Unmanned aerial vehicle inspection system and method for power transmission, transformation and distribution power equipment

Abstract

The invention relates to the technical field of power system automation, in particular to an unmanned aerial vehicle inspection system and method for transmission, transformation and distribution power equipment. Comprising an unmanned aerial vehicle flight platform, a high-resolution multispectral imaging system, a data transmission and communication module, a quantum encryption wireless communication network module, an edge intelligent data processing unit and a ground control station. The ultra-light high-strength composite fuselage of the flying platform of the unmanned aerial vehicle is constructed by adopting the nano reinforced carbon fiber composite material, and the surface is coated with the intelligent self-adaptive coating, so that the strength and the light weight of the fuselage are ensured, and the optical and physical properties can be automatically adjusted according to the external environment; and the flight stability and safety of the unmanned aerial vehicle in a complex environment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and particularly to an unmanned aerial vehicle (UAV) inspection system and method for power transmission, transformation and distribution equipment. Background Technique

[0002] In modern power systems, the safe and stable operation of power transmission, transformation and distribution equipment is crucial for ensuring the normal power supply of social production and life. With the continuous expansion of the power grid scale, the number of power equipment has increased sharply and is more widely distributed.

[0003] The traditional manual inspection method is difficult to meet the requirements of efficient, accurate and comprehensive inspection. Manual inspection not only consumes a large amount of manpower, material resources and time, but also has disadvantages such as limited detection range, strong subjectivity, and difficulty in detecting hidden faults. Moreover, in some harsh environments or high-risk areas, the implementation of manual inspection faces great difficulties and even dangers. However, early UAV inspection systems have many deficiencies in aspects such as fuselage structure, flight control, detection functions, and data processing and transmission. The traditional UAV fuselage materials are difficult to balance the requirements of high strength and light weight, resulting in limited flight payload, and are easily damaged in complex environments, affecting flight stability and safety, and are difficult to meet the needs of long-term, long-distance and complex environment operations. The flight control system is not intelligent enough, and the navigation and positioning accuracy is poor. In complex electromagnetic environments or signal occlusion areas, flight deviations or even out-of-control often occur, increasing the risk of flight accidents.

[0004] In terms of detection equipment, in the past, most were single imaging or detection means, unable to comprehensively obtain multi-dimensional information of power equipment, and difficult to accurately identify potential faults and defects. For example, it is difficult to detect hidden dangers such as internal thermal anomalies or corona discharges of equipment only by visible light imaging, and it cannot provide sufficient basis for equipment maintenance and management. Data transmission and communication are easily interfered, there is a risk of data leakage, the transmission efficiency is low, the delay is large, and a large amount of collected data cannot be processed and analyzed in real time, seriously restricting the inspection efficiency and response speed. The ground control station lacks an intelligent management platform, is difficult to integrate and process a large amount of inspection data, has poor accuracy in evaluating the health status of equipment, and cannot provide personalized and accurate decision-making support for equipment management personnel, which is not conducive to optimizing equipment maintenance plans and resource allocation. Summary of the Invention

[0005] The purpose of the present invention is to provide an unmanned aerial vehicle inspection system and method for power transmission, transformation and distribution equipment to solve the problems raised in the above background technique.

[0006] The technical solution of the present invention is: an unmanned aerial vehicle inspection system and method for power transmission, transformation and distribution equipment, including an unmanned aerial vehicle flight platform, a high-resolution multi-spectral imaging system, a data transmission and communication module, the quantum encryption wireless communication network module, an edge intelligent data processing unit, a ground control station and an unmanned aerial vehicle inspection method for power transmission, transformation and distribution equipment;

[0007] The UAV flight platform includes an ultra-lightweight high-strength composite fuselage and an omni-directional intelligent flight control system;

[0008] The ultra-lightweight high-strength composite fuselage is constructed of nano-enhanced carbon fiber composite materials, and the surface is coated with an intelligent adaptive coating that can automatically adjust optical and physical properties according to external environmental conditions;

[0009] The omni-directional intelligent flight control system integrates a multi-sensor fusion navigation and positioning system, and the multi-sensor fusion navigation and positioning system includes an inertial measurement unit, a global positioning system, a laser altimeter, a vision sensor, a geomagnetic sensor, a barometric pressure sensor, and a microwave radar;

[0010] The high-resolution multi-spectral imaging system includes visible light, infrared thermal imaging, ultraviolet imaging, hyperspectral imaging, and lidar and spectral analysis modules;

[0011] A data transmission and communication module, and the data transmission and communication module includes a quantum encryption wireless communication network and an edge intelligent data processing unit;

[0012] The quantum encryption wireless communication network module is established based on quantum encryption technology and adopts an adaptive networking technology with multiple frequency bands and multiple channels;

[0013] The edge intelligent data processing unit integrates a deep learning chip, a graphics processing unit, and a field programmable gate array;

[0014] The ground control station includes an immersive virtual inspection and command center and a big data-driven power equipment health management platform.

[0015] Preferably, for the big data-driven power equipment health management platform of the ground control station, its distributed storage adopts Ceph distributed storage technology, the number of computing nodes in cloud computing technology is not less than 10, and the health status assessment model is based on at least 5000 groups of historical inspection data of power equipment.

[0016] Preferably, a UAV inspection method for power transmission, transformation and distribution equipment includes pre-inspection preparation steps, flight inspection steps, and post-inspection data processing and report generation steps;

[0017] The pre-inspection preparation steps include equipment initialization and data synchronization, and intelligent route planning and task assignment;

[0018] The flight inspection steps include autonomous flight and adaptive data collection, and real-time data processing and edge decision-making;

[0019] The post-inspection data processing and report generation steps include data integration and in-depth mining analysis, and personalized report generation and intelligent push.

[0020] Preferably, in the device initialization and data synchronization step, the ground control station synchronizes the data related to the inspection task to the local storage device of the UAV, and conducts a comprehensive self-check on the flight control system and the data transmission and communication module.

[0021] Preferably, in the intelligent flight path planning and task allocation step, the operator formulates the initial inspection flight path at the ground control station, and the platform prioritizes the inspection tasks according to the power equipment information and reasonably allocates resources.

[0022] Preferably, in the real-time data processing and edge decision-making step, the edge artificial intelligence data processing unit processes and analyzes the data in real time, and uses the deep learning model for fault identification and diagnosis.

[0023] Preferably, in the data integration and in-depth mining and analysis step, after the UAV returns to the ground, the ground control station integrates, preprocesses and stores the inspection data in the database.

[0024] Preferably, in the personalized report generation and intelligent push step, a detailed inspection report is generated according to the data analysis results, and the report content is personalized according to the user role and requirements.

[0025] Preferably, in the autonomous flight and adaptive data acquisition step, the UAV takes off automatically according to the flight path, and the flight control system monitors and controls the flight state in real time.

[0026] The present invention provides a UAV inspection system and method for power transmission, transformation and distribution equipment by improvement. Compared with the prior art, it has the following improvements and advantages:

[0027] First: In the present invention, the ultra-lightweight and high-strength composite fuselage of the UAV flight platform is constructed by using nano-enhanced carbon fiber composite materials, and the surface is coated with an intelligent adaptive coating, which not only ensures the strength and lightweight of the fuselage, but also can automatically adjust the optical and physical properties according to the external environment, improving the flight stability and safety of the UAV in complex environments. The omnidirectional intelligent flight control system integrates a multi-sensor fusion navigation and positioning system, including a variety of sensors, which can achieve precise navigation and positioning and flight control, further improving the flight reliability and reducing the risk of flight accidents.

[0028] Second: In the present invention, the high-resolution multi-spectral imaging system includes visible light, infrared thermal imaging, ultraviolet imaging, hyperspectral imaging, as well as lidar and spectral analysis modules, which can comprehensively detect the power transmission, transformation and distribution equipment from multiple angles. For example, infrared thermal imaging can detect temperature anomalies of the equipment, and ultraviolet imaging can discover problems such as corona discharge. By comprehensively analyzing these multi-spectral data, potential faults and defects of the equipment can be more accurately identified, providing a reliable basis for the maintenance and management of the equipment.

[0029] Thirdly: In the present invention, the data transmission and communication module adopts a quantum encryption wireless communication network and an edge intelligent data processing unit. The quantum encryption technology ensures the security of data transmission. The multi-band and multi-channel adaptive networking technology improves the stability and efficiency of communication. The edge intelligent data processing unit integrates a deep learning chip, a graphics processing unit, and a field programmable gate array, which can perform real-time processing and analysis of the collected data locally, reducing the pressure and latency of data transmission, realizing real-time data processing and edge decision-making, and improving the efficiency and response speed of the inspection.

[0030] Fourthly: In the present invention, the immersive virtual inspection command center of the ground control station and the big data-driven power equipment health management platform, combined with the drone inspection system, realize intelligent equipment management. The big data-driven power equipment health management platform adopts Ceph distributed storage technology and cloud computing technology with no less than 10 computing nodes. Based on at least 5000 groups of historical inspection data of power equipment, a health status evaluation model is constructed, which can accurately evaluate and predict the health status of power equipment. At the same time, the personalized report generation and intelligent push function customize inspection reports according to user roles and needs, providing more targeted decision-making support for equipment management personnel, helping to optimize the equipment maintenance plan and resource allocation, and improving the operation efficiency and reliability of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The present invention will be further explained below with reference to the drawings and embodiments:

[0032] Figure 1 is a flow diagram of the present invention;

[0033] Figure 2 is a flow diagram of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0034] The present invention will be described in detail below. The technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] The present invention provides a drone inspection system and method for transmission and distribution power equipment by improvement. The technical solution of the present invention is as follows:

[0036] Such as Figure 1 - Figure 2As shown, a UAV inspection system and method for power transmission, transformation and distribution equipment includes a UAV flight platform, a high-resolution multi-spectral imaging system, a data transmission and communication module, a quantum encryption wireless communication network module, an edge intelligent data processing unit, a ground control station and a UAV inspection method for power transmission, transformation and distribution equipment;

[0037] The UAV flight platform includes an ultra-lightweight, high-strength composite fuselage and an omnidirectional intelligent flight control system;

[0038] The ultra-lightweight, high-strength composite fuselage is constructed of nano-reinforced carbon fiber composite materials, and the surface is coated with an intelligent adaptive coating that can automatically adjust the optical and physical properties according to the external environmental conditions. It is constructed of nano-reinforced carbon fiber composite materials, which have an extremely high strength-to-weight ratio. While ensuring that the fuselage strength is sufficient to cope with various stresses during flight, it greatly reduces the weight of the fuselage, thereby reducing the energy consumption of the drone and extending the flight time. The intelligent adaptive coating coated on the surface is a highlight. It can keenly sense changes in external environmental conditions, such as light intensity, temperature, humidity, etc. When the light is too strong, the coating can adjust its optical properties to reduce reflections and avoid affecting the shooting effect of the imaging system; in severe weather conditions, the coating can change the physical properties, enhance the waterproof, dustproof and corrosion-resistant capabilities of the fuselage, and ensure that the drone can still fly stably in complex environments;

[0039] The omnidirectional intelligent flight control system integrates a multi-sensor fusion navigation and positioning system. The multi-sensor fusion navigation and positioning system includes an inertial measurement unit, a global positioning system, a laser altimeter, a visual sensor, a geomagnetic sensor, a barometric pressure sensor, and a microwave radar. It is the key to achieving precise flight of drones. Among them, the inertial measurement unit can measure the acceleration and angular velocity of the drone in real time, providing accurate data for adjusting the flight attitude; the global positioning system can provide accurate geographic location information of the drone to ensure that it flies according to the predetermined route; the laser altimeter can accurately measure the distance between the drone and the ground or target object to avoid collision; the visual sensor can identify obstacles and target objects in the surrounding environment to assist navigation; the geomagnetic sensor is used to determine the heading of the drone; the barometric pressure sensor can measure the atmospheric pressure and then calculate the flight altitude; the microwave radar can monitor the objects around the drone in real time in complex environments and provide more comprehensive environmental information. Through the fusion of multiple sensors, the flight control system can dynamically adjust the flight attitude and route according to real-time data to achieve omnidirectional, flexible and safe flight.

[0040] The high-resolution multispectral imaging system includes visible light, infrared thermal imaging, ultraviolet imaging, hyperspectral imaging, lidar, and spectral analysis modules. The high-resolution multispectral imaging system is the core device for obtaining detailed information of power equipment. It includes visible light, infrared thermal imaging, ultraviolet imaging, hyperspectral imaging, lidar, and spectral analysis modules. The visible light imaging module can provide clear images of the equipment's appearance, facilitating the staff to directly observe the surface condition of the equipment, such as whether there are damages, deformations, etc. The infrared thermal imaging module can detect the temperature distribution on the surface of the equipment. By analyzing the temperature abnormal points, potential faults inside the equipment, such as overheating, short circuit, etc., can be discovered in a timely manner. The ultraviolet imaging module can detect the corona discharge phenomenon on the surface of the equipment. Corona discharge is an important manifestation of the decline in the insulation performance of the equipment. Discovering corona discharge in a timely manner helps prevent the occurrence of equipment failures. The hyperspectral imaging module can obtain the reflection information of the equipment in multiple spectral bands. By analyzing the spectral characteristics, a deeper understanding of the equipment's material and state can be achieved. Lidar can accurately measure the three-dimensional shape and position information of the equipment, providing accurate spatial data for subsequent data analysis and processing. The spectral analysis module can conduct a detailed analysis of the collected spectral data to further explore potential problems of the equipment;

[0041] The data transmission and communication module includes a quantum encryption wireless communication network and an edge intelligent data processing unit. The data transmission and communication module is the bridge connecting the drone and the ground control station. It includes a quantum encryption wireless communication network and an edge intelligent data processing unit. The quantum encryption wireless communication network is established based on quantum encryption technology. Quantum encryption technology has extremely high security and can effectively prevent data from being stolen or tampered with during transmission. Adopting multi-band and multi-channel adaptive networking technology, this network can automatically select the optimal frequency band and channel for data transmission according to the actual environmental conditions, ensuring the stability and efficiency of data transmission. The edge intelligent data processing unit integrates a deep learning chip, a graphics processing unit, and a field programmable gate array, and can perform preliminary processing and analysis of the collected data locally on the drone. Through the powerful computing capabilities of the deep learning chip and the graphics processing unit, the feature extraction and recognition of data can be quickly completed; the field programmable gate array can be flexibly configured according to different task requirements to achieve efficient data processing and transmission;

[0042] The quantum encryption wireless communication network module is built based on quantum encryption technology and adopts multi-band and multi-channel adaptive networking technology. The edge intelligent data processing unit integrates deep learning chips, graphics processors and field programmable gate arrays. The edge intelligent data processing unit integrates deep learning chips, graphics processors and field programmable gate arrays, and has powerful data processing and analysis capabilities. The deep learning chip is specifically used to run deep learning algorithms, which can quickly and accurately extract and classify the collected multispectral image data. The graphics processor is good at processing large-scale image and video data, which can accelerate the image processing and analysis process. The field programmable gate array can be flexibly configured according to different task requirements to achieve efficient processing and transmission of data. During the drone inspection process, the edge intelligent data processing unit can process and analyze the collected data in real time, and use deep learning models for fault identification and diagnosis. For example, by analyzing infrared thermal imaging data, the overheating area of ​​the equipment can be identified; by analyzing visible light images, the appearance defects of the equipment can be detected. This real-time processing and analysis capability can greatly reduce the amount of data transmission and improve inspection efficiency.

[0043] The ground control station includes an immersive virtual inspection command center and a big data-driven power equipment health management platform. The ground control station is the command center of the entire drone inspection system, including an immersive virtual inspection command center and a big data-driven power equipment health management platform. The immersive virtual inspection command center uses virtual reality technology to provide operators with a realistic inspection environment. Operators can wear virtual reality equipment to experience the flight process of the drone and the situation on the inspection site, and obtain inspection data and image information in real time. This immersive experience can greatly improve the decision-making efficiency and accuracy of operators. The big data-driven power equipment health management platform is based on massive historical inspection data of power equipment and uses advanced data analysis and mining technology to comprehensively evaluate and predict the health status of power equipment. By establishing a health status assessment model, the platform can warn of equipment failure risks based on real-time inspection data, providing a scientific basis for equipment maintenance and management.

[0044] Furthermore, for the big data-driven power equipment health management platform of the ground control station, its distributed storage adopts the Ceph distributed storage technology. The number of computing nodes in the cloud computing technology is not less than 10. The health status assessment model is based on at least 5,000 groups of historical inspection data of power equipment. The Ceph distributed storage technology features high scalability, high reliability, and high performance. For the UAV inspection system of power transmission, transformation, and distribution equipment, as the inspection tasks increase, the amount of generated data will continuously grow. Ceph can easily expand the storage capacity to meet the storage requirements of massive inspection data. At the same time, its distributed architecture enables data to be stored on multiple nodes. Even if some nodes fail, it will not affect the normal operation of the entire storage system, ensuring the security and integrity of the data. In addition, Ceph has high-performance data reading and writing capabilities, which can quickly respond to the data access requests of the ground control station, improving the efficiency of data processing and analysis. A large number of computing nodes provide powerful computing capabilities. When processing the multi-spectral imaging data obtained from UAV inspections, conducting complex deep learning model training, and performing operations on the health status assessment model, sufficient computing resources can significantly shorten the processing time. For example, when performing real-time analysis on high-resolution images and a large amount of sensor data, multiple computing nodes can process tasks in parallel, accelerating the data processing speed, enabling the ground control station to obtain analysis results in a timely manner, and providing faster support for the fault diagnosis and maintenance decision-making of power equipment. Abundant historical inspection data provides sufficient learning samples for the health status assessment model. The model can learn the characteristics and laws of power equipment in different operating states from these data, thereby more accurately assessing the current health status of the equipment. A large amount of data can cover more equipment fault scenarios and abnormal situations, improving the generalization ability of the model and reducing the probability of misjudgment and missed judgment. This helps to detect potential faults of power equipment in advance, provide a reliable basis for the preventive maintenance of the equipment, and reduce the losses caused by equipment failures.

[0045] Furthermore, a UAV inspection method for power transmission, transformation, and distribution equipment includes a pre-inspection preparation step, a flight inspection step, and a post-inspection data processing and report generation step;

[0046] The flight inspection step includes autonomous flight and adaptive data collection, as well as real-time data processing and edge decision-making;

[0047] The post-inspection data processing and report generation step includes data integration and in-depth mining analysis, as well as personalized report generation and intelligent push.

[0048] Furthermore, in the device initialization and data synchronization step, the ground control station synchronizes the data related to the inspection task to the local storage device of the UAV, and conducts a comprehensive self-check on the flight control system and the data transmission and communication module. Data synchronization ensures that the UAV can accurately obtain the inspection task information during flight and work according to the predetermined plan, avoiding inspection errors caused by inconsistent data. The comprehensive self-check can detect potential problems in the flight control system and the data transmission and communication module in advance. For example, if a certain sensor in the flight control system fails, it can be detected and repaired or adjusted in a timely manner during the self-check process, thus ensuring the stability and safety of the UAV during flight. At the same time, the self-check on the data transmission and communication module can ensure that data can be transmitted accurately and stably, providing guarantee for subsequent data processing and analysis.

[0049] Furthermore, in the intelligent flight path planning and task allocation step, the operator formulates the initial inspection flight path at the ground control station. The platform prioritizes the inspection tasks according to the power equipment information and reasonably allocates resources. The operator formulating the initial inspection flight path can consider actual geographical environment, equipment distribution and other factors to ensure the rationality and feasibility of the flight path. The platform prioritizing the inspection tasks according to the power equipment information can give priority to inspecting important equipment with potential fault risks, improving the inspection efficiency and pertinence. Reasonably allocating resources can, according to factors such as the flight ability and load capacity of the UAV, allocate appropriate inspection tasks to each UAV, avoiding resource waste and giving full play to the role of the UAV, so as to complete more inspection work under limited time and resource conditions.

[0050] Furthermore, in the real-time data processing and edge decision-making step, the edge artificial intelligence data processing unit processes and analyzes the data in real time, and uses deep learning models for fault identification and diagnosis. Real-time data processing and analysis can process the data immediately after the UAV collects it, reducing the delay of data transmission. The edge artificial intelligence data processing unit processes the data locally without transmitting a large amount of data back to the ground control station, reducing the pressure and risk of data transmission. Using deep learning models for fault identification and diagnosis can give full play to the advantages of deep learning in processing complex data and pattern recognition, and more accurately identify faults and abnormal conditions of power equipment. Once a problem is found, it can make decisions in a timely manner, such as adjusting the flight attitude of the UAV to conduct a more detailed inspection of the faulty equipment, improving the timeliness and accuracy of fault discovery.

[0051] Further, in the data integration and in-depth mining and analysis step, after the UAV returns to the ground, the ground control station integrates, preprocesses and stores the inspection data into the database. Data integration can uniformly manage different types of inspection data, such as visible light images, infrared thermal imaging data, hyperspectral data, etc., facilitating subsequent analysis and query. Preprocessing can remove noise and invalid information in the data, improve the quality and usability of the data, and store the processed data in the database, providing rich data resources for subsequent in-depth mining and analysis. By deeply mining a large amount of data in the database, potential laws and trends of equipment failures can be discovered, providing more valuable information for the long-term maintenance and management of power equipment.

[0052] Further, in the personalized report generation and intelligent push step, a detailed inspection report is generated according to the data analysis results. The content of the report is customized according to the user roles and needs. The personalized report can meet the needs of different users. For equipment management personnel, the report can provide macroscopic information such as the overall health status of the equipment and the maintenance plan, helping them make decisions and allocate resources. For technical personnel, the report can provide more detailed technical information such as fault analysis, diagnosis results and maintenance suggestions, facilitating them to handle faults and maintain equipment. The intelligent push function can ensure that relevant personnel can obtain the inspection reports related to their work in a timely manner, improve the efficiency of information transmission, enable them to make quick responses and take corresponding measures.

[0053] Further, in the autonomous flight and adaptive data acquisition step, the UAV takes off automatically according to the flight route, and the flight control system monitors and controls the flight state in real time. The automatic takeoff of the UAV according to the flight route reduces the complexity and uncertainty of manual operation, improving the accuracy and safety of takeoff. The flight control system monitoring and controlling the flight state in real time can ensure that the UAV maintains a stable attitude and flight trajectory during flight, avoiding deviation from the flight route due to external interference. At the same time, according to the flight state and the position of the target equipment, data is adaptively acquired, which can ensure that the acquired data is representative and accurate, improving the quality of inspection data and providing a reliable basis for subsequent fault diagnosis and analysis.

[0054] The above description enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An unmanned aerial vehicle (UAV) inspection system and method for power transmission, transformation and distribution equipment, including a UAV flight platform, a high-resolution multi-spectral imaging system, a data transmission and communication module, the quantum encryption wireless communication network module, an edge intelligent data processing unit, a ground control station and a UAV inspection method for power transmission, transformation and distribution equipment, characterized in that: The UAV flight platform includes an ultra-lightweight high-strength composite fuselage and an omnidirectional intelligent flight control system; The ultra-lightweight high-strength composite fuselage is constructed of nano-enhanced carbon fiber composite materials, and the surface is coated with an intelligent adaptive coating that can automatically adjust optical and physical properties according to external environmental conditions; The omnidirectional intelligent flight control system integrates a multi-sensor fusion navigation and positioning system, and the multi-sensor fusion navigation and positioning system includes an inertial measurement unit, a global positioning system, a laser altimeter, a vision sensor, a geomagnetic sensor, a barometric pressure sensor and a microwave radar; The high-resolution multi-spectral imaging system includes visible light, infrared thermal imaging, ultraviolet imaging, hyperspectral imaging, lidar and spectral analysis modules; A data transmission and communication module, the data transmission and communication module includes a quantum encryption wireless communication network and an edge intelligent data processing unit; The quantum encryption wireless communication network module is established based on quantum encryption technology and adopts an adaptive networking technology with multiple frequency bands and multiple channels; The edge intelligent data processing unit integrates a deep learning chip, a graphics processor and a field programmable gate array; The ground control station includes an immersive virtual inspection command center and a big data-driven power equipment health management platform.

2. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 1, characterized in that: For the big data-driven power equipment health management platform of the ground control station, its distributed storage adopts Ceph distributed storage technology, the number of computing nodes in cloud computing technology is not less than 10, and the health status evaluation model is based on at least 5,000 groups of historical inspection data of power equipment.

3. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 1, characterized in that: A UAV inspection method for power transmission, transformation and distribution equipment includes pre-inspection preparation steps, flight inspection steps, and post-inspection data processing and report generation steps; The pre-inspection preparation steps include equipment initialization and data synchronization, as well as intelligent flight path planning and task allocation; The flight inspection steps include autonomous flight and adaptive data collection, as well as real-time data processing and edge decision-making; The post-inspection data processing and report generation steps include data integration and in-depth mining analysis, as well as personalized report generation and intelligent push.

4. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 3, characterized in that: In the equipment initialization and data synchronization step, the ground control station synchronizes the inspection task-related data to the local storage device of the UAV, and conducts a comprehensive self-inspection on the flight control system and the data transmission and communication module.

5. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 3, characterized in that: In the intelligent flight path planning and task allocation step, the operator formulates an initial inspection flight path at the ground control station, and the platform prioritizes the inspection tasks according to the power equipment information and reasonably allocates resources.

6. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 3, characterized in that: In the real-time data processing and edge decision-making step, the edge artificial intelligence data processing unit processes and analyzes the data in real time, and uses a deep learning model for fault identification and diagnosis.

7. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 3, characterized in that: In the data integration and in-depth mining and analysis step, after the UAV returns to the ground, the ground control station integrates, preprocesses, and stores the inspection data in the database.

8. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 3, characterized in that: In the personalized report generation and intelligent push step, a detailed inspection report is generated based on the data analysis results, and the content of the report is personalized according to the user roles and requirements.

9. The UAV inspection system and method for power transmission, transformation and distribution equipment according to claim 3, characterized in that: In the autonomous flight and adaptive data collection step, the UAV takes off automatically according to the flight route, and the flight control system monitors and controls the flight state in real time.

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