UAV transmission line deicing device and its digital control system

Abstract

The present invention discloses an unmanned aerial vehicle transmission line deicing device and its data-based control system. The device uses a radio remote control device and a self-contained program control module to control the unmanned aerial vehicle carrying a load, and controls the unmanned aerial vehicle to move quickly to drive the mounted impact mass rod to impact the ice-covered line with the impact force that meets the calculation result of the embedded data characterization model to perform deicing operations on the ice-covered transmission line; the radio remote control device optimizes the flight algorithm based on the self-contained program control module to control the data source to perform fully or intermittently automated unmanned aerial vehicle deicing operations. The present invention is based on joint technical research and development by multiple parties, based on the construction of a multivariate linear data process and its data system, and considering the real-time change impact of multi-index characterization parameters. Through the gradual iterative evolution and supplementary construction of data, a relatively superior data characterization architecture is fitted, and the technical progress is very significant. It is a pioneering innovation in the field of transmission line deicing technology.

Description

Technical Field

[0001] The present invention relates to the technical field of power line deicing, and in particular to a deicing system based on an impact vibration data model of a power line controlled by an unmanned aerial vehicle. Background Art

[0002] Common types of icing on power transmission and distribution lines include rime, mixed rime, soft rime and hoarfrost. Icing on lines has many hazards, such as ice dancing on conductors or the detachment of a certain section of ice causing conductors to jump. These two situations are likely to cause impact loads. Impact loads are like sudden braking, collisions, and blows that occur in real life. They have a short action time and drastic load changes, which can cause serious damage to the line. In addition, if the insulator strings of the transmission line are covered with too much ice or bridged by ice, the insulation performance will be reduced, which will also cause line failures.

[0003] At present, mechanical deicing solutions still occupy a certain dominant position in the deicing operation of power lines. The common mechanical deicing solutions are: First, the solution that requires human traction (the equipment cannot move autonomously along the wire), such as deicing using long insulating rods, moisture-proof insulating ropes, pulley-mounted deicers and other tools, as well as short-bar operations of insulating boom vehicles to remove ice, and vibration deicing of blank bombs. This traditional technical method is relatively backward and has many obvious disadvantages, including: it cannot continuously cross poles, the applicable scenes are limited, the operation requires precision, it is greatly restricted by the terrain, the vehicle moves frequently, the efficiency and safety risks are high (electric shock, falling, etc.), the efficiency is low, the wires and insulators may be damaged, it is not suitable for the situation where the ice is more serious, and the phase change operation requires the re-hanging of the insulating rope, etc. Second, various robot devices that can walk and de-ice autonomously along the wires. At present, there are mainly three solutions: installing the deicing robot on the wire through manual tower hanging, drone hoisting, and drone / insulating rod + traction rope. The personnel control it through the remote control on the ground, and the robot can move along the wire to de-ice in the first gear line. The main de-icing methods include vibration, rotary blade stripping, sharp object chiseling, crushing ice, asymmetric breaking force ice crushing, etc. The current disadvantage is that without modifying the tower, the gear shifting and phase changing operations require re-mounting the machine.

[0004] At the same time, with the maturity and promotion of technology, the deicing technology of power lines based on drones has entered the implementation and application stage. Within the power grid companies, for example, State Grid Sichuan Power Transmission and Transformation Company, State Grid Hubei Electric Power Company and other units have adopted carrier drones for deicing of lines in many places, and deployed drones for autonomous inspections in key areas such as mountainous areas, lake areas, and forest areas.

[0005] However, the drone deicing technology currently introduced by power grid companies still has many shortcomings. For example, the deicing effect is not long enough (mainly ice melting, such as some drone deicing devices, which use heating methods to melt the ice layer, and the water formed after the ice melts will adhere to the surface of the line to re-form ice, resulting in poor deicing effect), high safety risks (electric shock, falling, etc.), low efficiency, possible damage to wires and insulators, etc.

[0006] However, from the technical perspective, the main problem is that the drone technology currently used for power grid de-icing is relatively rudimentary, with low levels of data and intelligence. The control of drones is more complicated than that of general ground robots, and the accuracy of operation is difficult to guarantee. The technical requirements for operators are relatively high, etc. This is seriously inconsistent with the technical development status and requirements of the State Grid for the intelligent and information construction of power grids. Therefore, the development and construction of corresponding intelligent control systems is an important technical development direction for many power grid departments. Based on the above-mentioned development status and technical deficiencies of drone de-icing technology, the technical team of the present invention, based on the research and development project of the power grid company, and in conjunction with the technical resources of multiple experts, carried out special technical development, based on the construction of a deep data control model to improve the data and intelligent control level of drone de-icing operations. Summary of the invention

[0007] The technical problem to be solved by the present invention is to overcome the above-mentioned deficiencies of the prior art and provide a data-driven multi-index digitized control model for transmission line icing and de-icing and its impact vibration data model, and also include its data execution process and method; the above-mentioned digitized control model is also suitable for carrying out icing and de-icing operations on power lines in a control system embedded in an unmanned aerial vehicle device.

[0008] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows.

[0009] A UAV power transmission line deicing device, which uses a radio remote control device and controls the UAV to carry a load based on a self-contained program control module, controls the UAV to move quickly to drive the mounted impact mass rod to impact the ice-covered line with the impact force consistent with the calculation result of the embedded data representation model to perform deicing operations on the ice-covered power transmission line; the radio remote control device optimizes the flight algorithm based on the self-contained program control module to control the data source to perform completely or intermittently automated UAV deicing operations.

[0010] As a preferred technical solution of the present invention, the impact mass rod carried by the drone for colliding with the power transmission line to break the ice layer and cause the line to vibrate is an insulating ring rod.

[0011] As a preferred technical solution of the present invention, the digitized control system is constructed as the dominant control system of the program control module of the UAV power transmission line icing and de-icing device; it manipulates the UAV to carry a load, controls the UAV to move quickly to drive the mounted insulating link rod to hit the ice-covered line with an impact force that meets the calculation results of the embedded collision detection quadtree data model, and performs de-icing operations on the transmission line.

[0012] As a preferred technical solution of the present invention, the digitized control system is also compatible with the simultaneous optimization of the flight algorithm control data source to perform fully or intermittently automated UAV de-icing operations, and determines the impact force of the insulating ring rod based on the transmission line parameters, icing parameters and damping effects, minimizing the number and period of intermittent human intervention.

[0013] As a preferred technical solution of the present invention, the physical path framework of data modeling in the digitized control system is that the UAV obtains instantaneous negative acceleration in front of the ice-covered cable and collides with the insulating link rod based on the inertia.

[0014] As a preferred technical solution of the present invention, based on the above-mentioned physical path framework, the data signal control path of the digitized control system is constructed as follows: on the basis of the discrete signal control architecture, the proportion paradigm, differentiation paradigm, and integration paradigm are embedded as needed to perform signal control, and data is collected according to the PID algorithm before takeoff, and parameter detection and adjustment are performed by superimposing the input operation results.

[0015] As a preferred technical solution of the present invention, based on the above-mentioned physical path framework, the initialization path of the data coordinates is: modeling the energy of the system through the Lagrangian method and constructing a data program based on the translation and rotation parameters of the six-degree-of-freedom system, and generalized coordinate vectors are used in data representation; the data output direction of the data program is: initiating speed braking in front of the transmission cable to make the mass rod hit the line.

[0016] As a preferred technical solution of the present invention, the insulating link rod hits the ice-covered line with an impact force that conforms to the calculation result of the embedded collision detection quadtree data characterization model, wherein the core, the data characterization model of the impact force that conforms to the calculation result of the embedded collision detection quadtree data model adopts a discretization model by integral thinking, and its force estimation algorithm uses Taylor series expansion to perform data characterization evolution and further iterative fitting on the multi-index data fitting characterization configuration, and its data steps include:

[0017] S1: Dimensional construction: ① The length of the transmission line is L; ② The radiation range of each impact of the insulating rod of the drone carrying the load on the transmission line is l; ③ L / 2l is the ordered data capacity of the number of hits; ④ The mass of the insulating rod is M1; ⑤ The mass of the transmission line is M2; ⑥ The mass of the drone is M3; ⑦ The dimension of the drone acceleration is LT-2;

[0018] S2: Further matching, supplementing and standardizing the elements of the iterative fitting model: UAV acceleration a, transmission line amplitude after collision ω, damping point is ω0, every i unit length is ωi, i = 1, 2, 3, ...

[0019] S3: Collision F0 = M1a. Due to the completely inelastic collision, there is a strong dissipation, and the actual effective force is named F;

[0020] S4: Further loading the damping effect, the amplitude of the transmission line is approximately fitted into a trigonometric function wave diagram, and the restoring force at each point of the cable after the transmission line is hit by the insulating ring rod is calculated by Taylor series expansion, and the amplitude function is f(x);

[0021] S5: Data cutting basic process: The restoring force F is cut as the difference between the maximum restoring force of each unit cell of the transmission line and the restoring force of the basic paradigm model. According to Hooke's law, the "subset A1" cut of the restoring force F = kx = f(x)-f(x0); The data evolution cutting process is obtained by iterating the data basic cutting step by step. The next level of cutting process is based on the "subset A1" cutting process. The database obtained by this level of cutting process is constructed into ordered discrete data corresponding to the discrete data group being cut and named "subset A2"; Based on Tai The valuable data selection of the Le series expansion analysis tool, the ordered discrete data group cut out by "subset A2" is characterized as f(x)-f(x0)=k1Δ1+k2Δ2+k3Δ3+…, i=1,2,3,…ki is the reciprocal of the elastic coefficient of the unit length line under the influence of factors such as gravity and wire tension; Δi is the amplitude of the i-th unit length of the transmission line under the influence of different restoring forces due to the influence of damping from the element position (the element position is the collision position between the insulating rod and the transmission line), which is obtained by F dissipation;

[0022] S6: The data set architecture is further improved: the minimum amplitude of the initial dynamic data element even if it falls on ice is represented as Δ0, and the initial dynamic data element corresponds to the corresponding position x1 on the transmission line with the element position as the reference distance l1 from the element position, where the maximum restoring force is f(x1);

[0023] S7: At the data output level, the preliminary discretized data fitting characterization configuration is converted into a multi-index data fitting characterization configuration F=M1a=∑kiΔi, i=1,2,3,…, F'=(M1+M2)a. According to the cable measurement dimension L and the above-mentioned various variable parameters, the above-mentioned real-time data parameters and operation algorithms are determined to manipulate the size of the drone and the insulating link rod LT-2 to achieve the effect of small impact and efficient deicing.

[0024] As a preferred technical solution of the present invention, considering the transmission line parameters, icing parameters and damping effects, the A damping effect in the data model also includes ξ1 wind resistance, ξ2 weight, ξ3 insulation skin, ξ4 wire tension, ξ5 ice layer tension, ξ6 gravity, ξ7 transmission line position, ξ8 fog and other meteorological parameters, ξ9 magnetic field data parameters; the B transmission line parameters and icing parameters include conductor vertical load ξ10, conductor wind pressure load ξ11, the theoretical ξ12 of the conductor's comprehensive load, and ice thickness ξ13, ξ1-11 can be recorded in real time by the visual multimedia monitoring equipment carried by the drone and imported into the device embedded data control system; then the empirical model is used to fit the random variable sequence ξ1, ξ2, ξ3, ξ4, ξ5, ξ6, ξ7, ξ8, ξ9, ξ10, ξ11, ξ12, ξ13 to the distribution column that meets the requirements and import it into the data control system;

[0025] If the fitted variances of the above random variables ξi are all bounded after measurement and conform to the data paradigm of the law of large numbers It can be judged that the operation can be performed and a n As the exported data, it is imported into the ki related database involved in step S5 of claim 6, that is, a multi-index parameter dynamic coefficient library is established in a matrix mode, and the application operation data ki is adjusted through the scheduling prediction and scheduling prediction data correction affected by the above data parameters.

[0026] As a preferred technical solution of the present invention, the method also includes the following data model: in claim 6, a discretized data model constructed by Taylor series expansion calculation is adopted, and further standardized fitting data operations are performed through continuous calculus data paths to construct a continuous data model to tightly couple the data, and the de-icing device operation is made accurate and efficient by improving the data system.

[0027] As a preferred technical solution of the present invention, the wire position before the first deicing operation is the reference point x10, at which time F0 = 0N, and the successive operations are x 2 0,x 3 0,…; real-time correction parameters before each operation.

[0028] The present invention also includes the use of the above-mentioned digital control system, which can be used alone or mounted on a universal drone control platform for the drone to carry out deicing operations on power transmission lines with a load.

[0029] The beneficial effects of adopting the above technical solution are:

[0030] 1. The present invention is an innovation in the field of transmission line deicing technology. The data method and data control system provided by the present invention have wide applicability, that is, the present invention can provide data information and parameter references for many deicing devices and deicing methods that use transmission line vibration or drones to de-ice during the process. The present invention is not only highly innovative, but also has development potential.

[0031] 2. The present invention uses visual detection equipment combined with aerodynamic calculation data to patrol and inspect the transmission line through unmanned aerial vehicles, reducing the impact of adverse factors such as extreme weather, high altitude terrain, low temperature operation, terrain influence, etc. on the inspection operation. The optimization scheme adopts large-scale load-bearing unmanned aerial vehicles and small multi-rotor unmanned aerial vehicles in conjunction with the deicing method, that is, the small unmanned aerial vehicle is equipped with a visual multi-angle monitoring and detection device to monitor the data, provide observation angles and refined patrols, and the large unmanned aerial vehicle is responsible for hanging rod impact and performing ice collision tasks, which improves the operation accuracy and detection sensitivity, makes the deicing operation more powerful, and improves the efficiency and quality of the deicing operation. Compared with traditional deicing methods, it can improve the timeliness and effectiveness of deicing, save time, manpower, material resources, electricity, nature and other valuable resources, effectively curb the growth rate of ice in the early stage of ice, and ensure the safety of transmission lines. Compared with traditional deicing methods, it can improve the timeliness and effectiveness of deicing, save time, manpower, material resources, electricity, nature and other valuable resources, effectively curb the growth rate of ice in the early stage of ice, and ensure the safety of transmission lines. At the same time, the non-contact operation of de-icing the transmission lines by manpower has greatly reduced the difficulty and danger of de-icing, and protected the lives of power workers.

[0032] 3. The present invention is based on the construction of multivariable linear data process and its data system, combined with vibration data model, taking into account the real-time change of multi-index characterization parameters, taking into account data regularity, variability, relative invariance, etc., and fitting a relatively superior data characterization framework from the two aspects of discretization and continuity through gradual iterative evolution and supplementary construction of data. Compared with the single index fitting characterization conclusion of the discrete data index library of data parameters such as time, example, impulse, etc., its Taylor series expansion characterization fitting result based on mathematical analysis can improve data estimation accuracy, reduce data offset angle, and improve operation accuracy through the linear extension of the data model.

[0033] 4. The data matrix and data system are formed by real-time updated data collection points. The coefficient parameter offset angle is adjusted based on the empirical data and combined with the real-time parameter optimization to adjust to more appropriate operation data. Based on this, a reasonable ki value is output and each Δi value is determined. After standardized data processing, the operation data is output by the data system, and the purpose of improving operation effectiveness is achieved in the process.

[0034] For more detailed technical effects of the present invention, please refer to the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Attached Figure 1 It is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0036] The following examples describe the present invention in detail. In the description of the following examples, specific details such as specific system structures, technologies, etc. are proposed for illustration rather than limitation, so as to provide a thorough understanding of the present application embodiments. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed description of well-known systems, devices, circuits and methods is omitted to prevent unnecessary details from hindering the description of the present application.

[0037] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or their collections. It should also be understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0038] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0039] In addition, in the description of the present application specification and the attached claims, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. The reference to "one embodiment" or "some embodiments" described in the present application specification means that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in the different parts of this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0040] Example 1

[0041] An impact vibration data model and method for a multi-index digitized dispatching and operating system for deicing of unmanned aerial vehicle transmission lines includes the following data processes: a. The radio remote control device controls the data source based on a human or vehicle-mounted computer through an optimized flight algorithm such as Kalman filtering and PID control to perform completely or intermittent autonomous operation. The impact force is selected according to the transmission line parameters and icing parameters. b. The device uses an unmanned aircraft drone controlled by a radio remote control device and a self-contained program control device to carry a load. The control device moves quickly to drive the mounted impact mass rod to impact the ice-covered line with an impact force that meets the calculation results of the collision detection quadtree and other data representation models.

[0042] For a, the data parameters must be collected accurately and at various collection angles. This is a practical application of existing data technology. The algorithm can be continuously optimized based on actual conditions to improve the application effect.

[0043] For b, the data parameters are required to be reasonably fitted, the estimated data deviation angle is as small as possible, the actual deviation data can be dynamically adjusted, and the operation and application can be flexibly combined with the actual situation. The core advantage lies in the discretization nature of the Taylor series characterization fitting and the quasi-continuity in the context of calculus: the first i units are more affected by the proximity to the vibration unit position, so they occupy a larger proportion of the distance. In the actual operation, the actual value of i can be selected according to the ice coverage (ice thickness, adhesion strength, etc.), which is based on the multidimensional linear characterization parameters and image conditions formed by data fitting.

[0044] Example 2

[0045] In a, the interactive database processed by the interactive discrete data module is grouped by cloud data operation or manual input method, based on the data processing of the interactive database group. The collision detection calculation results are controlled according to discrete signals. On the basis of the above physical path framework, the data signal control path of the digital control system is constructed as follows: on the basis of the discrete signal control architecture, the proportion paradigm, differentiation paradigm, and integration paradigm are embedded as needed for signal control. Before takeoff, data is collected according to the PID algorithm and parameter detection and adjustment are performed by superimposing the input operation results.

[0046] Example 3

[0047] When the actual conditions are complicated and one device is not conducive to completing the task, large-scale load-bearing UAVs and small multi-rotor UAVs can be used in conjunction with de-icing methods. Small UAVs equipped with visual multi-angle monitoring and detection equipment are responsible for monitoring data, providing observation perspectives and detailed patrols, while large UAVs are responsible for hanging rod impact and performing ice-collision tasks.

[0048] Example 4

[0049] In b, a new data model was constructed and put into use after joint development by multiple operating departments and data experts: the data representation model of the impact force that conforms to the calculation results of the collision detection quadtree and other data representation models adopts a discretized model from the integral thinking, and its force estimation method further iterates and fits the data representation evolution by Taylor series expansion of the multi-index data fitting representation configuration: data cutting basic process: the restoring force F cut is the difference between the maximum restoring force at each unit of the transmission line and the restoring force of the basic paradigm model. According to Hooke's law, the "subset A" cut of the restoring force F = kx = f(x)-f(x0). The data evolution cutting process is obtained by iterating the data basic cutting step by step. The next level of cutting process is based on the "subset A" cutting process. The database obtained by this level of cutting process is constructed into ordered discrete data corresponding to the discrete data group being cut and named "subset B". Based on the selection of valuable data by Taylor series expansion analysis tools, the ordered discrete data group cut out by "Subset B" is characterized as f(x)-f(x0)=k1Δ1+k2Δ2+k3Δ3+…, i=1,2,3,…ki is the reciprocal of the elastic coefficient of the unit length line under the influence of gravity, wire tension and other factors. Δi is the amplitude of the i-th unit length of the transmission line under the influence of different restoring forces due to the influence of damping from the element position (the element position is the collision position between the insulating rod and the transmission line), which is obtained by F dissipation. The data group architecture is further improved: the minimum amplitude of the initial dynamic data element even if it falls due to ice is characterized as Δ0, and the initial dynamic data element corresponds to the corresponding position x1 on the transmission line with the element position as the reference distance l1 from the element position measurement, where the maximum restoring force is f(x1). Then, the preliminary discretized data fitting characterization configuration is converted into a multi-index data fitting characterization configuration F=M1a=∑kiΔi, i=1,2,3,…, F'=(M1+M2)a. According to the cable measurement dimension L and the above-mentioned damping and other influencing factors, the above-mentioned real-time data parameters and operation algorithms are determined to manipulate the size of the drone and the insulating link rod LT-2 to achieve the effect of small impact and efficient deicing.

[0050] The A damping influence in the data model also includes ξ1 wind resistance, ξ2 weight, ξ3 insulation skin, ξ4 wire tension, ξ5 ice layer tension, ξ6 gravity, ξ7 transmission line location, ξ8 fog and other meteorological parameters, ξ9 magnetic field data parameters; B transmission line parameters and icing parameters include conductor vertical load ξ10, conductor wind pressure load ξ11, theoretical value of conductor comprehensive load ξ12, ice thickness ξ13, ξ1-11 can be recorded in real time by the visual multimedia monitoring equipment carried by the drone and imported into the device embedded digital control system; then the empirical model is used to fit the random variable sequence ξ1, ξ2, ξ3, ξ4, ξ5, ξ6, ξ7, ξ8, ξ9, ξ10, ξ11, ξ12, ξ13 to the distribution column that meets the requirements and import it into the digital control system;

[0051] If the fitted variances of the above random variables ξi are all bounded after measurement and conform to the data paradigm of the law of large numbers It can be judged that the operation can be performed and a n As the exported data, it is imported into the ki related database involved in step S5 of claim 6, that is, a multi-index parameter dynamic coefficient library is established in a matrix mode, and the application operation data ki is adjusted through the scheduling prediction and scheduling prediction data correction affected by the above data parameters.

[0052] Example 5

[0053] Furthermore, data parameter correction can generally be achieved through visual inspection equipment optimization, coefficient refinement selection, empirical parameter addition or other data means to strive to improve the accuracy and effectiveness of invariants and achieve optimal adjustment of real-time operation data.

[0054] In the above embodiments, the description of each embodiment has its own emphasis. For the part that is not described or recorded in detail in a certain embodiment, please refer to the relevant description of other embodiments. In each embodiment, the hardware implementation of the technology can directly adopt existing intelligent devices, including but not limited to drones, remote sensing equipment, communication equipment, handheld stand-alone machines, visualization equipment, insulation equipment, vehicle-mounted computers, etc. Its operating device preferably adopts an operating lever, its data storage and calculation module adopts existing memory, calculator, controller, its internal communication module adopts existing communication ports and protocols, and its remote communication adopts existing GPRS network, World Wide Internet, etc.

[0055] Example 6

[0056] The mass rod carried by the drone for colliding with the power transmission line to break the ice and make the line vibrate is an insulating gram rod. The existing practical mass data parameter is 23kg. In practice, it needs to be adjusted in real time based on the data parameters in the database established in step b.

[0057] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0058] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. UAV power transmission line deicing embedded data control system, characterized by: The digital control system is constructed as the dominant control system of the built-in program control module of the UAV power transmission line deicing device; it controls the UAV to carry the load and controls the UAV to move quickly, thereby driving the insulating link rod mounted on the UAV to hit the ice-covered line with the impact force that meets the collision detection quadtree data model, and performs deicing operations on the power transmission line; In the data-based control system, three data paths are provided: a physical path of data modeling, a data signal control path, and an initialization path of data coordinates; and the data signal control path and the initialization path of data coordinates are based on the physical path of data modeling; The physical path of data modeling is as follows: the UAV obtains instantaneous negative acceleration in front of the ice-covered cable and impacts it based on the inertia of the insulating link rod; The data signal control path of the digital control system is constructed as follows: based on the discrete signal control architecture, the proportion paradigm, the differentiation paradigm, and the integration paradigm are embedded to perform signal control, and before takeoff, data is collected according to the PID algorithm and parameter detection and adjustment are performed by superimposing the input operation results; Among them, the initialization path of the data coordinates is: modeling the energy of the system through the Lagrangian method and constructing a data program based on the translation and rotation parameters of the six-degree-of-freedom system, and using generalized coordinate vectors for data representation; the data output direction of the data program is: initiating speed braking in front of the transmission cable to make the insulating rod hit the line.

2. The embedded digital control system for deicing of UAV power transmission lines according to claim 1 is characterized by: The insulating link rod hits the ice-covered line with an impact force that conforms to the collision detection quadtree data characterization model, wherein the basic collision detection quadtree data model is improved into a discretization model, and its force estimation algorithm characterizes multi-index data fitting through Taylor series expansion, and performs data characterization evolution and iterative fitting; specifically, its data steps include: S1: Dimensional construction, including: ① The length of the transmission line L; ② The single radiation range of the insulating ring rod carrying the load of the drone impacting the transmission line is l; ③ L / 2l is the ordered data capacity of the number of hits; ④ The mass of the insulating ring rod M1; ⑤ The mass of the transmission line M2; ⑥ The mass of the drone M3; ⑦ The dimension of the drone acceleration LT -2 ; S2: Further matching, supplementation and specification of dimensions: UAV acceleration a, transmission line amplitude ω after collision, and the amplitude is ω0 at the damping point, and then every i unit length is ω i , i=1,2,3,… S3: The collision formula is F0=M1a. Due to the strong dissipation of completely inelastic collision, the actual effective force is named F; S4: Loading damping effect, the transmission line amplitude is fitted into a trigonometric function wave diagram, and the restoring force at each point of the cable after the transmission line is hit by the insulating ring rod is calculated by Taylor series expansion, and the amplitude function is recorded as f(x); S5： S5-1. Data cutting basic process: The restoring force F is cut as the difference between the maximum restoring force at each unit cell of the transmission line and the restoring force f(x0) of the basic collision detection quadtree data model. The "subset A1" of the restoring force can be obtained by Hooke's law, and its data representation is cut F=kx=f(x)-f(x0); S5-2. Data evolution cutting process: This process is obtained by iterating the basic data cutting process. The data evolution cutting process is established on the basic data cutting process. The database obtained by the data evolution cutting process is constructed into ordered discrete data corresponding to the discrete data group being cut, and is named "subset A2"; based on the valuable data selection of the Taylor series expansion analysis tool, the ordered discrete data group cut out by "subset A2" is characterized by F=f(x)-f(x0)=k1Δ1+k2Δ2+k3Δ3+…, i=1,2,3,…ki is the reciprocal of the elastic coefficient of the unit length line under the influence of gravity and wire tension factors; Δi is the amplitude of the i-th unit length of the transmission line from the element position, and its size is affected by damping and dissipation forces; among them, the element position is the collision position of the insulating ring rod and the transmission line.

3. The embedded digital control system for deicing of UAV power transmission lines according to claim 2 is characterized by: The digital control system is also compatible with optimizing the flight algorithm to control the data source to perform fully or intermittently automated drone de-icing operations, determining the impact force of the insulating rod based on the transmission line parameters, icing parameters and damping effects, and minimizing the number and duration of intermittent human intervention.

4. The embedded digital control system for deicing of UAV power transmission lines according to claim 3 is characterized by: The damping influence includes ξ1 wind resistance, ξ2 weight, ξ3 insulation skin, ξ4 wire tension, ξ5 ice layer tension, ξ6 gravity, ξ7 transmission line position, ξ8 fog meteorological parameter conditions, ξ9 magnetic field data parameters; the transmission line parameters and icing parameters include conductor vertical load ξ10, conductor wind pressure load ξ11, theoretical value of conductor comprehensive load ξ12, ice thickness ξ13; ξ1-ξ13 can be recorded in real time by the visual multimedia monitoring equipment carried by the drone and imported into the digital control system; then the empirical model is used to fit the random variable sequence ξ1, ξ2, ξ3, ξ4, ξ5, ξ6, ξ7, ξ8, ξ9, ξ10, ξ11, ξ12, ξ13 to the distribution column that meets the requirements and import it into the digital control system; If the fitted variances of the above random variables ξi are all bounded after measurement and conform to the data paradigm of the law of large numbers , it can be judged that the operation can be implemented and a n The exported data is imported into the ki-related database involved in step S5 of claim 2, and a multi-index parameter dynamic coefficient library is established in a matrix mode.

5. The embedded digital control system for deicing of UAV power transmission lines according to claim 4 is characterized by: The position of the wires before the first deicing operation is recorded as the reference point x¹0, at which time F0=0N, and the successive operations are x²0, x³0,…; the parameters are corrected in real time before each operation.

6. The use of the data control system according to any one of claims 1 to 5, characterized in that: It can be used alone or mounted on a general UAV control platform to carry out de-icing operations on power transmission lines by mounting payloads on the UAV.

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