Power transmission line airspace threat multi-source sensing fusion identification and grading expelling method and device

Abstract

The invention discloses a power transmission line airspace threat multi-source sensing fusion identification and grading expelling method and device, and relates to the technical field of power transmission line safety protection. The method comprises the following steps: synchronously acquiring a frequency spectrum signal, an acoustic signal and a visual image of a monitoring airspace; analyzing electronic identity information of a target from the frequency spectrum signal, extracting a target voiceprint feature from the acoustic signal, and obtaining a target visual feature from the visual image; based on the electronic identity information, the target voiceprint feature and the target visual feature, judging a target type through multi-modal fusion recognition; calculating a risk index of the target based on the target type, the distance between the target and the power transmission line and the motion trail of the target, and determining a threat level of the target according to the risk index; and according to the threat level, calling a repelling strategy corresponding to the threat level to repel the target.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power transmission line safety protection, and more particularly, to a power transmission line airspace threat multi-source perception fusion identification and hierarchical driving away method and device. BACKGROUND

[0002] With the rapid development of low-altitude economy, the airspace safety threat faced by power transmission lines is becoming increasingly serious: on the one hand, the "black flight" phenomenon of low-altitude aircraft such as plant protection drones and logistics drones occurs frequently, which is easy to collide with the conductor and cause power outage accidents. Traditional monitoring methods are difficult to accurately distinguish between authorized power operation drones and unauthorized threat targets due to the limitations of single perception technology, and there are problems of misjudgment and omission. On the other hand, the insulation failure caused by bird nesting has been high for a long time. Due to the adaptability of birds, the driving away efficiency of existing sound and light bird driving devices decreases with time, and it is difficult to achieve accurate disposal of high-risk bird species.

[0003] Current airspace protection technology has many shortcomings: high-end monitoring equipment is costly and difficult to scale to cover wide-area power transmission and distribution corridors; drone identification relies on single visual or spectral technology, which is easily affected by weather and terrain; there is no "white list" management mechanism for drones in the power industry, and there is a risk of misdriving legal operation drones; driving away technology either has poor electromagnetic compatibility or cannot solve the problem of bird adaptability, and the "perception-identification-disposal" links are disconnected, and there is no closed-loop management system. Therefore, it is urgent to develop a low-cost, high-precision, and self-adaptive power transmission line airspace threat protection system to break through the existing technical bottlenecks. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a power transmission line airspace threat multi-source perception fusion identification and hierarchical driving away method and device.

[0005] According to one aspect of the present application, a power transmission line airspace threat multi-source perception fusion identification and hierarchical driving away method is provided, comprising:

[0006] synchronously collecting spectrum signals, acoustic signals and visual images of the monitored airspace;

[0007] extracting target electronic identity information from the spectrum signals, extracting target voiceprint features from the acoustic signals, and obtaining target visual features from the visual images;

[0008] based on the electronic identity information, the target voiceprint features and the target visual features, determining the target type through multi-modal fusion identification;

[0009] based on the target type, the distance between the target and the power transmission conductor, and the motion trajectory of the target, calculating the risk index of the target, and determining the threat level of the target according to the risk index;

[0010] According to the threat level, a repelling strategy corresponding to the threat level is called to repel the target.

[0011] According to another aspect of the present application, there is provided a power transmission line airspace threat multi-source perception fusion identification and hierarchical repelling device, comprising:

[0012] The acquisition module is configured to synchronously acquire a spectrum signal, an acoustic signal and a visual image of a monitored airspace.

[0013] The extraction module is configured to parse electronic identity information of a target from the spectrum signal, extract a target voiceprint feature from the acoustic signal, and acquire a target visual feature from the visual image.

[0014] The identification module is configured to determine a target type based on the electronic identity information, the target voiceprint feature and the target visual feature through multi-modal fusion identification.

[0015] The calculation module is configured to calculate a risk index of the target based on the target type, a distance between the target and a power transmission conductor and a motion trajectory of the target, and determine a threat level of the target according to the risk index.

[0016] The repelling module is configured to repel the target according to the threat level by calling a repelling strategy corresponding to the threat level.

[0017] According to still another aspect of the present application, there is provided a computer readable storage medium, which stores a computer program for executing the method according to any one of the above aspects of the present application.

[0018] According to still another aspect of the present application, there is provided an electronic device, comprising a processor, a memory for storing executable instructions of the processor, and the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of the above aspects of the present application.

[0019] Therefore, the present application provides a power transmission line airspace threat multi-source perception fusion identification and hierarchical repelling system, which realizes accurate identification, differentiated disposal and whole-process management and control of airspace threats through multi-source perception fusion, dynamic identity authentication, adaptive repelling and closed-loop decision-making. BRIEF DESCRIPTION OF DRAWINGS

[0020] The exemplary embodiments of the present application can be more completely understood by reference to the following drawings:

[0021] Figure 1 is a flowchart of a power transmission line airspace threat multi-source perception fusion identification and hierarchical repelling method according to an exemplary embodiment of the present application;

[0022] Figure 2A structure schematic diagram of a power transmission line airspace threat multi-source perception fusion identification and hierarchical driving-off device provided by an exemplary embodiment of the present application is shown in the figure.

[0023] Figure 3 The structure of an electronic device provided by an exemplary embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0024] The exemplary embodiments according to the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, and are not all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described herein.

[0025] It should be noted that: the relative arrangement, numerical expression and numerical value of the components and steps set forth in these embodiments do not limit the scope of the present application, unless otherwise specified.

[0026] Those skilled in the art can understand that the terms "first", "second" and the like in the embodiments of the present application are only used to distinguish different steps, devices or modules, and do not represent any specific technical meaning, nor do they represent the inevitable logical sequence between them.

[0027] It should also be understood that in the embodiments of the present application, "a plurality of" can mean two or more, and "at least one" can mean one, two or more.

[0028] It should also be understood that for any component, data or structure mentioned in the embodiments of the present application, it can be understood as one or more in general, without explicit limitation or in the context of the opposite indication.

[0029] In addition, the term "and / or" in the present application is only a description of the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that there are three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.

[0030] It should also be understood that the description of each embodiment of the present application emphasizes the differences between each embodiment, and the same or similar parts can be referred to each other, and for the sake of brevity, will not be repeated.

[0031] At the same time, it should be understood that in order to facilitate description, the size of each part shown in the drawings is not drawn in accordance with the actual proportion relationship.

[0032] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way limiting on the application or its use.

[0033] Techniques, methods, and devices known to those of ordinary skill in the relevant art(s) can not be discussed in detail herein. However, where appropriate, the techniques, methods, and devices can be regarded as part of the present specification.

[0034] It should be borne in mind, that, as the use of the same reference numerals in different drawings usually indicates similar elements, so, once an element is defined in one drawing, it is not necessary to discuss it further in subsequent drawings.

[0035] Embodiments of the present application can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and / or configurations that can be suitable for use with electronic devices such as terminal devices, computer systems, servers, etc., include, but are not limited to: personal computers, servers, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputers, mainframe computers, and including any system of any of the above which includes distributed cloud computing environments, etc.

[0036] Electronic devices such as terminal devices, computer systems, servers, etc., can be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules can include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. Computer systems / servers can be practiced in distributed cloud-computing environments with remote processing devices that are linked through a communications network. In a distributed cloud-computing environment, program modules can reside on local or remote computer system storage media including memory storage devices.

[0037] Exemplary method

[0038] Figure 1 FIG. 1 is a flowchart illustrating a method for power transmission line airspace threat multi-source perception fusion identification and hierarchical driving-off according to an example embodiment of the present application. The method can be applied to electronic devices such as terminal devices, computer systems, servers, etc. Figure 1 As shown in FIG. 1, the method 100 for power transmission line airspace threat multi-source perception fusion identification and hierarchical driving-off includes the following steps:

[0039] Step 101, synchronously collecting frequency spectrum signals, acoustic signals, and visual images of a monitored airspace;

[0040] Step 102, parsing electronic identity information of a target from the frequency spectrum signals, extracting a target voiceprint feature from the acoustic signals, and obtaining a target visual feature from the visual images;

[0041] Step 103, based on the electronic identity information, the target voiceprint feature and the target visual feature, the target type is determined through multi-modal fusion recognition;

[0042] Step 104, based on the target type, the distance between the target and the power transmission conductor and the motion trajectory of the target, the risk index of the target is calculated, and the threat level of the target is determined according to the risk index;

[0043] Step 105, according to the threat level, the driving strategy corresponding to the threat level is called to drive the target away.

[0044] Specifically, the purpose of the present application is to overcome the defects of the existing power transmission line airspace protection technology, and to provide a power transmission line airspace threat multi-source perception fusion identification and hierarchical driving system, which realizes accurate identification, differentiated treatment and whole-process management and control of airspace threats through multi-source perception fusion, dynamic identity authentication, adaptive driving and closed-loop decision-making.

[0045] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0046] The present application includes multi-source perception, intelligent identification, hierarchical driving, intelligent decision-making and data storage, forming a "perception-identification-warning-driving-verification" closed-loop protection system:

[0047] 1. Multi-source perception: integrating a spectrum detection unit, a voiceprint acquisition unit and a visual monitoring unit, synchronously acquiring electronic identity information, acoustic features and visual image data of the target, providing multi-dimensional data support for subsequent identification;

[0048] 2. Intelligent identification: based on a multi-modal fusion algorithm, the data collected by the multi-source perception module is cooperatively processed to complete the accurate identification of authorized drones, unauthorized drones and high-risk birds;

[0049] 3. Hierarchical driving: according to the target type and threat level output by the intelligent identification module, the corresponding warning or driving means are called to realize differentiated treatment;

[0050] 4. Intelligent decision-making: a risk assessment model and an adaptive decision tree are constructed to dynamically match the treatment strategy, and the treatment effect is verified through target trajectory tracking to optimize the decision logic;

[0051] 5. Data storage: storing perception data, identification results, treatment records and equipment operation logs to provide data support for system iteration optimization and traceability.

[0052] (I) Multi-source perception

[0053] 1. Spectrum detection unit: using software-defined radio (SDR) technology, covering a frequency range of 25MHz-6000MHz, capturing real-time drone remote control and image transmission signals, analyzing device unique identification (ID), location, speed, and other electronic identity information in the signal; while supporting dynamic frequency scanning, adapting to the communication frequency bands of different brands and models of drones, ensuring the comprehensiveness and timeliness of spectrum signal capture;

[0054] 2. Voiceprint collection unit: configuring a high-sensitivity acoustic array to collect target acoustic signals (including drone rotor vibration sound, bird chirping sound) and environmental noise, filtering interference signals such as wind noise and wire corona sound through environmental noise suppression algorithms (such as wavelet threshold denoising algorithm), and extracting pure target voiceprint features;

[0055] 3. Visual monitoring unit: deploying visible light cameras and infrared thermal imaging cameras to achieve all-weather visual monitoring, obtaining target contour, motion trajectory, color, and other visual features; cameras have automatic zoom and gimbal control functions, which can adjust the shooting angle and focal length according to the target positioning results to ensure the clarity of visual data.

[0056] (II) Intelligent identification

[0057] 1. Drone identification sub-module:

[0058] (1) Establish a "white list" database of power operation drones, storing information such as authorized drone device ID, operation period, and airspace range;

[0059] (2) Adopting "electronic identity verification + feature fusion" dual recognition mechanism: first, compare the target electronic ID analyzed by the spectrum detection unit with the "white list", if matched, it is determined as an authorized target; if not matched, further fuse the target voiceprint features (such as frequency peak value corresponding to rotor speed) and visual features (such as body size, number of rotors), through a CNN-LSTM fusion model based on attention mechanism, to determine whether the target is an unauthorized high-risk drone (such as large-scale plant protection drone, logistics drone);

[0060] 2. Bird identification sub-module:

[0061] (1) Construct a high-risk bird species voiceprint database for power transmission scenarios, including magpie, crow, and other bird voiceprint samples that can cause faults, and extract the Mel frequency cepstral coefficient (MFCC) of the samples as feature vectors;

[0062] (2) Using support vector machine (SVM) algorithm, compare the target MFCC features extracted by the voiceprint collection unit with the database samples, and combine visual features (such as bird size, feather color) to assist identification, achieving accurate differentiation between high-risk bird species and ordinary birds.

[0063] (Three) hierarchical drive away

[0064] 1. Warning unit:

[0065] (1) High sound broadcast sub-unit: adopt directional speaker, support custom voice (such as "This is high-voltage transmission line protection area, no drone flight / bird nesting, violators will be held legally responsible"), adjust sound source direction combined with target positioning result, ensure accurate warning information reach pilot or surrounding personnel; At the same time, start audio and video recording synchronously, complete evidence collection;

[0066] (2) Virtual electronic fence sub-unit: simulate temporary flight restricted area message in ADS-B protocol through aviation signal broadcast equipment, send flight restricted instruction to compliant drones, trigger on-board obstacle avoidance system, guide autonomous detour;

[0067] 2. Drive away unit:

[0068] (1) Drone drive away sub-unit: adopt directional radio frequency interference technology, emit same frequency interference signal in 2.4GHz / 5.8GHz ISM frequency band, suppress control link of unlicensed drone; Realize beam orientation through phased array antenna, control interference range (interference radius can be adjusted, maximum not more than 50 meters), avoid electromagnetic interference to surrounding civil equipment;

[0069] (2) Bird drive away sub-unit: based on bird species information output by intelligent identification module, call exclusive dynamic sound wave sequence (such as calling the calling sound of its natural enemy (hawk) + non-periodic ultrasonic wave (frequency 20kHz-40kHz) combination for magpie), directional emission through sound wave emitter; Sound wave sequence adopts random frequency switching (switching interval 1-3 seconds), break bird biological adaptability, ensure long-term drive away effect.

[0070] (Four) Intelligent decision

[0071] 1. Risk assessment model: take target type (authorized drone / unauthorized drone / high-risk bird), distance between target and conductor (≤50 meters for high risk, 50-100 meters for medium risk, >100 meters for low risk), motion trajectory (toward conductor for high risk, away for low risk) as risk factors, determine weight of each factor by AHP (analytic hierarchy process), calculate risk index of target (0-10 points, ≤3 points for low risk, 4-7 points for medium risk, ≥8 points for high risk);

[0072] 2. Adaptive decision tree: dynamically match disposal strategy according to risk index:

[0073] (1) Low risk target: only start high sound broadcast warning, record target trajectory synchronously;

[0074] (2) Medium-risk target: Start high-pitched broadcast warning + virtual electronic fence (for drones) or dynamic sound wave warning (for birds), continuously monitor target behavior;

[0075] (3) High-risk target: Start directional radio frequency interference (for drones) or high-intensity dynamic sound wave repulsion (for birds), while enhancing audio and video evidence;

[0076] 3. Disposal effect verification: Use Kalman filter algorithm to track target trajectory, analyze target motion trend after disposal (such as moving away from the conductor, then determine the disposal effective, continue to approach, then upgrade the disposal strategy), and feedback the verification result to the decision tree to iteratively optimize the strategy matching logic.

[0077] In a specific embodiment of the present application, the workflow of the present application is:

[0078] 1. Data collection: The spectrum detection unit, voiceprint collection unit, and visual monitoring unit of the multi-source perception module work synchronously to collect frequency spectrum signals, voiceprint signals, and visual images in the airspace in real time, and realize the time and space alignment of multi-source data through a space-time synchronization algorithm (based on GPS timestamp);

[0079] 2. Intelligent identification: The intelligent identification module receives the aligned multi-source data, first determines authorized / unauthorized drones through the drone identification sub-module, and determines high-risk / ordinary birds through the bird identification sub-module, and outputs target type information;

[0080] Risk assessment: The intelligent decision-making module inputs target type, distance, and trajectory parameters into the risk assessment model to calculate the risk index and determine the threat level;

[0081] 3. Graded disposal: The graded repulsion module calls corresponding warning or repulsion means according to the threat level to execute disposal operations;

[0082] 4. Effect verification: The intelligent decision-making module verifies the disposal effect by tracking the target trajectory, records the result if the disposal is effective, and adjusts the disposal parameters (such as increasing the radio frequency interference power or switching the sound wave sequence) if it is not effective and re-executes the disposal;

[0083] 5. Data storage: Store the perception data, identification results, disposal records, and verification results into the data storage module to form a complete closed-loop management record.

[0084] In a specific embodiment of the present application, the implementation process of the above method is as follows:

[0085] I. System deployment

[0086] Select a cross-provincial ultra-high voltage transmission line (passing through mountainous areas, urban suburbs, and cross-river sections) as a pilot to deploy the system:

[0087] 1. Fixed device deployment: Deploy 1 set of fixed devices every 5 kilometers in important transmission line crossing sections (such as river crossing sections), areas with high bird nesting, and areas with frequent drone activities. The fixed devices integrate multi-source sensing modules, hierarchical repelling modules, and intelligent decision-making module core functions;

[0088] 2. Portable terminal configuration: Equip 5 portable terminals for operation and maintenance personnel. The terminals integrate small-sized spectrum detection units, voiceprint collection units, and visual monitoring units, support data intercommunication with fixed devices, and are used for mobile blind filling and temporary operation area protection;

[0089] 3. Data center construction: Deploy data storage modules and remote monitoring platforms in the power operation and maintenance center to receive data from fixed devices and portable terminals in real time, and realize centralized monitoring and management of the airspace safety of the pilot area.

[0090] II. System operation test

[0091] 1. Authorized drone identification test: Dispatch 3 power inspection drones (already recorded in the "white list") to operate in the pilot area. The system analyzes the drone electronic ID through the spectrum detection unit and determines it as an authorized target after matching with the "white list", without triggering the repelling operation, only low-level monitoring, with an identification accuracy of 100%;

[0092] 2. Non-authorized drone disposal test: Simulate 2 agricultural plant protection drones (not recorded in the "white list") approaching the transmission line. The system identifies them as medium-risk targets, first starts high-pitched broadcast warning and virtual electronic fence, and 1 drone receives the no-fly instruction and detours. The other drone continues to approach, and the system upgrades to directional radio frequency interference, successfully forces it to return, with a disposal efficiency of 100%;

[0093] 3. High-risk bird repelling test: In the area with high bird nesting, the system identifies 5 magpies (high-risk bird species) and starts the dynamic sound wave sequence (eagle cry + 25 kHz ultrasonic wave) for magpies. The magpies all fly away within 3 minutes, and no magpies return within the next 24 hours, with stable repelling effect;

[0094] 4. Complex environment adaptability test: In heavy rain and strong wind weather, the system still maintains more than 85% target identification accuracy through environmental noise suppression algorithm and visual image enhancement technology, with stable device operation and no faults.

[0095] III. Test results

[0096] During the 3-month pilot operation, the system cumulatively identified 23 unauthorized drones, 12 unauthorized drones and 48 high-risk birds, with a successful disposal rate of 98%. No faults caused by drone collisions or bird nesting occurred in the pilot area, and the fault rate decreased by 100% compared to the same period. The cost of a single set of fixed devices is 42% lower than that of traditional equipment, and the workload of manual inspection is reduced by 30%, achieving a balance between protection effectiveness and economy.

[0097] In summary, the beneficial effects of the present application include:

[0098] 1. High recognition accuracy: The "spectrum-voiceprint-vision" multi-source perception fusion technology is used to break through the limitations of single technology recognition, with an authorized drone recognition accuracy of ≥99%, and a non-authorized drone and high-risk bird recognition accuracy of ≥95%, effectively avoiding misjudgment and omission;

[0099] 2. Strong disposal adaptability: Differentiated disposal strategies are designed for different targets, with good electromagnetic compatibility of directional radio frequency interference, dynamic sound wave sequence can crack bird adaptability, and warning and driving means can be flexibly switched according to the threat level, taking into account disposal effect and safety;

[0100] 3. Controllable cost: Modular design and lightweight algorithm are used, and the cost of a single set of fixed devices is more than 40% lower than that of traditional high-end monitoring equipment, and "fixed + portable" networking is supported, which can realize low-cost coverage of wide-area power transmission and distribution corridors;

[0101] 4. Closed-loop control: Through risk assessment and trajectory tracking, the "perception-identification-disposal-verification" whole process is closed, and the system can autonomously learn and optimize the decision logic, with continuous improvement of long-term use performance;

[0102] 5. Good compatibility: It supports docking with existing power operation systems, can import "white list" data of power operation drones, and output identification and disposal data to provide data support for power grid operation, and is easy to popularize and apply.

[0103] Exemplary apparatus

[0104] Figure 2 The structural diagram of the power transmission line airspace threat multi-source perception fusion identification and hierarchical driving device provided by an exemplary embodiment of the present application is shown in FIG. 1. Figure 2 As shown in FIG. 1, the device 200 includes:

[0105] The acquisition module 210 is configured to synchronously acquire the spectrum signal, the acoustic signal and the visual image of the monitored airspace;

[0106] The extraction module 220 is configured to parse the electronic identity information of the target from the spectrum signal, extract the voiceprint features of the target from the acoustic signal, and obtain the visual features of the target from the visual image;

[0107] The identification module 230 is configured to determine the target type through multi-modal fusion identification based on the electronic identity information, the target voiceprint feature, and the target visual feature.

[0108] The calculation module 240 is configured to calculate the risk index of the target based on the target type, the distance between the target and the power transmission conductor, and the motion trajectory of the target, and determine the threat level of the target according to the risk index.

[0109] The driving-off module 250 is configured to drive off the target according to the threat level by calling a driving-off strategy corresponding to the threat level.

[0110] Exemplary electronic device

[0111] Figure 3 is a structure of an electronic device provided by an exemplary embodiment of the present application. As shown in Figure 3 The electronic device 30 includes one or more processors 31 and a memory 32.

[0112] The processor 31 can be a central processing unit (CPU) or other form of processing unit having data processing and / or instruction execution capabilities, and can control other components in the electronic device to perform desired functions.

[0113] The memory 32 can include one or more computer program products that can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM), cache, and / or the like. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, and / or the like. One or more computer program instructions can be stored on the computer-readable storage media, and the processor 31 can run the program instructions to implement the methods of the software programs of the various embodiments of the present application described above and / or other desired functions. In one example, the electronic device can further include an input device 33 and an output device 34, which are interconnected through a bus system and / or other forms of connection mechanism (not shown).

[0114] In addition, the input device 33 can also include, for example, a keyboard, a mouse, and the like.

[0115] The output device 34 can output various information to the outside. The output device 34 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0116] Of course, in order to simplify, Figure 3Only some of the components of the electronic device related to the present application are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition to this, the electronic device can include any other appropriate components according to a specific application.

[0117] Exemplary computer program product and computer readable storage medium

[0118] In addition to the above method and device, an embodiment of the present application can be a computer program product, which includes computer program instructions, which when executed by a processor, cause the processor to perform steps of the methods according to various embodiments of the present application described in the above "Exemplary Methods" section of this specification.

[0119] The computer program product can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, etc., and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server.

[0120] In addition, an embodiment of the present application can also be a computer readable storage medium, which stores computer program instructions, which when executed by a processor, cause the processor to perform steps of the methods according to various embodiments of the present application described in the above "Exemplary Methods" section of this specification.

[0121] The computer readable storage medium can be any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0122] The above describes the basic principles of the present application in conjunction with specific embodiments, but it should be noted that the advantages, benefits, effects and the like mentioned in the present application are only examples and are not limiting, and these advantages, benefits, effects and the like cannot be considered as necessary for each embodiment of the present application. In addition, the above specific details disclosed are only for the purpose of example and understanding, and are not limiting, and the above details do not limit the present application to be necessarily implemented with the above specific details.

[0123] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the same or similar parts between each embodiment can be understood by referring to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be understood by referring to the part of the method embodiment.

[0124] The block diagrams of the devices, systems, apparatuses, systems involved in the present application are only illustrative examples and are not intended to require or imply the connection, arrangement, configuration shown in the block diagram. As those skilled in the art will recognize, these devices, systems, apparatuses, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have" and the like are open-ended words, which mean "including but not limited to", and can be used interchangeably. The words "or" and "and" used herein mean the word "and / or", and can be used interchangeably unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0125] The method and system of the present application can be implemented in many ways. For example, the method and system of the present application can be implemented by software, hardware, firmware or any combination of software, hardware and firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present application are not limited to the above specific description, unless otherwise specifically described. In addition, in some embodiments, the present application can also be implemented as programs recorded in recording media, which include machine-readable instructions for implementing the method according to the present application. Therefore, the present application also covers the recording media storing the programs for executing the method according to the present application.

[0126] It is also important to note that the systems, devices and methods of the present application can be embodied in a variety of forms without departing from the spirit of the application. Furthermore, the foregoing description has been directed to certain embodiments of the application. It is recognized that modifications, additions and / or omissions can be made to these embodiments without departing from the spirit of the application. Accordingly, the particular arrangements disclosed are meant to be illustrative only and not limiting as to the scope of the application. It is thus intended that the true scope of the application be indicated by the appended claims together with their full scope of equivalents.

[0127] The foregoing description has been presented for purposes of illustration and description. Furthermore, the description is not intended to limit the embodiments of the application to the forms disclosed herein. Although the example aspects and embodiments have been discussed, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for multi-source perception fusion identification and hierarchical removal of airspace threats to transmission lines, characterized in that, include: Simultaneously acquire spectral signals, acoustic signals, and visual images of the monitored airspace; The electronic identity information of the target is parsed from the spectrum signal, the voiceprint features of the target are extracted from the acoustic signal, and the visual features of the target are obtained from the visual image; Based on the electronic identity information, the target voiceprint features, and the target visual features, the target type is determined through multimodal fusion recognition. Based on the target type, the distance between the target and the transmission line, and the target's trajectory, the risk index of the target is calculated, and the threat level of the target is determined according to the risk index. Based on the threat level, the corresponding expulsion strategy is invoked to expel the target.

2. The method according to claim 1, characterized in that, Based on the electronic identity information, the target voiceprint features, and the target visual features, the target type is determined through multimodal fusion recognition, including: The parsed electronic identity information is compared with a pre-stored database of authorized drone whitelists; If the comparison is successful, the target is determined to be an authorized drone; If the comparison fails, the target's voiceprint features and visual features are fused together, and the target is determined to be an unauthorized drone or bird using a preset fusion recognition model.

3. The method according to claim 2, characterized in that, Determining that the target is an unauthorized drone or bird also includes: When the target is determined to be a bird, the extracted voiceprint features of the target are compared with a pre-stored high-risk bird voiceprint database, and combined with the target's visual features, the high-risk bird species are identified.

4. The method according to claim 1, characterized in that, The expulsion strategy is as follows: If the threat level is low risk, a high-volume broadcast warning will be activated, and the target's movement trajectory will be recorded simultaneously. If the threat level is medium risk, a high-volume broadcast warning will be activated, and a virtual electronic fence or dynamic sound wave warning will be activated in addition. If the threat level is high risk, then directional radio frequency interference or high-intensity dynamic acoustic wave repellent will be initiated.

5. The method according to claim 1, characterized in that, Invoking the deportation strategy corresponding to the threat level to carry out graded deportation of the target, including: If the deterrence strategy is a warning measure, use a directional loudspeaker and combine it with the target location results to adjust the direction of the sound source and accurately send the warning information to the pilot or people in the vicinity. Based on the warning information, a no-fly zone instruction is sent to compliant drones by simulating a temporary no-fly zone message in the ADS-B protocol through aviation signal broadcasting equipment. If the expulsion strategy is to use expulsion methods, directional radio frequency jamming technology is adopted to transmit co-channel jamming signals in the 2.4GHz / 5.8GHz ISM band to suppress the control link of the target type unauthorized UAV, and the beam direction is achieved through phased array antenna to control the jamming range; Based on the bird species information in the target type, a unique dynamic sound wave sequence of calls and non-periodic ultrasonic waves are invoked and emitted directionally through a sound wave transmitter.

6. The method according to claim 1, characterized in that, Also includes: The movement trajectory of the target after the graded removal is tracked, and the treatment effect is verified based on the trajectory changes.

7. The method according to claim 6, characterized in that, Tracking the movement trajectory of the target after the graded removal and verifying the effectiveness of the treatment based on trajectory changes includes: Analyze the movement trajectory of the target after the graded removal. If the target moves away from the power transmission line, the action is deemed effective. If the target continues to move closer to the power transmission line, the removal strategy parameters are adjusted and the action is re-executed.

8. A device for multi-source perception fusion identification and hierarchical removal of airspace threats to transmission lines, characterized in that, include: The acquisition module is used to simultaneously acquire spectral signals, acoustic signals, and visual images of the monitored airspace; The extraction module is used to parse the electronic identity information of the target from the spectrum signal, extract the voiceprint features of the target from the acoustic signal, and obtain the visual features of the target from the visual image; The identification module is used to determine the target type based on the electronic identity information, the target voiceprint features, and the target visual features through multimodal fusion identification; The calculation module is used to calculate the risk index of the target based on the target type, the distance between the target and the power transmission line, and the target's movement trajectory, and to determine the threat level of the target based on the risk index; The expulsion module is used to invoke an expulsion strategy corresponding to the threat level to expel the target.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-7.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-7.

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