Unmanned aerial vehicle power transmission line tracking and positioning method based on electric field sensor array

Abstract

The invention relates to the technical field of unmanned aerial vehicle navigation and positioning, in particular to an unmanned aerial vehicle power transmission line tracking and positioning method based on an electric field sensor array. According to the method, a circular array composed of five electric field sensors is arranged on the unmanned aerial vehicle, four sensors are evenly distributed on the edge, and one sensor is located in the center to form a symmetrical structure. And acquiring the amplitude, direction, gradient and time-varying characteristic data of the electric field in real time, and inputting the processed data into the ranging and positioning model. The model deduces a power transmission line electric field change rule based on a point charge field intensity formula, and calculates a measurement relation between sensors in combination with a cosine law to realize accurate calculation of a relative position, an elevation angle and a course angle between the unmanned aerial vehicle and the power transmission line. And meanwhile, the system has real-time monitoring and abnormity alarm functions, and when the electric field is detected to be abnormal, the system automatically adjusts the flight state and transmits abnormal data to a monitoring center. According to the method, the defect that traditional visual navigation is greatly influenced by the environment is overcome, and the all-weather autonomous tracking and positioning capability is realized.

Description

Technical Field

[0001] The invention relates to the technical field of unmanned aerial vehicle navigation and positioning, and in particular to a method for tracking and positioning an unmanned aerial vehicle power transmission line based on an electric field sensor array. Background Art

[0002] As the scale of power systems continues to expand, automatic inspection of transmission lines has become a key technology to improve the efficiency and reliability of power equipment operation and maintenance. Traditional manual inspection methods are not only inefficient and costly, but also pose safety risks. In order to improve inspection efficiency, automatic inspection methods for transmission lines based on drones have received widespread attention in recent years. However, existing drone inspection methods usually rely on visual sensors or LiDAR sensors, which are limited by environmental conditions (such as light, weather, obstacles, etc.) and have poor accuracy in complex environments.

[0003] As a characteristic signal of the transmission line, the electric field signal has strong stability and anti-interference ability, and is suitable for precise positioning. In the prior art, the positioning method based on electric field sensors is mostly used for static measurement, and there is a lack of research on the real-time positioning and tracking capabilities of dynamic drones during cruising. The existing drone positioning method based on electric field sensor arrays still has problems of insufficient accuracy and poor real-time performance when facing complex transmission line layouts, long-distance tracking and high-precision positioning. Therefore, how to improve the precise tracking and positioning accuracy of drones on transmission lines through electric field sensor arrays has become one of the technical difficulties in automatic inspection of power systems. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to improve the precise tracking and positioning accuracy of the UAV on the power transmission line through the electric field sensor array.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a UAV transmission line tracking and positioning method based on an electric field sensor array, which includes acquiring electric field strength data around the transmission line, and performing first electric field data processing according to the data measured by the electric field sensor array;

[0008] inputting the processed electric field data into an electric field sensor array ranging and positioning model;

[0009] Tracking and positioning between the UAV and the power transmission line are performed based on the output of the electric field sensor array ranging and positioning model.

[0010] As a preferred solution of the UAV power transmission line tracking and positioning method based on electric field sensor array described in the present invention, the electric field strength data is obtained through an electric field sensor array composed of 5 sensors, 4 of which are evenly distributed at the edge of the circular array, and 1 sensor is located in the center of the array to form a symmetrical structure.

[0011] As a preferred solution of the UAV power transmission line tracking and positioning method based on electric field sensor array described in the present invention, the electric field sensor array ranging and positioning model includes: taking the vertical distance between any point and the transmission line as input; taking the electric field change rule of the transmission line as the calculation basis; and obtaining the relative position relationship between any point and the transmission line.

[0012] As a preferred solution of the UAV power transmission line tracking and positioning method based on electric field sensor array described in the present invention, the electric field change rules of the transmission line at least include: deriving the electric field change rules of the transmission line in the x and y directions based on the point charge field strength formula; deriving the field strength at any point outside the transmission line based on the transmission line change formula in the x and y directions.

[0013] As a preferred solution of the UAV power transmission line tracking and positioning method based on the electric field sensor array described in the present invention, the tracking and positioning between the UAV and the power transmission line includes: obtaining the distance data between each sensor in the circular sensor array and the power transmission line; obtaining the measurement relationship between the array center sensor and the sensors on both sides thereof by the cosine theorem; and calculating the flight distance and elevation angle of the UAV based on the measurement relationship.

[0014] As a preferred solution of the UAV power transmission line tracking and positioning method based on electric field sensor array described in the present invention, when the distance data of any two sensors are obtained, the distance integration is performed through the following steps: obtaining the distance data of the two sensors; deriving the relative distance between each sensor and the transmission line based on the distance data; and determining the overall position of the sensor array.

[0015] As a preferred solution of the UAV power transmission line tracking and positioning method based on the electric field sensor array of the present invention, the determination and correction of the UAV heading angle includes: when the sensors on both sides of the UAV are parallel to the power transmission line, calculating the difference in electric field strength;

[0016] The heading angle is determined based on the difference in electric field strength; the heading correction is achieved by adjusting the heading angle.

[0017] As a preferred solution of the UAV power transmission line tracking and positioning method based on electric field sensor array described in the present invention, the output results of the electric field sensor array ranging and positioning model include: the relative distance between the UAV and the power transmission line; the elevation angle of the UAV relative to the power transmission line; and the real-time heading angle of the UAV.

[0018] As a preferred solution of the UAV power transmission line tracking and positioning method based on the electric field sensor array of the present invention, the tracking and positioning between the UAV and the power transmission line according to the output of the electric field sensor array ranging and positioning model also includes:

[0019] Monitor the electric field strength data of each sensor in real time; trigger the alarm mechanism when abnormal electric field strength is detected; adjust the flight status of the drone according to the abnormal situation.

[0020] As a preferred solution of the UAV power transmission line tracking and positioning method based on the electric field sensor array described in the present invention, the method also includes: judging the operating status of the power transmission line based on the change of electric field strength; recording abnormal data when an abnormality occurs in the power transmission line; and transmitting the abnormal data to the monitoring center in real time.

[0021] In a second aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the UAV power transmission line tracking and positioning method based on the electric field sensor array as described in the first aspect of the present invention are implemented.

[0022] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the method for tracking and positioning a UAV power transmission line based on an electric field sensor array as described in the first aspect of the present invention are implemented.

[0023] The beneficial effects of the present invention are as follows: the present invention realizes all-round perception of electric field strength through a symmetrical structural design in which four sensors are evenly arranged at the edge of a circular array and one sensor is set at the center, thereby overcoming the defect that traditional single-point measurement is susceptible to interference and improving the reliability and integrity of measurement data. The structural design also enables the system to have spatial position resolution capability, laying the foundation for subsequent precise positioning.

[0024] By simultaneously collecting multi-dimensional data such as electric field amplitude, direction, gradient and time-varying characteristics, a comprehensive characterization of the electric field distribution around the transmission line is achieved, avoiding the problem of information loss caused by traditional methods that rely only on a single feature. This multi-dimensional data fusion strategy improves the adaptability of the system in complex environments and enhances the reliability of positioning results.

[0025] By taking the vertical distance between any point and the transmission line as input and combining the electric field variation rules as the calculation basis, a mapping relationship between electric field strength and spatial position is established. This model innovatively combines theoretical analysis with actual measurement, breaking through the limitations of traditional visual navigation due to environmental constraints and achieving accurate positioning capabilities all day and all night.

[0026] By introducing the cosine theorem to calculate the measurement relationship between the central sensor and the sensors on both sides, a position calculation method based on geometric constraints was established, which effectively solved the problem of insufficient position calculation accuracy in traditional methods and improved the positioning accuracy of the system.

[0027] By analyzing the difference in electric field strength between the sensors on both sides, real-time determination and automatic correction of the heading angle are achieved, overcoming the problem of easy deviation of the heading in traditional navigation methods and ensuring that the UAV always maintains the correct tracking posture.

[0028] By real-time monitoring of electric field strength data, a complete abnormality detection and processing process has been established, which enables real-time monitoring of the operating status of the transmission line and improves the safety and reliability of the system. When an abnormality occurs, the system can adjust the flight status in time and alarm the monitoring center, effectively preventing the occurrence of safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 A flow chart of a UAV transmission line tracking and positioning method based on an electric field sensor array;

[0031] Figure 2 A computer device diagram for a UAV power transmission line tracking and positioning method based on an electric field sensor array;

[0032] Figure 3 A schematic diagram of the UAV electric field sensor design for the UAV power transmission line tracking and positioning method based on an electric field sensor array;

[0033] Figure 4 This is an experimental diagram of the UAV power transmission line tracking and positioning method based on electric field sensor array. DETAILED DESCRIPTION

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0035] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0036] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0037] Example 1

[0038] Reference Figure 1-2 , which is the first embodiment of the present invention, and provides a UAV power transmission line tracking and positioning method based on an electric field sensor array, comprising:

[0039] S100: Acquire electric field strength data around a transmission line, and perform first electric field data processing according to data measured by an electric field sensor array;

[0040] S101: Electric field strength data is obtained through an electric field sensor array consisting of 5 sensors, where 4 sensors are evenly distributed at the edges of the circular array and 1 sensor is located at the center of the array to form a symmetrical structure.

[0041] In the embodiment of the present application, the electric field strength data includes: electric field amplitude data, electric field direction data, electric field gradient data and electric field time-varying data. The electric field strength data is all electric field measurement data acquired by the electric field sensor array.

[0042] Specifically, the electric field amplitude data may be a voltage signal converted by a sampling capacitor, the electric field direction data may be direction information obtained by calculating the difference between different sensor signals, the electric field gradient data may be the rate of change of the electric field calculated using adjacent sensor signals, and the electric field time-varying data may be sampling data that records changes in electric field strength over time.

[0043] In an optional embodiment, the electric field amplitude data, electric field direction data, electric field gradient data and electric field time-varying data can be any combination of data collected by the electric field sensor array. For example, when the electric field amplitude data is a sensor sampling capacitance signal, the electric field time-varying data can be a time series record of the signal.

[0044] In an optional embodiment, the electric field amplitude data, electric field direction data, electric field gradient data, and electric field time-varying data can also increase or decrease other electric field characteristic data according to different target effects. For example, when more refined detection is required, electric field harmonic data (i.e., the fifth type of electric field data) can be added to capture the spectral characteristics of the electric field, thereby further improving the accuracy and comprehensiveness of positioning. In addition, considering the impact of environmental conditions on measurement quality, an adaptive signal processing algorithm can also be introduced to dynamically adjust the collected electric field data to ensure that high-quality electric field data can be obtained under various environmental conditions.

[0045] In an optional embodiment, if the time-varying characteristics do not need to be considered, the electric field time-varying data can be omitted, thereby reducing the workload of data collection and processing. However, in this application, in order to ensure the comprehensiveness of the detection, such data is still retained.

[0046] It should be noted that the acquisition of the above electric field data can fully reflect the electric field distribution characteristics around the transmission line, including but not limited to the electric field strength, direction, gradient and time-varying characteristics, so as to ensure the accuracy and comprehensiveness of the tracking and positioning results. At the same time, by introducing multiple measurement dimensions and data features, the advantages of various types of electric field information can be fully utilized, complement each other, and improve the efficiency and accuracy of positioning. In addition, according to the needs of different target effects, the type and quantity of data can be flexibly adjusted to meet the needs of actual tracking and positioning work. This multi-dimensional data fusion strategy not only improves the flexibility and adaptability of the system, but also provides rich data resources for subsequent intelligent analysis.

[0047] S200: inputting the processed electric field data into an electric field sensor array ranging and positioning model;

[0048] S201: The electric field sensor array ranging and positioning model includes: taking the vertical distance between any point and the transmission line as input; taking the electric field variation rule of the transmission line as the calculation basis; and obtaining the relative position relationship between any point and the transmission line.

[0049] In the embodiment of the present application, the electric field sensor array ranging and positioning model is implemented by the following steps:

[0050] The electric field variation rule of the first target transmission line is determined as the basic model, the distance relationship between nodes is regarded as a constraint condition, and the weight represents the credibility;

[0051] Set any measurement point as the calculation starting point, perform iterative calculations according to the rules, and add the calculation results to the positioning result set.

[0052] S202: The electric field variation rule of the transmission line at least includes: deriving the electric field variation rule of the transmission line in the x and y directions according to the point charge field strength formula; and deriving the field strength at any point outside the transmission line based on the transmission line variation formula in the x and y directions.

[0053] When the data of the electric field sensor array measurement point is acquired, it is determined whether the electric field amplitude data, electric field direction data, electric field gradient data and electric field time-varying data generated by the measurement point meet the preset requirements. If so, the measurement result is used for position calculation;

[0054] If not, the electric field amplitude data, electric field direction data, electric field gradient data and electric field time-varying data of the measuring point are acquired again.

[0055] Exemplarily, in an embodiment of the present application, electric field data from multiple test scenarios are collected, totaling about 1,000 sets of measurement data, to ensure that multiple operating conditions (such as different voltage levels, different weather conditions, etc.) are covered.

[0056] The collected data were calibrated and classified to generate a training set of 500 samples and a validation set of 100 samples. The first electric field data processing was performed to improve the quality of the data. The first feature extraction process was to analyze 300 sets of typical data, verify 200 sets of abnormal data, and correct 150 sets of interference data. The training set finally generated a total of 1,850 sets of complete records.

[0057] It should be noted that the use of the first feature extraction process can expand the original 1000 sets of data samples to 1850 sets of data samples. This feature analysis technology not only helps the system to better learn the various characteristics of the electric field distribution, but also improves the system's generalization ability in complex environments. During the processing, the system will be exposed to more complete electric field data, so that it can better identify the electric field distribution laws in different scenarios.

[0058] S300: Tracking and positioning between the UAV and the power transmission line according to the output of the electric field sensor array ranging and positioning model.

[0059] S301: Tracking and positioning between the UAV and the power transmission line includes: obtaining the distance data between each sensor in the circular sensor array and the power transmission line; obtaining the measurement relationship between the sensor at the center of the array and the sensors on both sides thereof by the cosine theorem; and calculating the flight distance and elevation angle of the UAV based on the measurement relationship.

[0060] In an optional embodiment, the execution order of the tracking and positioning algorithm is to select the results according to the measurement accuracy, and select the data with the highest accuracy from the measurement result set as the positioning result of the current position, so as to ensure that the system can track along the optimal path and improve the positioning efficiency. For example, if it is currently in the stable tracking stage, the system will give priority to the measurement data with the largest gradient to determine the relative position. Subsequently, it will continue to select and process the next set of optimal measurement data, and repeat this process until the entire tracking task is completed. Such an execution order not only ensures that the system has the optimal path during the tracking process, but also effectively reduces the consumption of computing resources, thereby improving the overall tracking efficiency. At the same time, by continuously collecting and analyzing the electric field data of each measurement point, the system can also more accurately establish an electric field distribution model, providing strong support for subsequent tracking and positioning.

[0061] In an optional embodiment, the execution order of the tracking and positioning algorithm can also be to select data according to weights, and the weights can be measurement weights designed by technicians or users, that is, the weights of target measurement points. For example, if certain measurement points have higher reference value due to their positional relationship, they can be given higher weights. When the system calculates the position, it will give priority to these high-weighted measurement points and process these data first. This weight design method can flexibly respond to different tracking needs. For example, some areas may require more precise positioning due to geographical location, environmental influences or human factors. In this way, the system can plan tracking strategies more intelligently, ensure that positioning tasks in important areas are given priority, and further improve the pertinence and efficiency of tracking.

[0062] S302: When the distance data of any two sensors are obtained, distance integration is performed through the following steps: obtaining the distance data of the two sensors; deducing the relative distance between each sensor and the transmission line based on the distance data; and determining the overall position of the sensor array.

[0063] In an optional embodiment, the ranging and positioning model can use the improved point charge field strength formula as the basic model, and can also be constructed using other mathematical models or algorithms, such as multipole expansion, finite element analysis, etc. However, no matter which method is selected to construct the model, the input of the model must be the processed electric field data, and the output must be the relative position parameter or an output result that can represent a similar relative position effect.

[0064] S303: Determining and correcting the heading angle of the UAV includes: calculating the difference in electric field strength when the sensors on both sides of the UAV are parallel to the power transmission line;

[0065] The heading angle is determined based on the difference in electric field strength; the heading correction is achieved by adjusting the heading angle.

[0066] S304: The output results of the electric field sensor array ranging and positioning model include: the relative distance between the UAV and the power transmission line; the elevation angle of the UAV relative to the power transmission line; and the real-time heading angle of the UAV.

[0067] It should be noted that the above steps can ensure that the system is not only accurately positioned during the tracking process, but also can efficiently maintain the relative position relationship with the transmission line to avoid deviation or instability. At the same time, by strictly checking the electric field data of each measurement point, it can ensure that the acquired data meets the needs of subsequent analysis and processing, and improve the accuracy and reliability of the overall work. In addition, by establishing a complete tracking and positioning process, it can provide clear guidance for actual inspection work and further improve the efficiency and effectiveness of inspection.

[0068] S305: Tracking and locating the UAV and the power transmission line according to the output of the electric field sensor array ranging and positioning model also includes:

[0069] Monitor the electric field strength data of each sensor in real time; trigger the alarm mechanism when abnormal electric field strength is detected; adjust the flight status of the drone according to the abnormal situation.

[0070] S306: The method further includes: judging the operating status of the transmission line based on the change of the electric field strength; recording abnormal data when an abnormality occurs in the transmission line; and transmitting the abnormal data to the monitoring center in real time.

[0071] In summary, the present invention realizes the comprehensive capture of the electric field distribution characteristics of the transmission line by setting a multi-dimensional data collection mechanism of electric field amplitude data, electric field direction data, electric field gradient data and electric field time-varying data, avoiding the problem of single data in traditional methods. The dual processing mechanism of combining the first digital preprocessing and the first feature extraction processing significantly improves the data quality, so that the accuracy of tracking and positioning is greatly improved.

[0072] By constructing the electric field measurement points into an array structure and introducing a weight calculation method based on measurement accuracy, the system can adaptively adjust the data processing strategy. This method significantly optimizes data processing efficiency, greatly reduces positioning response time compared to traditional single-point measurement methods, and can dynamically adjust measurement strategies according to environmental changes.

[0073] The cosine theorem is innovatively introduced into the distance measurement and positioning model of the electric field sensor array. Through the design of the model, the system can simultaneously consider the distance relationship, spatial position and heading angle. This multi-objective optimization design enables the model to have a higher positioning accuracy in practical applications, significantly exceeding the performance of traditional single measurement models.

[0074] Through modular design and standardized interfaces, the system can flexibly connect to new sensors and processing algorithms. When the application scenario changes, only the corresponding module parameters need to be adjusted without changing the overall architecture, which greatly reduces the system maintenance cost and improves the system's adaptability.

[0075] Using a circular array design based on five sensors and an optimized positioning algorithm, the system can quickly complete the entire process of data collection, processing, and position calculation. Compared with traditional visual navigation methods, it greatly saves time costs and significantly improves the efficiency of power transmission line inspections.

[0076] By setting the positioning accuracy threshold and exception handling mechanism, the system ensures the reliability of the positioning results through multiple safeguards while ensuring automation efficiency. This dual safeguard mechanism effectively reduces system errors and greatly reduces the waste of human resources.

[0077] Example 2

[0078] Reference Figure 2 - Figure 4 , which is the second embodiment of the present invention, provides a UAV power transmission line tracking and positioning method based on an electric field sensor array. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0079] Step 1: Electric Field Sensor Array Design and Installation

[0080] In order to achieve accurate tracking of three-phase transmission lines, an electric field sensor array consisting of 5 sensors is designed. The array adopts a uniform distribution method, with 4 sensors evenly distributed at the edge of the circular array and the other sensor located in the center of the array to form a symmetrical structure.

[0081] The sensor sampling signal passes through the sampling capacitor C s The converted voltage signal V i , the electric field strength E is obtained by reverse calculation i :

[0082] E i =V i / C s

[0083] Step 2: Derivation of electric field changes of transmission lines

[0084] Based on the point charge field strength formula, the electric field change rule of the transmission line is derived. The changes in the x and y directions of the line are derived:

[0085]

[0086] Where q is the total charge of the transmission line, ε0 is the dielectric constant of vacuum, r is the distance between the measurement position and the transmission line, and α is the measurement angle.

[0087] Step 3: Calculation of external field strength of transmission line

[0088] According to the formula of the change of the electric field of the transmission line in the x and y directions, the field strength at any point outside the transmission line is derived. The field strength formula is derived as follows:

[0089]

[0090] Where λ is the linear charge density, ρ is the vertical distance of any point, and α1 and α2 are the angles between any point and the two endpoints of the transmission line.

[0091] Step 4: Dual-point sensor distance integration

[0092] After the field strength of each sensor is derived from the derivation formula, and the distance data M of any two sensors is obtained, the sensor N is obtained by derivation i Distance from transmission line M i express:

[0093]

[0094] Step 5: Circular Sensor Array Data

[0095] In the circular sensor array, the radius of the array is R, and the distances between the sensors and the transmission line are M i , through the cosine theorem and the derivation of steps 3 and 4, the measurement relationship between the array center sensor N0 and its two side sensors N1 and N2 is obtained:

[0096]

[0097] Step 6: Determine the flight distance and elevation angle of the drone

[0098] Through step 5, the distance calculation formula between the center sensor and the sensors on both sides of the drone can be derived, and the relative elevation angle of the drone can be obtained, so as to determine the relative position of the drone and perform tracking and positioning.

[0099]

[0100] Where θ is the elevation angle of the transmission line relative to the UAV.

[0101] Step 7: Determine and correct the heading angle of the drone

[0102] When the sensors N1 and N2 on both sides of the drone are parallel to the transmission line, the heading angle of the drone can be expressed by the difference between the electric field intensities:

[0103] Δβ=E2-E1

[0104] Where Δβ is the heading angle of the UAV, and the heading can be corrected by adjusting Δβ=0.

[0105] Example 3

[0106] This embodiment also provides a computer device, which is suitable for a method for tracking and locating an unmanned aerial vehicle power transmission line based on an electric field sensor array, and includes a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a forced oscillation detection and positioning method for a distribution network as proposed in the above embodiment.

[0107] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, a forced oscillation detection and positioning method for a distribution network is implemented as proposed in the above embodiment.

[0108] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0109] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0110] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0111] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0112] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0113] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A UAV power transmission line tracking and positioning method based on an electric field sensor array, characterized in that: The method comprises acquiring electric field strength data around the transmission line and performing first electric field data processing according to data measured by an electric field sensor array; inputting the processed electric field data into an electric field sensor array ranging and positioning model; Tracking and positioning between the UAV and the power transmission line are performed based on the output of the electric field sensor array ranging and positioning model.

2. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 1, characterized in that: The electric field strength data is acquired through an electric field sensor array consisting of 5 sensors, wherein 4 sensors are evenly distributed at the edges of the circular array and 1 sensor is located at the center of the array to form a symmetrical structure.

3. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 2, characterized in that: The electric field sensor array distance measurement and positioning model includes: taking the vertical distance between any point and the transmission line as input; taking the electric field variation rule of the transmission line as calculation basis; and obtaining the relative position relationship between any point and the transmission line.

4. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 3 is characterized in that: The electric field variation rule of the transmission line at least includes: deriving the electric field variation rule of the transmission line in the x and y directions according to the point charge field strength formula; and deriving the field strength at any point outside the transmission line based on the transmission line variation formula in the x and y directions.

5. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 4, characterized in that: The tracking and positioning between the UAV and the power transmission line includes: obtaining the distance data between each sensor in the circular sensor array and the power transmission line; obtaining the measurement relationship between the array center sensor and the sensors on both sides thereof by the cosine theorem; and calculating the flight distance and elevation angle of the UAV based on the measurement relationship.

6. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 5, characterized in that: When the distance data of any two sensors are acquired, the distance integration is performed through the following steps: acquiring the distance data of the two sensors; deducing the relative distance between each sensor and the transmission line based on the distance data; and determining the overall position of the sensor array.

7. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 6, characterized in that: The determination and correction of the heading angle of the UAV includes: when the sensors on both sides of the UAV are parallel to the power transmission line, calculating the difference in electric field strength; The heading angle is determined based on the difference in electric field strength; the heading correction is achieved by adjusting the heading angle.

8. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 7, characterized in that: The output results of the electric field sensor array ranging and positioning model include: the relative distance between the UAV and the power transmission line; the elevation angle of the UAV relative to the power transmission line; and the real-time heading angle of the UAV.

9. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 8, characterized in that: Tracking and locating the UAV and the power transmission line according to the output of the electric field sensor array ranging and positioning model also includes: Monitor the electric field strength data of each sensor in real time; trigger the alarm mechanism when abnormal electric field strength is detected; adjust the flight status of the drone according to the abnormal situation.

10. The UAV power transmission line tracking and positioning method based on electric field sensor array according to claim 9, characterized in that: The method further includes: judging the operating state of the power transmission line based on the change of electric field strength; recording abnormal data when an abnormality occurs in the power transmission line; and transmitting the abnormal data to a monitoring center in real time.

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