A multi-machine signal transmission system and method applied to power distribution inspection

Abstract

This invention discloses a multi-machine signal transmission system and method for power distribution inspection. The system includes a multi-machine signal acquisition and preprocessing module, a dynamic spectrum allocation and multi-link transmission module, an edge relay node cluster, a secure encrypted transmission module, a collaborative scheduling and signal optimization module, and an emergency communication support module. The method achieves signal transmission through steps such as task initialization, signal acquisition and preprocessing, spectrum allocation and multi-link establishment, signal relay and secure transmission, dynamic optimization of transmission quality, emergency communication activation, and data sharing and processing. The technology is implemented by combining dynamic spectrum allocation, hierarchical relay, national cryptographic algorithm encryption, Ad Hoc self-organizing emergency network, and transmission and scheduling linkage optimization. This invention reduces signal interference during multi-machine operation, achieves wide-area signal coverage without dead zones, improves data transmission security and emergency transmission reliability, optimizes transmission efficiency, and meets the high-reliability and high-security multi-machine collaborative inspection requirements of power distribution networks.

Description

Technical Field

[0001] This invention relates to the field of power inspection technology, specifically to a multi-machine signal transmission system and method for power distribution inspection. Background Technology

[0002] With the continuous expansion of power distribution networks and the deepening of urbanization, the demand for the scope and frequency of power distribution line inspections has increased significantly. Traditional manual inspection methods are no longer sufficient to meet the actual requirements of modern power distribution network operation and maintenance management in terms of operational efficiency, coverage, and response speed. Unmanned aerial vehicle (UAV) inspection, with its advantages of flexible deployment, strong environmental adaptability, and wide coverage, is gradually becoming the mainstream technology for power distribution line inspection. In particular, the introduction of multi-UAV collaborative inspection modes can effectively improve the overall efficiency of inspection operations, providing a feasible technical path for full-coverage, high-frequency inspections of large-scale power distribution networks.

[0003] However, in multi-drone collaborative operation scenarios, the stability and reliability of communication links face severe challenges. Due to intense competition for channel resources when multiple drones operate simultaneously, co-channel interference is easily generated, leading to increased packet loss rate and transmission latency, which in turn affects the real-time transmission of inspection data and immediate analysis at the ground end. Furthermore, in remote areas or regions with complex terrain, 5G public network signal coverage has blind spots, and a single communication link is highly susceptible to signal interruption, resulting in the loss of inspection data and severely impacting the continuity and integrity of inspection tasks. At the same time, power distribution inspection data involves sensitive information such as the layout of power grid equipment and the precise location of defects, belonging to critical infrastructure data. The encryption mechanisms used in existing transmission systems are insufficient to meet the stringent standards of power grid companies for cyberspace information security and graded protection requirements in terms of security strength and protection level, posing a risk of data leakage and tampering during transmission and storage. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a multi-machine signal transmission system and method for power distribution inspection, so as to improve the anti-interference capability of the UAV power distribution inspection system in multi-machine collaborative communication and adapt to the development needs of high reliability and high safety power distribution inspection operations.

[0005] To address the aforementioned technical problems, this invention provides a multi-machine signal transmission system for power distribution inspection, comprising: a multi-machine signal acquisition and preprocessing module, a dynamic spectrum allocation and multi-link transmission module, an edge relay node cluster, a secure encrypted transmission module, a collaborative scheduling and signal optimization module, and an emergency communication support module; The multi-machine signal acquisition and preprocessing module is deployed on the inspection drone and is used to acquire image and video signals related to power line defects and external damage hazards. The dynamic spectrum allocation and multi-link transmission module is used to dynamically allocate communication spectrum resources based on the location of multiple machines, task priority and spectrum occupancy status, and establish multi-link redundant transmission channels to realize differentiated signal transmission. The edge relay node cluster is used to build a large-scale signal transmission network and to relay and preprocess the transmitted signals at the edge. The secure encrypted transmission module is used to implement identity authentication, data encryption, and integrity verification during signal transmission. The collaborative scheduling and signal optimization module is used to dynamically adjust the UAV's flight path and transmission parameters based on the signal transmission quality, thereby optimizing signal transmission efficiency, using a multi-machine multi-task scheduling algorithm. The emergency communication support module is used for signal transmission when the link is interrupted.

[0006] Preferably, the multi-machine signal acquisition and preprocessing module includes a signal acquisition unit, a signal noise reduction unit, and an adaptive compression unit. The signal acquisition unit acquires various types of inspection signals of power distribution lines through the sensing devices mounted on the UAV. The signal noise reduction unit is used to remove noise from the original signal. The adaptive compression unit processes the signal using different compression algorithms based on the importance classification of the signal.

[0007] Preferably, the dynamic spectrum allocation and multi-link transmission module includes a spectrum sensing unit, a dynamic allocation unit, a multi-link construction unit, and a multi-link switching unit. The spectrum sensing unit is used to detect idle spectrum resources in real time, the dynamic allocation unit is used to allocate spectrum resources, the multi-link construction unit is used to establish multi-layer redundant transmission links, and the multi-link switching unit is used to achieve seamless switching between links.

[0008] Preferably, the edge relay node cluster includes a mobile nest relay unit, a high-altitude fixed relay UAV, and a relay coordination control unit. The mobile nest relay unit is used for signal relay forwarding and AI preprocessing. The high-altitude fixed relay UAV and the mobile nest relay unit form a hierarchical relay network. The relay coordination control unit is used to sense network topology changes and adjust accordingly to ensure high reliability of the relay network.

[0009] Preferably, the secure encrypted transmission module establishes a dedicated encrypted channel through an APN card and adopts a national cryptographic algorithm suite, which includes an identity authentication unit based on the SM2 algorithm, a data encryption transmission unit based on the SM4 algorithm, a data integrity verification unit based on the SM3 algorithm, and a secure docking unit.

[0010] Preferably, the collaborative scheduling and signal optimization module includes a transmission quality monitoring unit, a path adjustment unit, a parameter optimization unit, and a model adaptation unit. The transmission quality monitoring unit is used to generate a transmission quality score, the path adjustment unit is used to adjust the UAV flight path according to the score, the parameter optimization unit is used to dynamically adjust the encoding method and transmission bandwidth according to the score, and the model adaptation unit is used to adapt the communication configuration of different types of UAVs.

[0011] Preferably, the emergency communication support module includes a self-organizing network construction unit, a priority scheduling unit, and an emergency recovery unit. The self-organizing network construction unit is used to activate the self-organizing network between UAVs to achieve chain relay. The priority scheduling unit is used to prioritize the transmitted information. The emergency recovery unit is used to monitor the status of the main link and realize link switching.

[0012] Preferably, the signal denoising unit uses an algorithm combining wavelet transform and adaptive median filtering to remove salt-and-pepper noise and Gaussian noise, and the adaptive compression unit uses the LZ77 lossless compression algorithm for the defect feature region signal and the H.265 lossy compression algorithm for the background region signal, with the compression ratio dynamically adjusted.

[0013] Preferably, the parameter optimization unit sets three transmission modes based on the transmission quality score: a high transmission rate mode is used when the score is ≥80, a balanced mode is used when the score is 60 < score < 80, and the path adjustment unit sends an early warning to the multi-machine multi-task scheduling algorithm and triggers the UAV flight path adjustment when the score is <60.

[0014] The present invention also provides a multi-machine signal transmission method for power distribution inspection, implemented based on the aforementioned multi-machine signal transmission system for power distribution inspection, the method comprising: Step S1: Receive the distribution inspection task issued by the power grid management platform. The collaborative scheduling and signal optimization module plans the flight route of the drones and the deployment location of the edge relay nodes based on the inspection area, the number of drones and terrain data, and determines the initial inspection area and task priority of each drone. Step S2: The multi-machine signal acquisition and preprocessing module acquires images and video signals related to power distribution line defects and external damage hazards; Step S3: The dynamic spectrum allocation and multi-link transmission module identifies idle spectrum resources in the inspection area and completes spectrum allocation. At the same time, it establishes multi-link redundant transmission channels and determines the transmission data type corresponding to each transmission channel. Step S4: Determine whether the drone is in a signal coverage blind spot. If it is, relay the signal to be transmitted through the edge relay node cluster and perform edge preprocessing. Then, after identity authentication, data encryption and integrity verification are completed through the secure encrypted transmission module, the signal is transmitted to the power grid management platform. If it is not in a signal coverage blind spot, the signal is transmitted directly to the power grid management platform after identity authentication, data encryption and integrity verification are completed through the secure encrypted transmission module. Step S5: The collaborative scheduling and signal optimization module monitors the signal transmission quality in real time and generates a transmission quality score. Based on the transmission quality score, it dynamically adjusts the UAV's flight path and signal transmission parameters and adapts the UAV's communication configuration. Step S6: The emergency communication support module monitors the transmission status of the multi-link redundant transmission channels in real time. When all transmission links are interrupted, it constructs a self-organizing network between UAVs and realizes UAV chain relay transmission of signals. When the main transmission link resumes normal communication, it switches back to the main transmission link for signal transmission.

[0015] The implementation of this invention has the following beneficial effects: This invention optimizes spectrum resource allocation through a dynamic spectrum allocation algorithm, effectively reducing the signal interference coefficient during multi-drone operations, improving transmission stability, and ensuring that multiple drones can operate simultaneously without significant lag; relying on a layered relay network built using mobile drone nests and high-altitude relay drones, it achieves signal coverage without dead zones over a 100-square-kilometer area, significantly improving the reliability of signal transmission in remote areas and effectively addressing the signal attenuation problem of traditional single links; based on the national cryptographic algorithm suite, it achieves end-to-end secure transmission, interfacing with the unified cryptographic service platform of the power grid and meeting the requirements of Level II security protection, preventing the leakage and tampering of sensitive data from power distribution inspections, and improving the success rate of secure data transmission; in emergency scenarios, it can activate an Ad Hoc self-organizing network, supporting chain relay of 10 drones, significantly improving the success rate of critical signal transmission, ensuring timely uploading of emergency defect alarm information, and solving the problem of inspection data loss after link interruption in traditional systems; simultaneously, it links signal transmission with multi-drone task scheduling, dynamically adjusting drone flight paths and transmission parameters through a transmission quality scoring mechanism, effectively improving signal transmission efficiency and fully meeting the actual operational needs of rapid power distribution network inspections. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1This is a schematic diagram of a multi-machine signal transmission system applied to power distribution inspection according to an embodiment of the present invention.

[0018] Figure 2 This is an architectural block diagram of the multi-machine signal acquisition and preprocessing module in Embodiment 1 of the present invention.

[0019] Figure 3 This is a block diagram of the dynamic spectrum allocation and multi-link transmission module architecture in Embodiment 1 of the present invention.

[0020] Figure 4 This is a block diagram of the edge relay node cluster architecture in Embodiment 1 of the present invention.

[0021] Figure 5 This is a block diagram of the secure encrypted transmission module architecture in Embodiment 1 of the present invention.

[0022] Figure 6 This is a block diagram of the collaborative scheduling and signal optimization module architecture in Embodiment 1 of the present invention.

[0023] Figure 7 This is a block diagram of the emergency communication support module architecture in Embodiment 1 of the present invention.

[0024] Figure 8 This is a flowchart illustrating a multi-machine signal transmission method applied to power distribution inspection according to Embodiment 2 of the present invention. Detailed Implementation

[0025] The following descriptions of the embodiments are taken with reference to the accompanying drawings, illustrating specific embodiments in which the present invention can be implemented. These embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0026] Please refer to Figure 1 As shown, Embodiment 1 of the present invention provides a multi-machine signal transmission system for power distribution inspection, including: a multi-machine signal acquisition and preprocessing module, a dynamic spectrum allocation and multi-link transmission module, an edge relay node cluster, a secure encrypted transmission module, a collaborative scheduling and signal optimization module, and an emergency communication support module; The multi-machine signal acquisition and preprocessing module is deployed on the inspection drone and is used to acquire image and video signals related to power line defects and external damage hazards. The dynamic spectrum allocation and multi-link transmission module is used to dynamically allocate communication spectrum resources based on the location of multiple machines, task priority and spectrum occupancy status, and establish multi-link redundant transmission channels to realize differentiated signal transmission. The edge relay node cluster is used to build a large-scale signal transmission network and to relay and preprocess the transmitted signals at the edge. The secure encrypted transmission module is used to implement identity authentication, data encryption, and integrity verification during signal transmission. The collaborative scheduling and signal optimization module is used to dynamically adjust the UAV's flight path and transmission parameters based on the signal transmission quality, thereby optimizing signal transmission efficiency, using a multi-machine multi-task scheduling algorithm. The emergency communication support module is used for signal transmission when the link is interrupted.

[0027] The multi-machine signal transmission system for power distribution inspection in this embodiment of the invention achieves wide-range, highly reliable, and highly secure transmission of inspection signals through the coordinated operation of multiple modules. Each module is a functional combination of hardware and software, with mutually complementary functions. Its specific structure, working principle, and interaction method are as follows: like Figure 2 As shown, the multi-machine signal acquisition and preprocessing module is deployed on each inspection drone and is the core module for the acquisition and preprocessing of inspection signals. It is used to acquire images and video signals related to power line defects and external damage hazards. The module specifically includes a signal acquisition unit, a signal noise reduction unit, and an adaptive compression unit. The three units work together in sequence to complete the acquisition, noise reduction, and compression of signals to form the inspection signal to be transmitted.

[0028] The signal acquisition unit, equipped with a high-definition camera, infrared sensor, and acoustic sensor mounted on a drone, simultaneously acquires visible light images, infrared thermal imaging videos, and acoustic signals of power distribution lines. The acquired signals cover six common equipment defects, including broken conductor strands, damaged insulators, and tilted towers, as well as external damage hazards such as construction machinery intrusion, enabling multi-dimensional, full-scene acquisition of power distribution line inspection signals. The signal noise reduction unit employs a composite noise reduction algorithm combining wavelet transform and adaptive median filtering to remove noise from the original signal acquired by the signal acquisition unit. Specifically, wavelet transform decomposes the original signal into low-frequency and high-frequency components. Thresholding is applied to the noisy high-frequency components for initial noise reduction. Adaptive median filtering then performs secondary noise reduction on the wavelet-transformed signal, removing residual salt-and-pepper noise and Gaussian noise. After processing by this unit, the signal-to-noise ratio of the inspection signal can be improved to over 35dB. The adaptive compression unit performs hierarchical compression processing based on signal importance, and the compression ratio can be dynamically adjusted according to the bandwidth of the subsequent transmission link. Specifically, for key area signals containing defects and potential external damage features, the LZ77 lossless compression algorithm is used for compression to fully preserve the feature information in the signal; for background area signals without key inspection information, the H.265 lossy compression algorithm is used for compression to minimize the signal transmission bandwidth occupation while ensuring that the effective information of the inspection signal is not lost.

[0029] like Figure 3As shown, the dynamic spectrum allocation and multi-link transmission module is the core module for communication resource scheduling and transmission channel construction of the system. It is used to dynamically allocate communication spectrum resources based on the location of multiple machines, task priority, and spectrum occupancy status, and at the same time establish multi-link redundant transmission channels to realize differentiated signal transmission. This module specifically includes a spectrum sensing unit, a dynamic allocation unit, a multi-link construction unit, and a multi-link switching unit. Each unit works together to achieve efficient utilization of spectrum resources and redundancy guarantee of transmission links.

[0030] The spectrum sensing unit employs cognitive radio technology to monitor the spectrum resource occupancy status of 2.4GHz and 5GHz civilian spectrum and 5G licensed spectrum within the power distribution inspection area in real time. It accurately identifies idle resources in various spectrum types, providing real-time and accurate resource data for subsequent spectrum allocation. The dynamic allocation unit constructs a spectrum allocation model based on a genetic algorithm, with the core optimization objectives of minimizing interference and transmission delay in multi-drone signal transmission. It allocates idle spectrum resources identified by the spectrum sensing unit to each inspection drone. The genetic algorithm, through core operations such as parameter encoding, initial population setting, and fitness function evaluation, iterates multiple times to approximate the optimal solution for spectrum allocation, effectively solving the channel resource contention problem during multi-drone collaborative operations and achieving efficient utilization of spectrum resources. The multi-link construction unit establishes a three-layer redundant transmission link system consisting of a 5G public network link, a power dedicated network link, and a direct connection link between the drone and its nest. Based on the type of inspection signal and task priority, it matches corresponding transmission links to different signals, achieving differentiated transmission of inspection signals. The three-layer links back each other up, providing channel assurance for signal transmission. The multi-link switching unit collects and evaluates the communication quality of each transmission link in real time through a fuzzy PID algorithm. When the communication quality of the main transmission link fails to meet the preset transmission index, it automatically completes a seamless switch to the backup transmission link. There is no interruption in signal transmission during the switching process, ensuring the continuity of inspection signal transmission.

[0031] For example Figure 4 As shown, the edge relay node cluster is used to build a large-scale signal transmission network, relay and forward inspection signals and perform edge preprocessing, effectively solving the signal coverage blind spot problem in remote inspection areas. The cluster specifically includes a mobile nest relay unit, a high-altitude fixed relay UAV and a relay cooperative control unit. The three work together to form a hierarchical and adaptive relay transmission network to achieve signal coverage without dead zones in the inspection area.

[0032] The mobile drone relay unit is modified from existing unattended automated drone nests. It integrates an RK3588 chip edge computing module, an omnidirectional gain antenna, and a 5G / 4G dual-mode communication module. Deployed at fixed intervals of 5 kilometers along power distribution lines, it features both signal relay and AI preprocessing functions. It can perform edge-end AI recognition preprocessing on inspection signals transmitted by drones, extracting key information before transmitting it upwards, significantly reducing the amount of invalid data transmitted. Simultaneously, the unit integrates an environmental perception structure, which can collect real-time temperature, humidity, and wind speed data of the deployment area. When environmental parameters exceed the device's preset operating thresholds, it automatically adjusts the relay power and signal transmission frequency to ensure the stability of the relay transmission. The high-altitude fixed relay drone consists of a long-endurance drone equipped with an omnidirectional gain antenna and a multi-link communication module. Its flight altitude is set at 50-100 meters, with a signal coverage radius of no less than 5 kilometers. It can hover and operate in remote areas without public network signal coverage, forming a hierarchical relay network with the mobile drone relay unit, compensating for the spatial coverage limitations of the mobile drone relay unit. The relay coordination control unit adopts a distributed routing protocol to perceive the topology changes of the entire relay transmission network in real time. When a relay node fails and cannot work normally, it automatically switches the transmission task of that node to an adjacent normal relay node, realizing the adaptive adjustment of the relay network topology, ensuring the high reliability of the relay network, and supporting the wide-range, dead-angle-free transmission of inspection signals.

[0033] Please refer to Figure 5 As shown, the secure encrypted transmission module is used to realize identity authentication, data encryption and integrity verification during the transmission of inspection signals, providing security for the transmission of sensitive data in power distribution inspection. The module uses a national cryptographic algorithm suite to build an encryption system and establishes a dedicated encrypted channel through an APN card to prevent signals from being illegally intercepted during transmission over the public network. Specifically, it includes an identity authentication unit based on the SM2 algorithm, a data encryption transmission unit based on the SM4 algorithm, a data integrity verification unit based on the SM3 algorithm, and a secure docking unit.

[0034] The identity authentication unit, based on the SM2 elliptic curve cryptography algorithm, assigns a unique digital certificate to each inspection drone, relay node, and power grid management platform. Identity authentication between devices is completed via a U-key; only authenticated devices can access the transmission network, preventing data leakage risks from unauthorized access at the source. The data encryption transmission unit uses the SM4 block cipher algorithm to fully encrypt the transmitted inspection signals. The encrypted signals can only be decrypted using the corresponding key, ensuring that inspection data is not stolen or cracked during transmission. The data integrity verification unit uses the SM3 hash algorithm to perform a hash operation on the encrypted transmitted data, generating a 128-bit hash value, which is transmitted along with the encrypted data. The data receiving end re-performs the SM3 hash operation on the received data and compares the hash values ​​to determine whether the data has been tampered with during transmission, achieving accurate data integrity verification. The security docking unit interfaces with the power grid unified cryptographic service platform, which handles the unified generation, distribution, and updating of encryption keys. The key update cycle for this unit can be flexibly set according to actual operation and maintenance needs, and it also supports emergency key updates. The entire encryption system meets the Level 2 security protection requirements of the power grid industry.

[0035] Please refer to Figure 6 As shown, the collaborative scheduling and signal optimization module works in conjunction with the multi-machine multi-task scheduling algorithm to dynamically adjust the UAV's flight path and transmission parameters based on the signal transmission quality, thereby optimizing signal transmission efficiency. This module specifically includes a transmission quality monitoring unit, a path adjustment unit, a parameter optimization unit, and a model adaptation unit. These units work together to achieve real-time monitoring of transmission quality and dynamic optimization of transmission strategies.

[0036] The transmission quality monitoring unit collects three core indicators—signal strength, packet loss rate, and latency—for each transmission link in real time. Every 100ms, it generates a comprehensive transmission quality score based on preset scoring criteria. The maximum score is 100 points, with the following specific criteria: signal strength greater than 70dBm earns 30 points, deducting 10 points for every 10dBm decrease; packet loss rate less than 0.5% earns 30 points, deducting 10 points for every 0.5% increase; latency less than 50ms earns 40 points, deducting 10 points for every 50ms increase. The path adjustment unit receives the real-time scoring data from the transmission quality monitoring unit. When the comprehensive transmission quality score falls below 60 points, it immediately sends a warning signal to the multi-machine, multi-task scheduling algorithm and triggers a UAV flight path adjustment command. By adjusting the UAV's flight position, it improves the signal transmission environment and enhances transmission quality. The parameter optimization unit dynamically adjusts the signal encoding method and transmission bandwidth based on the comprehensive transmission quality score, and sets three differentiated transmission modes: a high transmission rate mode is used when the score is greater than or equal to 80 points to maximize signal transmission efficiency; a balanced mode is used when the score is greater than 60 points but less than 80 points to balance transmission rate and transmission stability; and a low latency mode is used when the score is less than 60 points, dynamically adjusting encoding and bandwidth parameters to reduce transmission latency. The drone model adaptation unit supports the access of inspection drones of different sizes, load capacities, and flight performances to the system. By dynamically adjusting the transmission protocol and communication parameters, it adapts to the communication hardware configuration of different drones. The protocol adaptation latency of this unit does not exceed 100ms, making it compatible with mainstream inspection drone models. This eliminates the need for custom development of adaptation modules for individual models, effectively improving the system's versatility and reducing secondary development costs associated with subsequent model updates.

[0037] Please refer to Figure 7 As shown, the emergency communication support module is used for signal transmission when the link is interrupted. When all regular transmission links cannot work properly, it provides temporary emergency communication support for inspection signal transmission. The module specifically includes a self-organizing network construction unit, a priority scheduling unit, and an emergency recovery unit. The units work together to achieve rapid construction of the emergency communication network, priority transmission of critical signals, and seamless switching back to regular links.

[0038] The self-organizing network building unit adopts the AODV routing protocol, automatically activating the Ad Hoc self-organizing network among the inspection drones when the link is interrupted, forming a drone chain relay transmission channel. This network does not rely on fixed communication base stations and can be quickly built in remote signal blind spots, complex terrain with obstructions, or main link failure scenarios, adapting to the communication needs of large-scale multi-drone inspection operations. The priority scheduling unit prioritizes inspection signals, setting emergency defect alarm information and drone fault information as the highest priority. During emergency communication, communication resources are allocated to high-priority signals first, avoiding non-critical data occupying limited emergency bandwidth and ensuring that core data required for operation and maintenance decisions is transmitted back as soon as possible. The emergency recovery unit monitors the communication status of the regular main transmission link in real time. When the main link resumes normal communication, it automatically switches signal transmission from the emergency self-organizing network back to the regular main link, forming a drone chain relay transmission channel without relying on fixed communication base stations. Even in remote signal blind spots, complex terrain with obstructions, or main link failure scenarios, it can provide temporary communication support for multi-machine collaborative inspections, adapt to the needs of large-scale multi-machine operations, ensure seamless signal transmission, and guarantee the timely transmission of core data for operation and maintenance decisions, thus buying time for rapid handling of potential hazards and ensuring power grid safety. Switching back to main link transmission while shutting down the emergency self-organizing network avoids the transmission efficiency degradation caused by prolonged use of the emergency network and achieves a seamless transition from emergency communication to regular communication, ensuring the stability and efficiency of signal transmission throughout the entire inspection process.

[0039] The multi-machine signal transmission system of the present invention, applied to power distribution inspection, forms a technical closed loop through the coordinated cooperation of the above modules, covering signal acquisition and preprocessing, spectrum resource allocation, relay coverage and blind spot filling, data encryption and security, dynamic transmission optimization, and emergency communication support. It effectively solves the core technical problems of co-frequency interference, signal blind spots, and data security in multi-UAV collaborative power distribution inspection, improves the anti-interference capability and transmission reliability of multi-machine collaborative communication, and meets the development needs of highly reliable and highly secure power distribution inspection operations.

[0040] Please refer to the following: Figure 8 As shown, Embodiment 2 of the present invention also provides a multi-machine signal transmission method for power distribution inspection, based on the multi-machine signal transmission system for power distribution inspection described in Embodiment 1 of the present invention. The method includes: Step S1: Receive the distribution inspection task issued by the power grid management platform. The collaborative scheduling and signal optimization module plans the flight route of the drones and the deployment location of the edge relay nodes based on the inspection area, the number of drones and terrain data, and determines the initial inspection area and task priority of each drone. Step S2: The multi-machine signal acquisition and preprocessing module acquires images and video signals related to power distribution line defects and external damage hazards; Step S3: The dynamic spectrum allocation and multi-link transmission module identifies idle spectrum resources in the inspection area and completes spectrum allocation. At the same time, it establishes multi-link redundant transmission channels and determines the transmission data type corresponding to each transmission channel. Step S4: Determine whether the drone is in a signal coverage blind spot. If it is, relay the signal to be transmitted through the edge relay node cluster and perform edge preprocessing. Then, after identity authentication, data encryption and integrity verification are completed through the secure encrypted transmission module, the signal is transmitted to the power grid management platform. If it is not in a signal coverage blind spot, the signal is transmitted directly to the power grid management platform after identity authentication, data encryption and integrity verification are completed through the secure encrypted transmission module. Step S5: The collaborative scheduling and signal optimization module monitors the signal transmission quality in real time and generates a transmission quality score. Based on the transmission quality score, it dynamically adjusts the UAV's flight path and signal transmission parameters and adapts the UAV's communication configuration. Step S6: The emergency communication support module monitors the transmission status of the multi-link redundant transmission channels in real time. When all transmission links are interrupted, it constructs a self-organizing network between UAVs and realizes UAV chain relay transmission of signals. When the main transmission link resumes normal communication, it switches back to the main transmission link for signal transmission.

[0041] It should be noted that the power grid management platform receives encrypted signals through the data sharing interface module. After decryption and decompression, it combines the improved MobileNet-YOLO V4 model to complete AI recognition, generate inspection reports, and synchronize them to the defect management, anti-external damage visa management modules and the Dianhong ecosystem to achieve data sharing and application collaboration.

[0042] For the working principle and process of this embodiment, please refer to the description of the aforementioned Embodiment 1 of the present invention, which will not be repeated here.

[0043] As can be seen from the above description, compared with the prior art, the beneficial effects of the present invention are as follows: The present invention optimizes spectrum resource allocation through a dynamic spectrum allocation algorithm, effectively reducing the signal interference coefficient during multi-drone operation, improving transmission stability, and ensuring that multiple drones can operate simultaneously without significant lag; relying on a layered relay network built with mobile drone nests and high-altitude relay drones, it achieves signal coverage without dead zones in a 100-square-kilometer area, significantly improving the reliability of signal transmission in remote areas and effectively improving the signal attenuation problem of traditional single links; based on the national cryptographic algorithm suite, it achieves end-to-end secure transmission, connects with the unified cryptographic service platform of the power grid, and meets the requirements of the second-level security protection level, avoiding leakage and tampering of sensitive data in power distribution inspection, and improving the success rate of secure data transmission; in emergency scenarios, it can activate the Ad Hoc self-organizing network, supporting chain relay of 10 drones, significantly improving the success rate of key signal transmission, ensuring timely uploading of emergency defect alarm information, and solving the problem of inspection data loss after link interruption in traditional systems; at the same time, it links signal transmission with multi-drone task scheduling, dynamically adjusting the drone flight path and transmission parameters through a transmission quality scoring mechanism, effectively improving signal transmission efficiency and fully meeting the actual operational needs of rapid power distribution network inspection.

[0044] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A multi-machine signal transmission system for power distribution inspection, characterized in that, include: Multi-machine signal acquisition and preprocessing module, dynamic spectrum allocation and multi-link transmission module, edge relay node cluster, secure encrypted transmission module, collaborative scheduling and signal optimization module, and emergency communication support module; The multi-machine signal acquisition and preprocessing module is deployed on the inspection drone and is used to acquire image and video signals related to power line defects and external damage hazards. The dynamic spectrum allocation and multi-link transmission module is used to dynamically allocate communication spectrum resources based on the location of multiple machines, task priority and spectrum occupancy status, and establish multi-link redundant transmission channels to realize differentiated signal transmission. The edge relay node cluster is used to build a large-scale signal transmission network and to relay and preprocess the transmitted signals at the edge. The secure encrypted transmission module is used to implement identity authentication, data encryption, and integrity verification during signal transmission. The collaborative scheduling and signal optimization module is used to dynamically adjust the UAV's flight path and transmission parameters based on the signal transmission quality, thereby optimizing signal transmission efficiency, using a multi-machine multi-task scheduling algorithm. The emergency communication support module is used for signal transmission when the link is interrupted.

2. The system according to claim 1, characterized in that, The multi-machine signal acquisition and preprocessing module includes a signal acquisition unit, a signal noise reduction unit, and an adaptive compression unit. The signal acquisition unit acquires various types of inspection signals of power distribution lines through the sensing devices mounted on the UAV. The signal noise reduction unit is used to remove noise from the original signal. The adaptive compression unit processes the signal using different compression algorithms based on the importance classification of the signal.

3. The system according to claim 1, characterized in that, The dynamic spectrum allocation and multi-link transmission module includes a spectrum sensing unit, a dynamic allocation unit, a multi-link construction unit, and a multi-link switching unit. The spectrum sensing unit is used to detect idle spectrum resources in real time, the dynamic allocation unit is used to allocate spectrum resources, the multi-link construction unit is used to establish multi-layer redundant transmission links, and the multi-link switching unit is used to achieve seamless switching between links.

4. The system according to claim 1, characterized in that, The edge relay node cluster includes a mobile nest relay unit, a high-altitude fixed relay UAV, and a relay coordination control unit. The mobile nest relay unit is used for signal relay forwarding and AI preprocessing. The high-altitude fixed relay UAV and the mobile nest relay unit form a hierarchical relay network. The relay coordination control unit is used to sense network topology changes and adjust them to ensure high reliability of the relay network.

5. The system according to claim 1, characterized in that, The secure encrypted transmission module establishes a dedicated encrypted channel through the APN card and adopts a national cryptographic algorithm suite, which includes an identity authentication unit based on the SM2 algorithm, a data encryption transmission unit based on the SM4 algorithm, a data integrity verification unit based on the SM3 algorithm, and a secure docking unit.

6. The system according to claim 1, characterized in that, The collaborative scheduling and signal optimization module includes a transmission quality monitoring unit, a path adjustment unit, a parameter optimization unit, and a drone model adaptation unit. The transmission quality monitoring unit is used to generate a transmission quality score. The path adjustment unit is used to adjust the drone's flight path according to the score. The parameter optimization unit is used to dynamically adjust the encoding method and transmission bandwidth according to the score. The drone model adaptation unit is used to adapt the communication configuration of different types of drones.

7. The system according to claim 1, characterized in that, The emergency communication support module includes a self-organizing network construction unit, a priority scheduling unit, and an emergency recovery unit. The self-organizing network construction unit is used to activate the self-organizing network between UAVs to achieve chain relay. The priority scheduling unit is used to prioritize the transmitted information. The emergency recovery unit is used to monitor the status of the main link and realize link switching.

8. The system according to claim 2, characterized in that, The signal denoising unit uses an algorithm combining wavelet transform and adaptive median filtering to remove salt-and-pepper noise and Gaussian noise. The adaptive compression unit uses the LZ77 lossless compression algorithm for the defect feature region signal and the H.265 lossy compression algorithm for the background region signal, and the compression ratio is dynamically adjusted.

9. The system according to claim 6, characterized in that, The parameter optimization unit sets three transmission modes based on the transmission quality score. When the score is ≥80, a high transmission rate mode is used. When the score is 60 < and the score is <80, a balanced mode is used. When the score is <60, the path adjustment unit sends an early warning to the multi-machine multi-task scheduling algorithm and triggers the UAV flight path adjustment.

10. A multi-machine signal transmission method for power distribution inspection, implemented based on the multi-machine signal transmission system for power distribution inspection as described in claim 1, characterized in that, The method includes: Step S1: Receive the distribution inspection task issued by the power grid management platform. The collaborative scheduling and signal optimization module plans the flight route of the drones and the deployment location of the edge relay nodes based on the inspection area, the number of drones and terrain data, and determines the initial inspection area and task priority of each drone. Step S2: The multi-machine signal acquisition and preprocessing module acquires images and video signals related to power distribution line defects and external damage hazards; Step S3: The dynamic spectrum allocation and multi-link transmission module identifies idle spectrum resources in the inspection area and completes spectrum allocation. At the same time, it establishes multi-link redundant transmission channels and determines the transmission data type corresponding to each transmission channel. Step S4: Determine whether the drone is in a signal coverage blind spot. If it is, relay the signal to be transmitted through the edge relay node cluster and perform edge preprocessing. Then, after identity authentication, data encryption and integrity verification are completed through the secure encrypted transmission module, the signal is transmitted to the power grid management platform. If it is not in a signal coverage blind spot, the signal is transmitted directly to the power grid management platform after identity authentication, data encryption and integrity verification are completed through the secure encrypted transmission module. Step S5: The collaborative scheduling and signal optimization module monitors the signal transmission quality in real time and generates a transmission quality score. Based on the transmission quality score, it dynamically adjusts the UAV's flight path and signal transmission parameters and adapts the UAV's communication configuration. Step S6: The emergency communication support module monitors the transmission status of the multi-link redundant transmission channels in real time. When all transmission links are interrupted, it constructs a self-organizing network between UAVs and realizes UAV chain relay transmission of signals. When the main transmission link resumes normal communication, it switches back to the main transmission link for signal transmission.

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