model, an electric tower three-dimensional model, an enhanced unmanned aerial vehicle position three-dimensional model, an unmanned aerial vehicle cluster position three-dimensional model and a distribution line surrounding environment three-dimensional model are respectively generated, the three-dimensional models are combined to generate the digital twin line diagram.
Optionally, the step of acquiring the basic data of the unmanned aerial vehicle cluster in the power transmission line inspection method based on the digital twin and Beidou grids comprises:
and planning a path of the unmanned aerial vehicle cluster based on a genetic algorithm to generate the basic data of the unmanned aerial vehicle cluster.
Optionally, the step of generating the digital twin line diagram in the power line inspection method based on the digital twin and Beidou grids comprises:
setting a starting point of the unmanned aerial vehicle cluster, routing inspection of branch towers and weights of towers to be inspected, and constructing a mathematical model for path planning, wherein the weights represent time intervals from the last routing inspection of the towers, and the larger the weights are, the longer the time intervals are;
and based on the mathematical model, performing population initialization by setting constraint conditions to generate a routing inspection path.
Optionally, the step of generating the patrol route in the power transmission line patrol method based on the digital twin and Beidou grids comprises:
generating a tower set serving as a routing inspection target by taking the starting point of the enhanced unmanned aerial vehicle as a circle center and the cruising ability of the unmanned aerial vehicle cluster as a diameter;
randomly arranging the tower numbers of the tower set to generate a chromosome to obtain a patrol sub-path, wherein whether the chromosome has the same tower number is judged, and redundant numbers are deleted; calculating the path length of the unmanned aerial vehicle according to the chromosome code, dividing the path length by the flight speed of the unmanned aerial vehicle to obtain the flight time of the routing inspection path, and if the flight time exceeds the endurance time, sequentially deleting the serial numbers from small to large according to the weight of the tower; when the two weights are the same, preferentially deleting the tower with the farthest distance until the flight time is less than or equal to the endurance time of the unmanned aerial vehicle;
and generating the routing inspection path based on each routing inspection sub-path.
Optionally, the step of performing the routing inspection sub-path generation in the power transmission line inspection method based on the digital twin and beidou grids comprises:
performing cross operation on each chromosome of the parent population to generate an offspring population;
performing mutation operation on the parent population and the child population based on Metropolis criterion, and sequencing according to the fitness of the chromosomes, wherein the child population comprises a first chromosome number, and the parent population comprises a second chromosome number;
and combining the first chromosome number digit after the fitness ranking of the offspring population, the corresponding first chromosome, the second chromosome number digit before the fitness ranking of the parent population and the corresponding second chromosome to form a new population, and iterating until the routing inspection path is generated.
In another aspect, the present application provides a storage medium, in particular, having stored thereon a computer program which, when executed by a processor, implements a digital twin and beidou mesh based power line inspection method as described above.
As mentioned above, the power transmission line inspection method and the storage medium based on the digital twin and Beidou grids provided by the application are associated by using the position information of the Beidou grid codes, so that the purpose of rapid positioning and accurate inspection is realized, and the advantages of improving the detection efficiency, improving the accuracy safety and the like are achieved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart of a power transmission line inspection method based on digital twin and Beidou grids according to an embodiment of the present application.
Fig. 2 is a structure diagram of the enhanced unmanned aerial vehicle of an embodiment of the present application.
Fig. 3 is a flowchart of enhancing the operation of the drone according to an embodiment of the present application.
Fig. 4 is a structural diagram of an unmanned aerial vehicle cluster according to an embodiment of the present application.
Fig. 5 is a flowchart of the operation of the unmanned aerial vehicle cluster according to an embodiment of the present application.
Fig. 6 is a flowchart of a power line inspection method based on digital twin and Beidou grids according to another embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings. Specific embodiments of the present application have been shown by way of example in the drawings and will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element, and further, components, features, elements, and/or steps that may be similarly named in various embodiments of the application may or may not have the same meaning, unless otherwise specified by its interpretation in the embodiment or by context with further embodiments.
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one aspect, the application provides a power transmission line inspection method based on a digital twin and a beidou grid, and fig. 1 is a flowchart of the power transmission line inspection method based on the digital twin and the beidou grid according to an embodiment of the application.
Referring to fig. 1, in an embodiment, a power line inspection method based on digital twin and Beidou grids includes:
s10: the system for patrolling and examining the power transmission line, which is composed of the enhanced unmanned aerial vehicle and the unmanned aerial vehicle cluster, is constructed.
Optionally, the unmanned aerial vehicle of the application is divided into two forms of an enhanced unmanned aerial vehicle and an unmanned aerial vehicle cluster.
Fig. 2 is a structure diagram of the enhanced unmanned aerial vehicle of an embodiment of the present application. Fig. 3 is a flowchart of enhancing the operation of the drone according to an embodiment of the present application. Referring to fig. 2 and 3, the enhanced drone includes a camera: the method comprises the following steps of preparing for shooting the whole routing inspection path by the enhanced unmanned aerial vehicle for the first time, and for later-stage Beidou grids, digital twins and automatic routing inspection paths; a WIFI module: the enhanced unmanned aerial vehicle can fall at the circular center position of a common unmanned aerial vehicle cluster in the automatic inspection process, information of each unmanned aerial vehicle is transmitted to the cloud, and WIFI transmission information is selected for preventing disordered communication when the enhanced unmanned aerial vehicle sends an automatic inspection instruction to the common unmanned aerial vehicle; big dipper module: acquiring a geographical position map by using a Beidou module, and carrying out Beidou grid positioning on a pole tower in a distribution line according to the position; a positioning device: the patrol personnel can check the current position of the enhanced unmanned aerial vehicle through the positioning device and can find the enhanced unmanned aerial vehicle in time when the enhanced unmanned aerial vehicle fails; a wireless communication device: an automatic inspection algorithm is arranged in the enhanced unmanned aerial vehicle, the enhanced unmanned aerial vehicle can send the enhanced unmanned aerial vehicle to the common unmanned aerial vehicle cluster through 5G, and the common unmanned aerial vehicle cluster can automatically perform inspection when receiving an instruction; a data storage device: when the cloud end has a problem, the polling personnel can check the polling record through the data storage device; a power supply device: because the enhanced unmanned aerial vehicle can run the algorithm when running, the power consumption can be increased in order to keep endurance. Only supply power to camera, WIFI module, big dipper module, positioner, data storage device when patrolling and examining the shooting for the first time. When automatic patrolling and examining in the back, can open WIFI module, big dipper module, positioner, wireless communication device, data storage device.
Fig. 4 is a structural diagram of an unmanned aerial vehicle cluster according to an embodiment of the present application. Fig. 5 is a flowchart of the operation of the unmanned aerial vehicle cluster according to an embodiment of the present application. Referring to fig. 4 and 5, the unmanned aerial vehicle cluster includes a WIFI module: when the cloud uploading of the enhanced unmanned aerial vehicle is in a problem, the power supply system can supply power to the WIFI module to enable the WIFI module to be directly uploaded to the cloud, otherwise, the WIFI module is not turned on to keep supplying power; a camera: the common unmanned aerial vehicle cluster sends the video to the enhanced unmanned aerial vehicle through the wireless communication device in the routing inspection process, and the video is uploaded to the cloud end by the enhanced unmanned aerial vehicle; a positioning device: the patrol personnel can check the current position of the unmanned aerial vehicle cluster through the positioning device and can find the unmanned aerial vehicle cluster in time when the unmanned aerial vehicle cluster fails; a wireless communication device: the system is used for receiving an automatic routing inspection path instruction and a distributed path of the enhanced unmanned aerial vehicle and sending a current video to the enhanced unmanned aerial vehicle; a data storage device: when the wireless communication device and the WIFI module of the common unmanned aerial vehicle cluster have faults, the data storage module can be checked; a power supply device: can utilize power supply unit to close the power supply of WIFI module when unmanned aerial vehicle cluster work, can open the power supply when enhancing the unmanned aerial vehicle high in the clouds problem, practice thrift electric power, increase continuation of the journey.
S20: and based on the Beidou grid codes, carrying out grid coding positioning conversion on the electric tower and the power distribution network line of the routing inspection line, dividing the routing inspection line into Beidou grids, associating multi-source data of the routing inspection line, and generating a digital twin line diagram.
Optionally, the beidou grid code is a short for beidou grid code and big data organization and utilization technology system, and is a fundamental major innovation of space-time big data category which is independently original in china and expected to lead global standard, and includes two levels of contents: the Beidou grid code technology and the Beidou grid-based space-time big data organization and utilization technology are characterized in that Beidou grid codes are used as a space-time big data basic organization framework and a big data analysis and utilization basic tool to support and create a space-time big data base facing a digital twin world, and a universal data interconnection and intercommunication space-time standard of a current digital new infrastructure is formed, so that the promotion of a national strategy of 'digital China and intelligent society' is assisted. The Beidou grid technology can greatly simplify the complexity of identification, expression and calculation of the location information, and has unique advantages in the aspects of information calculation speed, information indexing efficiency, information exchange and integration, expansion and enhancement of navigation positioning capability and the like. More importantly, the method not only can effectively make up for the defects and short boards under the traditional longitude and latitude technical system, but also can be perfectly compatible with the longitude and latitude, and is extremely perfect and complementary to the longitude and latitude technical system; the method not only can effectively solve the organization problem of massive, multi-source and heterogeneous spatial information, but also can be very conveniently converted with information systems under various existing technical systems.
S30: based on the digital twin line diagram, the unmanned aerial vehicle cluster is controlled by the enhanced unmanned aerial vehicle for routing inspection.
Optionally, the digital twin is to fully utilize data such as a physical model, sensor update, operation history and the like, integrate a multidisciplinary, multi-physical quantity, multi-scale and multi-probability simulation process, and complete mapping in a virtual space, so as to reflect a full life cycle process of corresponding entity equipment. Digital twinning is an beyond-realistic concept that can be viewed as a digital mapping system of one or more important, interdependent equipment systems.
In this embodiment, the power transmission line inspection method based on digital twin and big dipper net utilizes the position information that big dipper net code itself had to carry out the correlation, realize the purpose of the accurate searching of quick location, contain the three-dimensional grid map of constructing the distribution network circuit according to big dipper net code, and dynamic association multisource data, form digital twin circuit diagram, to patrolling and examining the route planning and conveying the reinforcing unmanned aerial vehicle in, the instruction that reinforcing unmanned aerial vehicle assigned to the unmanned aerial vehicle cluster is patrolled and examined the distribution network circuit, have advantages such as improvement detection efficiency and accuracy safety.
In an embodiment, the power line inspection method based on the digital twin and Beidou grids executes S20: the step of dividing the routing inspection line into Beidou grids comprises the following steps:
s21: carrying out grid coding positioning conversion on the electric tower and the power distribution network line to form a grid position database, wherein the grid position database is used for storing line positioning data, and the line positioning data comprises grid codes, ultra-wideband position data and video data;
s22: and generating the Beidou grid according to the grid position database.
In this embodiment, the beidou grid technology includes line location data: and carrying out grid coding positioning conversion on the electric tower and the power distribution network line, forming a grid position database and establishing data. The power distribution network line positioning data comprises grid codes, ultra wide band position data and video data, and the ultra wide band position data and the video data are connected with the grid codes through bidirectional signals. The Beidou network technology further comprises a Beidou grid terminal: the method is used for establishing, fusing, calculating and the like data among all terminals of a planning system; data processing: the method is used for basic data processing of the power distribution network line planning system.
In an embodiment, the power line inspection method based on the digital twin and Beidou grids executes S20: the step of generating a digital twin map comprises:
s200: and constructing a three-dimensional grid graph of the inspection line based on the Beidou grid, dynamically associating multi-source data, and generating a digital twin line graph, wherein the digital twin line graph comprises CAD data, three-dimensional data, an electronic map and a remote sensing image.
Optionally, the three-dimensional application scene generated by the digital twin comprises CAD data, three-dimensional data, an electronic map and a remote sensing image, and all the CAD data, the three-dimensional data, the electronic map and the remote sensing image are in bidirectional signal connection.
In one embodiment, the power line inspection method based on the digital twin and Beidou grids executes S20: the step of generating a digital twin map further comprises:
s210: and the remote sensing image is respectively associated with the CAD data, the three-dimensional data and the electronic map.
In one embodiment, the power line inspection method based on the digital twin and Beidou grids executes S20: the step of generating a digital twin map further comprises:
s220: according to the Beidou grid, acquiring distribution line geographic data, electric tower positions, enhanced unmanned aerial vehicle routing inspection line data, unmanned aerial vehicle cluster basic data, unmanned aerial vehicle cluster flight control data and distribution line surrounding environment data;
s230: according to the digital twin technology, after a distribution line three-dimensional model, an electric tower three-dimensional model, an enhanced unmanned aerial vehicle position three-dimensional model, an unmanned aerial vehicle cluster position three-dimensional model and a distribution line surrounding environment three-dimensional model are respectively generated, the three-dimensional models are combined to generate a digital twin line diagram.
Optionally, according to the Beidou grid code obtained by the Beidou grid technology, distribution line geographic data are obtained, the position of an electric tower, the data of an enhanced unmanned aerial vehicle routing inspection line, the basic data of an unmanned aerial vehicle cluster, the data of unmanned aerial vehicle cluster flight control and the data of distribution line surrounding environment are based on digital twinning technology to the distribution line data, the data of the electric tower, the data of the enhanced unmanned aerial vehicle routing inspection line, the data of the unmanned aerial vehicle cluster and the data of the distribution line surrounding environment are respectively processed, and a distribution line three-dimensional model, an electric tower three-dimensional model, an enhanced unmanned aerial vehicle position three-dimensional model, an unmanned aerial vehicle cluster position three-dimensional model and a distribution line surrounding environment three-dimensional model are obtained. And combining the three-dimensional models to obtain a power inspection digital twin scene.
In an embodiment, the power line inspection method based on the digital twin and the beidou grid executes S220: the step of obtaining the basic data of the unmanned aerial vehicle cluster comprises the following steps:
s221: and based on a genetic algorithm, carrying out path planning on the unmanned aerial vehicle cluster to generate the basic data of the unmanned aerial vehicle cluster.
Alternatively, genetic Algorithm (GA) is a heuristic Algorithm proposed by professor John h holland, michigan university, which simulates natural evolutionary mechanisms and biological evolutionary theory, and is a typical class of algorithms. The genetic algorithm is an algorithm irrelevant to the problem, and performs operations such as selection, intersection, variation and the like on the codes of the parameters, so that the chromosomes in the population are evaluated only by a fitness function without knowing relevant knowledge of the problem. The genetic algorithm is widely applied to the field of combination optimization such as unmanned aerial vehicle path planning by the aid of the advantages.
In an embodiment, the power line inspection method based on the digital twin and Beidou grids executes S20: based on big dipper net code, carry out the grid coding location conversion to the electric tower and the distribution network circuit of patrolling and examining the circuit, will patrol and examine the circuit and divide into big dipper net to the multisource data of patrolling and examining the circuit is correlated, and the step that generates the digital twin circuit diagram includes:
s222: the method comprises the steps of setting a starting point of an unmanned aerial vehicle cluster, routing inspection of branch towers and the weight of a tower to be inspected, and constructing a mathematical model for path planning, wherein the weight represents a time interval from the last time of routing inspection of the tower, and the larger the weight is, the longer the time interval is.
Optionally, the larger the weight of the tower to be inspected is, the longer the time interval is, the higher the priority of inspection of the tower is, and the unmanned aerial vehicle needs to be arranged to inspect the tower as soon as possible.
S223: based on the mathematical model, by setting constraint conditions, population initialization is carried out, and a routing inspection path is generated.
Illustratively, the step of establishing a mathematical model includes:
starting from a starting point 0, selecting part of towers for polling by the unmanned aerial vehicle, returning to a terminal point N +1 after completing a polling task, wherein the total duration from take-off to landing of the unmanned aerial vehicle cannot exceed the maximum duration T of the unmanned aerial vehicle max . Suppose that the unmanned aerial vehicle carries an automatic obstacle avoidance and stability augmentation device, has automatic obstacle avoidance and certain wind resistance, and the path deviation caused by wind influence or obstacle avoidance is ignored relative to the total flight path length. The starting point and the end point of the unmanned aerial vehicle are respectively represented by 0 and N +1, the set T = {1, …, i, …, N } is the set of all towers to be patrolled, and the set consisting of the starting point, the end point of the unmanned aerial vehicle and all the towers to be patrolled is A = {0,1, …, i, …, N, N +1}. W for weighting tower i to be patrolled and examined i (i ∈ T), indicating that the weight represents the time interval that tower i was last polled from. P = {0,i, …, j, N +1} (i, j ∈ T) represents a unmanned aerial vehicle patrol path, and the unmanned aerial vehicle finally returns to an end point after starting to execute a task. The flight time of the unmanned aerial vehicle between the tower i and the tower j is set as t ij ，d ij The Euclidean distance between the tower i and the tower j is shown, v is the flight speed of the unmanned aerial vehicle, and A is the combination of all vertexes. Then t ij ＝d ij V (assuming that any i, j are all from set A)
The time for executing the task corresponding to the unmanned aerial vehicle routing inspection task path P is set as, then
The maximum weight sum of the towers patrolled and examined by the unmanned aerial vehicle is used as a target function and is set as
The most important constraints are:
the intelligent inspection of each tower is carried out at most once,
wherein any j ∈ T
Endurance constraint of unmanned aerial vehicle, t p ≤T max
In an embodiment, the power transmission line inspection method based on the digital twin and the beidou grid executes step S223: the step of generating the routing inspection path comprises the following steps:
s224: generating a tower set serving as a polling target by taking the starting point of the enhanced unmanned aerial vehicle as a circle center and the cruising ability of the unmanned aerial vehicle cluster as a diameter;
s225: randomly arranging the tower numbers of the tower set to generate a chromosome to obtain a patrol sub-path, wherein whether the chromosome has the same tower number or not is judged, and redundant numbers are deleted; calculating the path length of the unmanned aerial vehicle according to the chromosome code, dividing the path length by the flight speed of the unmanned aerial vehicle to obtain the flight time of the routing inspection path, and if the flight time exceeds the endurance time, sequentially deleting the serial numbers from small to large according to the weight of the tower; and when the two weights are the same, preferentially deleting the tower with the farthest distance until the flight time is less than or equal to the endurance time of the unmanned aerial vehicle.
Optionally, the tower numbers of the tower set are randomly arranged, and after a chromosome is generated, constraint verification and adjustment of the chromosome are required. The chromosome after initialization and cross operation is possibly threatened to the situation that the intelligence of each tower is patrolled and examined once at most and the unmanned aerial vehicle endurance is restrained, and the following operations are carried out:
judging whether the chromosomes have the same tower numbers or not, and deleting redundant numbers to ensure that the chromosomes only appear once; calculating the path length of the unmanned aerial vehicle according to the chromosome codes, dividing the path length by the flight speed of the unmanned aerial vehicle to obtain the flight time of the path, if the length of the path exceeds the duration, deleting numbers from small to large according to the weights of the towers, and if the two weights are the same, preferentially deleting the tower with the farthest distance to ensure that the flight time of the path is less than or equal to the endurance time of the unmanned aerial vehicle. Finally, a feasible solution can be obtained by adjusting the chromosome.
S226: and generating a routing inspection path based on each routing inspection sub-path.
Illustratively, the step of generating the patrol path includes:
let T be the set that unmanned aerial vehicle patrolled and examined the shaft tower to reinforcing unmanned aerial vehicle's starting point is the centre of a circle, and the duration of unmanned aerial vehicle cluster is the diameter, constructs "T max Circle ", delete" T "in the set T max And numbering the towers outside the circle to obtain a tower set T which can be covered by the cruising ability of the unmanned aerial vehicle. And randomly arranging the tower numbers corresponding to the T in the set to design a chromosome, and obtaining the routing inspection path P. And repeating the above two steps according to the population scale to obtain an initial population.
Because the cruising ability of the unmanned aerial vehicle is limited, the initial population is not necessarily a feasible solution, so that each chromosome in the population needs to be subjected to constraint inspection, and the condition is not met for adjustment.
In one embodiment, the power line inspection method based on the digital twin and the beidou grids executes S225: the step of generating the patrol sub-path comprises the following steps:
s2250: and performing cross operation on each chromosome of the parent population to generate an offspring population.
Alternatively, the crossover operation refers to a crossover operation of selecting chromosomes from a parent population by using a roulette method, and the higher the fitness is, the higher the possibility that a point will be inherited is.
Illustratively, 2 crossed chromosomes were selected, denoted as parent A and parent B, to generate one [0,1 [ ]]Random number r of interval, if r is greater than P of cross probability c It is finished. If r is less than P of crossover probability c Since the chromosome length of the parents A and B may be different, 2 crossovers are generated, which are interchanged to obtain the children C and D.
S2251: and performing mutation operation on a parent population and an offspring population based on Metropolis criterion, and sequencing according to the fitness of the chromosomes, wherein the offspring population comprises a first chromosome number, and the parent population comprises a second chromosome number.
Optionally, fitness of the chromosome represents the superiority and inferiority of the path planning scheme, and the better the fitness is, the better the planning is, so that the sum of the weights of the towers patrolled and inspected by the unmanned aerial vehicle is maximized as a fitness function. Due to the different weights of the towers, it is possible to improve the fitness by replacing the numbers in the chromosomes. Meanwhile, length verification is carried out on chromosome paths, whether the routing inspection sequence of the tower is possible to cause the path of the short unmanned aerial vehicle to swell or not is changed, so that the unmanned aerial vehicle can access more towers, and the chromosome fitness is improved by using the following two mutation operators.
Illustratively, mutation operator a: and (4) gene replacement, wherein a gene position is randomly selected, and the tower number of the gene position is replaced by the tower number which does not appear in the tower set T which can be covered by the cruising ability of the unmanned aerial vehicle. Mutation operator B: and (3) gene exchange, wherein two gene positions are randomly selected, and the pole tower numbers on the two gene positions are exchanged. Each compiling operation randomly selects a mutation operator to generate a chromosome, then carries out constraint check and adjustment on the chromosome to obtain a new chromosome meeting the constraint, and receives the chromosome with a certain probability by applying the Metropolis criterion.
S2252: and combining the first chromosome number after the fitness ranking of the child population, the corresponding first chromosome, the second chromosome number before the fitness ranking of the parent population and the corresponding second chromosome to form a new population, and iterating until the patrol path is generated.
Optionally, the newly-born child population and the parent population are combined to achieve the purpose of population updating, and a routing inspection path is generated.
Illustratively, the chromosomes of the offspring population and the parent population are sorted according to fitness, respectively. Setting the number of chromosomes extracted from the offspring population as N 1 Population size N p Gap is a surrogate groove, the following areThe formula: n is a radical of hydrogen 1 ＝N p * And (4) Gap. The number of chromosomes extracted from the parent population is set as N 2 Then N is 2 ＝N p * (1-Gap). Rank from offspring population fitness N 1 Chromosome and father ranking top N of bits 2 Combining the chromosomes to obtain a new population, and iterating until the new population appears.
In another aspect, the present application provides a storage medium, in particular, a storage medium having a computer program stored thereon, fig. 6 is a flowchart of a power line inspection method based on digital twin and beidou grids according to another embodiment of the present application, please refer to fig. 6, when the computer program is executed by a processor, the power line inspection method based on digital twin and beidou grids as described above is implemented.
Illustratively, the Beidou grid code is short for a Beidou grid code and big data organization and utilization technology system, is an important innovation with domestic independent originality and hopeful lead of global standard space-time big data category foundation, and comprises two levels of contents: the Beidou grid code technology and the Beidou grid-based space-time big data organization and utilization technology are characterized in that Beidou grid codes are used as a space-time big data basic organization framework and a big data analysis and utilization basic tool to support and create a space-time big data base facing a digital twin world, and a universal data interconnection and intercommunication space-time standard of a current digital new infrastructure is formed, so that the promotion of a national strategy of 'digital China and intelligent society' is assisted. The method can greatly simplify the complexity of identifying, expressing and calculating the position information, and has unique advantages in the aspects of information calculation speed, information indexing efficiency, information exchange and integration, expansion and enhancement of navigation positioning capability and the like. More importantly, the method not only can effectively make up for the defects and short boards under the traditional longitude and latitude technical system, but also can be perfectly compatible with the longitude and latitude, and is extremely perfect and complementary to the longitude and latitude technical system; the method not only can effectively solve the organization problem of massive, multi-source and heterogeneous spatial information, but also can be very conveniently converted with information systems under various existing technical systems.
Optionally, the specific implementation of the Beidou grid technology is as follows:
1. beidou grid terminal: the method is used for establishing, fusing, calculating and the like data among all terminals of a planning system;
2. data processing: basic data processing for the power distribution network line planning system;
3. line positioning data: and carrying out grid coding positioning conversion on the electric tower, forming a grid position database and establishing data. The distribution network line positioning data comprises grid codes, ultra-wideband position data and video data, the ultra-wideband position data, the video data and the grid codes are in bidirectional signal connection, the three-dimensional application scene generated by digital twins at the back comprises CAD data, three-dimensional data, an electronic map and remote sensing images, and the CAD data, the three-dimensional data, the electronic map and the remote sensing images are in bidirectional signal connection.
The digital twin is a simulation process integrating multidisciplinary, multi-physical quantity, multi-scale and multi-probability by fully utilizing data such as a physical model, sensor updating, operation history and the like, and mapping is completed in a virtual space, so that the full life cycle process of corresponding entity equipment is reflected. Digital twinning is an beyond-realistic concept that can be viewed as a digital mapping system of one or more important, interdependent equipment systems.
Optionally, a digital twinning technique embodiment:
according to a Beidou grid code obtained by a Beidou grid technology, obtaining distribution line geographic data, an electric tower position, enhanced unmanned aerial vehicle patrol line data, unmanned aerial vehicle cluster basic data, unmanned aerial vehicle cluster flight control data and distribution line peripheral environment data after a genetic algorithm, and respectively processing the distribution line data, the electric tower data, the enhanced unmanned aerial vehicle patrol line data, the unmanned aerial vehicle cluster data and the distribution line peripheral environment data based on a digital twin technology to obtain a distribution line three-dimensional model, an electric tower three-dimensional model, an enhanced unmanned aerial vehicle position three-dimensional model, an unmanned aerial vehicle cluster position three-dimensional model and a distribution line peripheral environment three-dimensional model; and combining the three-dimensional models to obtain a power inspection digital twin scene.
Genetic Algorithm (GA) is a heuristic Algorithm, which simulates the evolution mechanism of nature and the biological theory of evolution, and is a typical cluster Algorithm [13]. The GA is an algorithm irrelevant to the problem, and is used for selecting, crossing, mutating and the like the codes of the parameters, so that the chromosomes in the population are evaluated only by a fitness function without knowing relevant knowledge of the problem. The advantage makes GA by combined optimization fields such as unmanned aerial vehicle route planning of wide application.
Firstly, establishing a mathematical model
Starting from a starting point 0, selecting part of towers for polling by the unmanned aerial vehicle, returning to a terminal point N +1 after completing a polling task, wherein the total duration from take-off to landing of the unmanned aerial vehicle cannot exceed the maximum duration T of the unmanned aerial vehicle max . Suppose that unmanned aerial vehicle carries on automatic obstacle avoidance and stability augmentation device, has automatic obstacle avoidance and certain anti-wind ability, because of wind
The path deviation caused by force effects or obstacle avoidance is negligible with respect to the total flight path length. The starting point and the end point of the unmanned aerial vehicle are respectively represented by 0 and N +1, the set T = {1, …, i, …, N } is the set of all towers to be patrolled, and the set consisting of the starting point, the end point of the unmanned aerial vehicle and all towers to be patrolled is A = {0,1, …, i, …, N, N +1}. W for weighting tower i to be patrolled and examined i (i ∈ T), indicating that the weight represents the time interval that tower i was last polled from. P = {0,i, …, j, N +1} (i, j ∈ T) represents a unmanned aerial vehicle inspection path, and the unmanned aerial vehicle finally returns to an end point after starting to execute a task. The flight time of the unmanned aerial vehicle between the tower i and the tower j is set as t ij ，d ij The Euclidean distance between the tower i and the tower j is shown, v is the flight speed of the unmanned aerial vehicle, and A is the combination of all vertexes. Then the
t ij ＝d ij V (assuming that any i, j are all from set A)
The time for executing the task corresponding to the unmanned aerial vehicle routing inspection task path P is set as, then
The maximum weight sum of the towers patrolled and examined by the unmanned aerial vehicle is used as a target function and is set as
The most important constraints are:
the intelligence of each tower is patrolled and examined once at most,
wherein any j ∈ T
Endurance constraint of unmanned aerial vehicle, t p ≤T max
Second, group initialization
A group of integer coding chromosomes is designed, and the numbers of all towers to be patrolled and examined are shown in a table 1:
| 2 | 10 | 8 | 4 | 6 |
TABLE 1 IGA Algorithm chromosome coding
The chromosomes in table 1 indicate that the unmanned aerial vehicle patrols the towers of No. 2, no. 10, no. 8, no. 4 and No. 6 in sequence from the starting point. And then returns to the site.
The population initialization steps are as follows:
1. let T be the set that unmanned aerial vehicle patrolled and examined shaft tower to strengthen unmanned aerial vehicleThe starting point of the unmanned aerial vehicle cluster is used as the circle center, the cruising ability of the unmanned aerial vehicle cluster is used as the diameter, and the T-shaped structure max Circle ", delete" T "in the set T max And numbering the towers outside the circle to obtain a tower set T which can be covered by the cruising ability of the unmanned aerial vehicle.
2. And randomly arranging the tower numbers corresponding to the T in the set to design a chromosome, and obtaining the routing inspection path P.
3. And repeating the steps 1 to 2 according to the population scale to obtain an initial population.
Because the cruising ability of the unmanned aerial vehicle is limited, the initial population is not necessarily a feasible solution, so that each chromosome in the population needs to be subjected to constraint test, and the condition is not met for adjustment.
Third, constraint checking and adjusting of chromosome
The chromosome after initialization and cross operation is possibly threatened by inspection once and unmanned aerial vehicle cruising ability constraint at most against each tower, and the following operation is carried out.
And judging whether the chromosomes have the same tower numbers or not, deleting redundant numbers and ensuring that the chromosomes only appear once.
Calculating the path length of the unmanned aerial vehicle according to the chromosome codes, dividing the path length by the flight speed of the unmanned aerial vehicle to obtain the flight time of the path, if the length of the path exceeds the duration, deleting numbers from small to large according to the weights of the towers, and if the two weights are the same, preferentially deleting the tower with the farthest distance to ensure that the flight time of the path is less than or equal to the endurance time of the unmanned aerial vehicle.
A feasible solution can be obtained by adjusting the chromosome.
Fitness evaluation of population
The fitness of the chromosome represents the advantages and disadvantages of the path planning scheme, and the better the fitness is, the better the planning is, so that the sum of the weights of the towers inspected by the unmanned aerial vehicle is maximized into a fitness function.
Evaluating the fitness of the population
The fitness of the chromosome represents the advantages and disadvantages of the path planning scheme, and the better the fitness is, the better the planning is, so that the sum of the weights of the towers inspected by the unmanned aerial vehicle is maximized into a fitness function.
Cross operation
The roulette method is selected to select chromosomes from the parent population for crossover operation, and the probability that a point will be inherited is higher as the fitness is higher.
Selecting 2 crossed chromosomes, marking as father A and father B, and generating a [0,1]Random number r of interval, if r is less than P of cross probability c The following 2 is performed, otherwise it ends.
Since the chromosomes of parent A and B may be of different lengths, 2 crossovers are generated, which are interchanged to give child C and child D.
Mutation operation of Metropolis criterion
It is possible to improve fitness by replacing the numbers in the chromosomes, since the weights of the towers are different. Meanwhile, length verification is carried out on chromosome paths, whether the routing inspection sequence of the tower is possible to cause the path of the short unmanned aerial vehicle to swell or not is changed, so that the unmanned aerial vehicle can access more towers, and the chromosome fitness is improved by using the following two mutation operators.
Mutation operator a: and (4) gene replacement, wherein a gene position is randomly selected, and the tower number of the gene position is replaced by the tower number which does not appear in the tower set T which can be covered by the cruising ability of the unmanned aerial vehicle.
Mutation operator B: and (4) gene exchange, wherein two gene positions are randomly selected, and pole tower numbers on the two gene positions are exchanged.
Each compiling operation randomly selects a mutation operator to generate a chromosome, then carries out constraint check and adjustment on the chromosome to obtain a new chromosome meeting the constraint, and receives the chromosome with a certain probability by applying the Metropolis criterion.
Eight-group update operation
The population update operation is an operation of merging a new offspring population with a parent population.
1. And respectively sequencing the chromosomes of the offspring population and the parent population according to the fitness.
2. Setting the number of chromosomes extracted from the offspring population as N 1 Population sizeIs N P Gap is a surrogate groove, and has the following formula: n is a radical of 1 ＝N p *Gap。
3. The number of chromosomes extracted from the parent population is set as N 2 Then N is 2 ＝N p *(1-Gap)。
4. Rank from offspring population fitness N 1 Chromosome and father class top N of bits 2 Combining the chromosome positions to obtain a new population, and iterating until the new population appears.
4.6 simulation results
| Total number of poles and towers | Number of inspection pole towers | Total path length/min | Algorithm run length/s |
| 80 | 27 | 21.3 | 53.6 |
| 80 | 43 | 21.2 | 53.1 |
| 80 | 70 | 21.5 | 53.8 |
| 80 | 31 | 30.1 | 53.7 |
| 80 | 68 | 30.2 | 53.2 |
| 80 | 80 | 29.1 | 53.4 |
| 80 | 53 | 32.5 | 53.4 |
| 80 | 75 | 32.1 | 52.4 |
| 80 | 80 | 28.4 | 53.6 |
TABLE 2 simulation results
Optionally, the unmanned aerial vehicle of this application divide into two kinds, and one kind is reinforcing unmanned aerial vehicle, and one kind is ordinary unmanned aerial vehicle cluster.
1. The enhanced drone may include:
(1) A camera: for the first time by reinforcing unmanned aerial vehicle to the shooting of whole route of patrolling and examining, for the big dipper net and the digital twin of later stage and automatic route of patrolling and examining make preparation.
(2) A WIFI module: the reinforcing unmanned aerial vehicle can fall on the circular centre of a circle position of ordinary unmanned aerial vehicle cluster at the in-process of automatic patrolling and examining, with every unmanned aerial vehicle's information transfer to high in the clouds, and the communication is chaotic when here in order to prevent reinforcing unmanned aerial vehicle from assigning the automatic instruction of patrolling and examining to ordinary unmanned aerial vehicle, so chooses for use WIFI conveying information.
(3) Big dipper module: and acquiring a geographical position map by using the Beidou module, and carrying out Beidou grid positioning on the pole tower in the distribution line according to the position.
(4) A positioning device: the patrol personnel can check the position where the enhanced unmanned aerial vehicle is located and find the enhanced unmanned aerial vehicle in time when the enhanced unmanned aerial vehicle breaks down through the positioning device.
(5) A wireless communication device: the enhanced unmanned aerial vehicle has an automatic inspection algorithm, the enhanced unmanned aerial vehicle can send the enhanced unmanned aerial vehicle to the common unmanned aerial vehicle cluster through 5G, and the common unmanned aerial vehicle cluster can automatically perform inspection when receiving an instruction.
(6) A data storage device: when the cloud end goes wrong, the patrol personnel can check the patrol record through the data storage device.
(7) A power supply device: because the enhanced unmanned aerial vehicle can run the algorithm when running, the power consumption can be increased in order to keep endurance. Only supply power to camera, WIFI module, big dipper module, positioner, data storage device when patrolling and examining the shooting for the first time. When automatic patrolling and examining in the back, can open WIFI module, beidou module, positioner, wireless communication device, data storage device.
2. The generic drone cluster may include:
(1) A WIFI module: when the cloud of reinforcing unmanned aerial vehicle uploads and goes wrong, power supply system can give the WIFI module power supply, lets it directly upload to the cloud, otherwise can not open the WIFI module, keeps the power supply.
(2) A camera: ordinary unmanned aerial vehicle cluster can be patrolled and examined the in-process and send the video for reinforcing unmanned aerial vehicle through wireless communication device, is uploaded to the high in the clouds by reinforcing unmanned aerial vehicle.
(3) A positioning device: the patrol personnel can check the current position of the unmanned aerial vehicle cluster through the positioning device and can find the unmanned aerial vehicle cluster in time when the unmanned aerial vehicle cluster breaks down.
(4) A wireless communication device: the video processing system is used for receiving the automatic routing inspection path instruction and the distributed path of the enhanced unmanned aerial vehicle and sending the current video to the enhanced unmanned aerial vehicle.
(5) A data storage device: when the wireless communication device and the WIFI module of the common unmanned aerial vehicle cluster break down, the data storage module can be checked.
(6) A power supply device: can utilize power supply unit to close the power supply of WIFI module when unmanned aerial vehicle cluster work, can open the power supply when enhancing the unmanned aerial vehicle high in the clouds problem, practice thrift electric power, increase continuation of the journey.
Optionally, please refer to fig. 3 for the enhanced drone workflow, and refer to fig. 5 for the general drone workflow.
As described above, the power transmission line inspection method and the storage medium based on the digital twin and the Beidou grids provided by the application comprise the Beidou grids, the digital twin, the unmanned aerial vehicle cluster and a genetic algorithm. Utilize the position information that big dipper grid code itself has to carry out the correlation, realize the purpose of the accurate searching of quick location, contain the three-dimensional grid map of constructing the distribution network circuit according to big dipper grid code, and dynamic association multisource data, form the twin circuit diagram of digit, utilize genetic algorithm to patrol and examine during route planning conveys reinforcing unmanned aerial vehicle, reinforcing unmanned aerial vehicle patrols and examines to the distribution network circuit to the instruction that unmanned aerial vehicle cluster assigned, consider the circumstances of environment pernicious, communication between reinforcing unmanned aerial vehicle and the unmanned aerial vehicle cluster chooses for use 5G, convey the message back to reinforcing unmanned aerial vehicle by the unmanned aerial vehicle cluster, reinforcing unmanned aerial vehicle sends to the high in the clouds, the high in the clouds receives in data can feed back to patrolling and examining personnel, have advantages such as improvement detection efficiency and accuracy safety.
It should be noted that, in the present application, step numbers such as S10 and S20 are used for the purpose of more clearly and briefly describing corresponding contents, and do not constitute a substantial limitation on the sequence, and those skilled in the art may perform S20 first and then S10 in the specific implementation, but these should be within the protection scope of the present application.
In the embodiments of the intelligent terminal and the computer-readable storage medium provided in the present application, all technical features of any one of the above-described method embodiments may be included, and the expanding and explaining contents of the specification are basically the same as those of the above-described method embodiments, and are not described herein again.
Embodiments of the present application further provide a computer program product, which includes computer program code, when the computer program code runs on a computer, the computer is caused to execute the method as in the above various possible embodiments.
Embodiments of the present application further provide a chip, which includes a memory and a processor, where the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that a device in which the chip is installed executes the method in the above various possible embodiments.
It is to be understood that the foregoing scenarios are only examples, and do not constitute a limitation on application scenarios of the technical solutions provided in the embodiments of the present application, and the technical solutions of the present application may also be applied to other scenarios. For example, as can be known by those skilled in the art, with the evolution of system architecture and the emergence of new service scenarios, the technical solution provided in the embodiments of the present application is also applicable to similar technical problems.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
The steps in the method of the embodiment of the application can be sequentially adjusted, combined and deleted according to actual needs.
The units in the device in the embodiment of the application can be merged, divided and deleted according to actual needs.
In the present application, the same or similar term concepts, technical solutions and/or application scenario descriptions will be generally described only in detail at the first occurrence, and when the description is repeated later, the detailed description will not be repeated in general for brevity, and when understanding the technical solutions and the like of the present application, reference may be made to the related detailed description before the description for the same or similar term concepts, technical solutions and/or application scenario descriptions and the like which are not described in detail later.
In the present application, each embodiment is described with emphasis, and reference may be made to the description of other embodiments for parts that are not described or illustrated in any embodiment.
The technical features of the technical solution of the present application may be arbitrarily combined, and for brevity of description, all possible combinations of the technical features in the embodiments are not described, however, as long as there is no contradiction between the combinations of the technical features, the scope of the present application should be considered as being described in the present application.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A power transmission line inspection method based on digital twin and Beidou grids is characterized by comprising the following steps:
constructing a system which consists of an enhanced unmanned aerial vehicle and an unmanned aerial vehicle cluster and is used for inspecting the power transmission line;
based on Beidou grid codes, carrying out grid coding positioning conversion on an electric tower and a power distribution network line of an inspection line, dividing the inspection line into Beidou grids, and associating multi-source data of the inspection line to generate a digital twin line diagram;
and based on the digital twin line diagram, controlling the unmanned aerial vehicle cluster to carry out routing inspection through the enhanced unmanned aerial vehicle.
2. A power transmission line inspection method based on digital twin and beidou grids as claimed in claim 1, wherein the step of dividing the inspection line into beidou grids comprises:
grid coding positioning conversion is carried out on the electric tower and the power distribution network lines to form a grid position database, wherein the grid position database is used for storing line positioning data, and the line positioning data comprise grid codes, ultra-wideband position data and video data;
and generating the Beidou grid according to the grid position database.
3. A power transmission line inspection method based on digital twin and beidou grids according to claim 1, wherein the step of generating a digital twin route map comprises:
and constructing a three-dimensional grid graph of the inspection line based on the Beidou grid, and dynamically associating the multi-source data to generate a digital twin line graph, wherein the digital twin line graph comprises CAD data, three-dimensional data, an electronic map and a remote sensing image.
4. A power line inspection method based on digital twin and beidou grids as claimed in claim 3, wherein the step of generating a digital twin route map further comprises:
and the remote sensing image is respectively in data association with the CAD data, the three-dimensional data and the electronic map.
5. A power line inspection method based on digital twin and beidou grids according to claim 4, wherein the step of generating a digital twin route map further comprises:
according to the Beidou grid, acquiring distribution line geographic data, electric tower positions, enhanced unmanned aerial vehicle routing inspection line data, unmanned aerial vehicle cluster basic data, unmanned aerial vehicle cluster flight control data and distribution line surrounding environment data;
according to a digital twin technology, after a distribution line three-dimensional model, an electric tower three-dimensional model, an enhanced unmanned aerial vehicle position three-dimensional model, an unmanned aerial vehicle cluster position three-dimensional model and a distribution line surrounding environment three-dimensional model are respectively generated, the three-dimensional models are combined to generate the digital twin line diagram.
6. A power transmission line inspection method based on digital twin and Beidou grids according to claim 5, wherein the step of obtaining unmanned aerial vehicle cluster basic data comprises:
and planning a path of the unmanned aerial vehicle cluster based on a genetic algorithm to generate the basic data of the unmanned aerial vehicle cluster.
7. A power transmission line inspection method based on digital twin and beidou grids according to claim 1, wherein the step of generating a digital twin route map comprises:
setting a starting point of the unmanned aerial vehicle cluster, routing inspection of branch towers and weights of towers to be inspected, and constructing a mathematical model for path planning, wherein the weights represent time intervals from the last routing inspection of the towers, and the larger the weights are, the longer the time intervals are;
and based on the mathematical model, performing population initialization by setting constraint conditions to generate a routing inspection path.
8. A power transmission line inspection method based on digital twin and beidou grids according to claim 7, wherein the step of generating an inspection path comprises:
generating a tower set serving as a routing inspection target by taking the starting point of the enhanced unmanned aerial vehicle as a circle center and the cruising ability of the unmanned aerial vehicle cluster as a diameter;
randomly arranging the tower numbers of the tower set to generate a chromosome to obtain a patrol sub-path, wherein whether the chromosome has the same tower number or not is judged, and redundant numbers are deleted; calculating the path length of the unmanned aerial vehicle according to the chromosome code, dividing the path length by the flight speed of the unmanned aerial vehicle to obtain the flight time of the routing inspection path, and if the flight time exceeds the endurance time, sequentially deleting the serial numbers from small to large according to the weight of the tower; when the two weights are the same, preferentially deleting the tower with the farthest distance until the flight time is less than or equal to the endurance time of the unmanned aerial vehicle;
and generating the routing inspection path based on each routing inspection sub-path.
9. A power transmission line inspection method based on digital twin and beidou grids according to claim 8, wherein the step of generating an inspection sub-path comprises:
performing cross operation on each chromosome of the parent population to generate an offspring population;
performing mutation operation on the parent population and the child population based on Metropolis criterion, and sequencing according to the fitness of the chromosomes, wherein the child population comprises a first chromosome number, and the parent population comprises a second chromosome number;
and combining the first chromosome number digit after the fitness ranking of the offspring population, the corresponding first chromosome, the second chromosome number digit before the fitness ranking of the parent population and the corresponding second chromosome to form a new population, and iterating until the routing inspection path is generated.
10. A storage medium having stored thereon a computer program which, when executed by a processor, implements a digital twin and beidou mesh based power line inspection method according to any one of claims 1 to 9.
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| CN116484118B (en) * | 2023-03-24 | 2024-04-09 | 中国科学院空天信息创新研究院 | Unmanned aerial vehicle flight environment data service system and method |
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| CN116342825B (en) * | 2023-05-24 | 2023-08-18 | 广东电网有限责任公司江门供电局 | Construction method and related device of three-dimensional visualization system of power grid |
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| CN117312591B (en) * | 2023-10-17 | 2024-03-12 | 南京海汇装备科技有限公司 | Image data storage management system and method based on virtual reality |
| CN117132086A (en) * | 2023-10-25 | 2023-11-28 | 广东电网有限责任公司佛山供电局 | Unmanned aerial vehicle laser operation plan arrangement method, system, equipment and medium |
| CN117132086B (en) * | 2023-10-25 | 2024-02-13 | 广东电网有限责任公司佛山供电局 | Unmanned aerial vehicle laser operation plan arrangement method, system, equipment and medium |
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