Unmanned aerial vehicle electric field monitoring system

Abstract

The invention discloses an unmanned aerial vehicle electric field monitoring system, and relates to the technical field of electric power inspection, and the system comprises an unmanned aerial vehicle platform module which employs a four-rotor or six-rotor unmanned aerial vehicle and carries a lightweight electric drive system to improve the cruising ability; the electric field monitoring module is used for collecting data in an electric field and converting the electric field intensity in the space into measurable electric signals; the data processing module is used for carrying out cleaning, fusion, analysis and early warning processing on the disordered data collected in the electric field; the positioning module is used for acquiring accurate position and attitude information of the unmanned aerial vehicle in real time, binding electric field monitoring data with a physical space, and providing a position reference for autonomous cruise and obstacle avoidance of the unmanned aerial vehicle; and the communication module is used for realizing bidirectional interaction between the unmanned aerial vehicle and the ground control terminal. According to the monitoring system, through unmanned monitoring, the terrain and space limitation can be broken through, the monitoring efficiency and precision are improved, the personnel safety risk is reduced, and the long-term operation and maintenance cost is reduced.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of electric power inspection, and particularly relates to a UAV electric field monitoring system. BACKGROUND

[0002] In an electric power system, a power frequency electric field is generated around facilities such as a power transmission line and a transformer substation, and when the intensity of the electric field exceeds a safety threshold, the environment, equipment and personnel around the facilities can be affected. A traditional electric field monitoring method mainly relies on fixed monitoring points or manual inspection by a handheld device, which not only reduces the inspection progress, but also increases the workload of the staff. Therefore, a UAV is needed to monitor the electric field.

[0003] A patent with the announcement number CN120756693A discloses a UAV power management and information monitoring system, which comprises a power management and information monitoring device connected between a UAV power supply, a UAV flight control and a UAV load set. The power management and information monitoring device is internally integrated with a unified power management module for receiving power from the UAV power supply and providing one or more transformed stable power supplies for the UAV load set, and an information and control hub module for relaying information and control between the UAV flight control and the UAV load set and sensors. The application aims to help solve the problems of complex flight control interfaces, heavy computation burden and low system integration and insufficient reliability caused by the scattered management of power supplies in existing UAV systems.

[0004] A patent with the announcement number CN117148007A discloses a UAV-based power grid fault monitoring system and relates to the field of electric power grid monitoring. The system comprises a UAV for flying to a high altitude and contacting a power grid. An electric shell is installed on the lower surface of the UAV, and the electric shell contains a data measurement module for measuring the diameter, length and snow thickness of the power lines in the power grid, and a data storage module for storing the collected data in a database. The data storage module has the functions of adding, deleting and modifying data, and can help users conveniently store data and provide data query and management functions. A hot air balloon is hung above the UAV, and a heat source is installed on the upper surface of the UAV. The heat source provides heat for the hot air balloon, which can prevent the UAV from shaking or falling in a high altitude with strong wind. A height detection module detects the flying height of the UAV and the height of the power lines to be detected. When the difference between the height of the UAV and the height of the power lines is within ±20 cm, a flight height suppression module is used to control the UAV to stay at the current height position.

[0005] For example, patent CN118348886A discloses a drone-based offshore wind farm inspection and monitoring system and method. It uses drone formations to autonomously inspect and collect data from the wind farm, the onboard system provides real-time diagnosis and early warning, interconnects with remote systems to achieve layered collaborative diagnosis, 5G network to transmit massive amounts of data, edge nodes to support real-time decision-making, and digital twins to perform refined assessment and predictive maintenance. It integrates multiple cutting-edge technologies to achieve fully automated intelligent monitoring, timely fault detection, and improve the reliability and economic benefits of wind farm operation, which has broad application prospects.

[0006] However, in the aforementioned monitoring systems, the flight systems of unmanned aerial vehicles (UAVs) are susceptible to interference from the external environment, such as radio signal interference and weather interference. Strong winds and heavy rain can disrupt the attitude estimation of the inertial navigation system, causing the UAV to experience turbulence, yaw, and obstacle avoidance delays, thus affecting the normal operation of the monitoring work. Therefore, there is an urgent need for an improved method for UAV monitoring systems. Summary of the Invention

[0007] The purpose of this invention is to provide an unmanned aerial vehicle (UAV) electric field monitoring system to solve the problem in the existing monitoring and drive systems described in the background art, where the UAV's flight system is easily affected by external environmental interference, such as wireless signal interference and weather interference. Strong winds and heavy rain can disrupt the attitude estimation of the inertial navigation system, causing the UAV to experience turbulence, yaw, and obstacle avoidance delays, thus affecting the normal operation of the monitoring work.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an unmanned aerial vehicle (UAV) electric field monitoring system, comprising:

[0009] The drone platform module uses a quadcopter or hexcopter drone and is equipped with a lightweight electric drive system to improve endurance. Its flight control system supports autonomous cruise, hovering and obstacle avoidance. It can perform monitoring tasks according to a preset path and can also be manually controlled through a ground control terminal.

[0010] The electric field monitoring module is used to collect data in the electric field, converting the electric field intensity in space into a measurable electrical signal, providing the original physical quantity basis for subsequent data processing and anomaly early warning;

[0011] The data processing module is used to clean, fuse, analyze, and provide early warnings for the messy data collected in the electric field, transforming meaningless raw data into monitoring results that can guide decision-making, while ensuring the real-time performance and reliability of the data.

[0012] The positioning module is used to acquire the precise position and attitude information of the UAV in real time, bind the electric field monitoring data with the physical space, and provide a position reference for the UAV's autonomous navigation and obstacle avoidance.

[0013] The communication module is used to realize two-way interaction between the UAV and the ground control terminal. It needs to transmit electric field monitoring data, UAV position and status information in real time, and receive flight control commands issued by the ground. At the same time, it must ensure the stability, real-time performance and security of the transmission, and perform anti-interference processing on the transmitted data.

[0014] The ground control terminal module is used to connect operators with the UAV system, realizing a closed loop of the entire process of command issuance, data reception, analysis and decision-making, and result output, solving the problems of how to control UAVs, how to interpret monitoring data, and how to implement operation and maintenance decisions.

[0015] Preferably, the UAV platform module includes a mission preparation phase, a takeoff and deployment phase, an autonomous cruise monitoring phase, an anomaly response phase, and a return and recovery phase. The mission preparation phase mainly involves equipment checks and parameter configuration, which can be divided into hardware assembly and status checks, flight parameters, and mission planning. The takeoff and deployment phase is mainly for accurate takeoff and arrival at the monitoring starting point, which can be divided into final calibration before takeoff and takeoff and initial cruise. The autonomous cruise monitoring phase is mainly for performing electric field data acquisition according to the plan, which can be divided into regular cruise and data acquisition linkage and environmental adaptation and dynamic adjustment. The anomaly response phase is mainly for dynamic handling of electric field anomalies or equipment failures, which can be divided into electric field anomaly response and equipment failure emergency handling. The return and recovery phase is mainly for the safe landing of the UAV and completion of data handover, which includes autonomous return, landing, and data processing.

[0016] Preferably, the electric field monitoring module includes a preparation stage, a real-time acquisition stage, a data output and interaction stage, and a post-task maintenance stage.

[0017] Preferably, the data processing module includes a data receiving and parsing stage, a data preprocessing stage, a data fusion stage, a real-time analysis and early warning stage, and a data output and storage stage. The data receiving and parsing stage is used to acquire and standardize multi-source raw data; the data preprocessing stage is used to filter noise and correct errors to ensure data accuracy; the data fusion stage is used to bind spatiotemporal information and construct a location and electric field related dataset; the real-time analysis and early warning stage is used to identify anomalies and trigger responses to support rapid decision-making; and the data output and storage stage is used to adapt for transmission and archiving to support subsequent applications.

[0018] Preferably, the data receiving and parsing stage includes real-time reception of multi-source data and data format parsing and verification; the data preprocessing stage includes outlier removal and noise filtering, and environmental and system error correction; the data fusion stage includes spatiotemporal alignment and data association, and multi-dimensional data supplementation and fusion; the real-time analysis and early warning stage includes electric field anomaly identification and classification, early warning triggering and linkage response; and the data output and storage stage includes data format adaptation and transmission, local caching and archiving.

[0019] Preferably, the positioning module includes an initialization and calibration phase, a real-time positioning and fusion phase, a location output and interaction phase, and an anomaly handling and calibration phase.

[0020] Preferably, the initialization and calibration phase includes module power-on and hardware self-test, scene adaptation and parameter configuration; the real-time positioning and fusion phase includes multi-source positioning data acquisition, multi-source data fusion and optimization; the location output and interaction phase includes standardized location data output, waypoint triggering and collaborative control; and the anomaly handling and calibration phase includes positioning anomaly detection and response, post-task calibration and data review.

[0021] Preferably, the communication module includes an initialization and connection establishment phase, a bidirectional data transmission phase, a dynamic mode switching and environment adaptation phase, and an exception handling and post-task completion phase. The initialization and connection establishment phase includes module power-on and hardware self-test, communication parameter configuration and connection establishment. The bidirectional data transmission phase includes uplink data transmission and downlink data transmission. The dynamic mode switching and environment adaptation phase includes communication quality monitoring and mode switching, anti-interference and power consumption adaptation. The exception handling and post-task completion phase includes communication exception detection and emergency response, post-task data retransmission and module maintenance.

[0022] Preferably, the ground control terminal module includes a pre-mission preparation stage, a mission monitoring stage, and a post-mission analysis stage.

[0023] Preferably, the pre-task preparation stage includes system initialization and device connection, task parameter configuration and path planning; the in-task monitoring stage includes real-time reception and display of multi-dimensional data, anomaly monitoring and dynamic response; and the post-task analysis stage includes data review and in-depth analysis, report generation and business linkage.

[0024] Preferably, the hardware heat dissipation structure includes a high thermal conductivity interface material, a lightweight heat dissipation structure, a heat pipe or a vapor chamber, and the auxiliary heat dissipation design includes structural layout optimization, temperature monitoring and intelligent control, and material surface treatment.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] 1. By setting an anti-interference mode, the system can actively resist or weaken the impact of external interference on the system, ensuring accurate electric field monitoring data, stable drone flight, and reliable communication links. This avoids data distortion, equipment failure, or mission interruption caused by interference, guarantees the accuracy of electric field monitoring data, avoids measurement distortion caused by interference, ensures the stability of the drone flight control system, avoids safety risks caused by interference, maintains reliable communication links, avoids data transmission interruption or errors caused by interference, and enables the drone to adapt to complex monitoring scenarios, thus expanding the system's applicability.

[0027] 2. After the drone returns to base, data processing is performed. By safely recovering the equipment, completing the data chain, mining the value of the data, optimizing subsequent tasks, and reducing labor costs, the drone electric field monitoring is upgraded from simple flight data collection to a complete service that can support operation and maintenance decisions. This avoids the problem of focusing only on the process and not the result. It is the core support for the system to realize the monitoring-analysis-operation and maintenance closed loop. At the same time, it can optimize the next flight and data collection parameters and continuously improve monitoring efficiency.

[0028] 3. Unmanned monitoring can overcome terrain and spatial limitations, improve monitoring efficiency and accuracy, reduce personnel safety risks, and lower long-term operation and maintenance costs. Attached Figure Description

[0029] Fig. 1 This is a schematic diagram of the overall monitoring system of the present invention.

[0030] Fig. 2 This is a schematic diagram of the monitoring method of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] This application provides an embodiment of an unmanned aerial vehicle (UAV) electric field monitoring system, including:

[0033] The drone platform module uses a quadcopter or hexcopter drone and is equipped with a lightweight electric drive system to improve endurance. Its flight control system supports autonomous cruise, hovering and obstacle avoidance. It can perform monitoring tasks according to a preset path and can also be manually controlled through a ground control terminal.

[0034] The electric field monitoring module is used to collect data in the electric field, converting the electric field intensity in space into a measurable electrical signal, providing the original physical quantity basis for subsequent data processing and anomaly early warning;

[0035] The data processing module is used to clean, fuse, analyze, and provide early warnings for the messy data collected in the electric field, transforming meaningless raw data into monitoring results that can guide decision-making, while ensuring the real-time performance and reliability of the data.

[0036] The positioning module is used to acquire the precise position and attitude information of the UAV in real time, bind the electric field monitoring data with the physical space, and provide a position reference for the UAV's autonomous navigation and obstacle avoidance.

[0037] The communication module is used to realize two-way interaction between the UAV and the ground control terminal. It needs to transmit electric field monitoring data, UAV position and status information in real time, and receive flight control commands issued by the ground. At the same time, it must ensure the stability, real-time performance and security of the transmission, and perform anti-interference processing on the transmitted data.

[0038] The ground control terminal module is used to connect operators with the UAV system, realizing a closed loop of the entire process of command issuance, data reception, analysis and decision-making, and result output, solving the problems of how to control UAVs, how to interpret monitoring data, and how to implement operation and maintenance decisions.

[0039] In order to better understand the above technical solutions, the following will describe the above technical solutions in detail with reference to the accompanying drawings and specific embodiments. Figs. 1-2 As shown in this embodiment of the present application, a drone electric field monitoring system includes the following monitoring methods:

[0040] S1, select the drone platform module, which can be a quadcopter or a hexcopter drone, equipped with a lightweight electric drive system to improve endurance;

[0041] In this application, it should be noted that because the UAV platform module includes the mission preparation phase, takeoff and deployment phase, autonomous cruise monitoring phase, anomaly response phase, and return and recovery phase, and the mission preparation phase mainly involves equipment inspection and parameter configuration, which can be divided into hardware assembly and status inspection, flight parameters and mission planning; the takeoff and deployment phase is mainly for accurate takeoff and arrival at the monitoring starting point, which can be divided into final calibration before takeoff and takeoff and initial cruise; the autonomous cruise monitoring phase is mainly for performing electric field data collection according to the plan, which can be divided into regular cruise and data collection linkage and environmental adaptation and dynamic adjustment; the anomaly response phase is mainly for dynamic handling of electric field anomalies or equipment failures, which can be divided into electric field anomaly response and equipment failure emergency handling; and the return and recovery phase is mainly for the safe landing of the UAV and completion of data handover, which includes autonomous return, landing and data processing, preparation work needs to be done before the UAV takes off.

[0042] S2, System Deployment: Install the electric field monitoring module, data processing module, positioning module, and communication module in the corresponding positions on the selected UAV fuselage.

[0043] In this application, it should be noted that the electric field monitoring module includes a preparation phase, a real-time acquisition phase, a data output and interaction phase, and a post-mission maintenance phase. The preparation phase primarily involves module initialization and environmental adaptation, which can be divided into hardware power-on and self-test, calibration and parameter configuration. The real-time acquisition phase mainly acquires electric field data synchronously with the UAV operation, including acquisition triggering, data acquisition, and signal preprocessing. The data output and interaction phase is used to transmit standardized data to other modules of the system, including analog-to-digital conversion and format encapsulation, data transmission and interaction. The post-mission maintenance phase is used for module inspection and data archiving, including module status inspection, data archiving, and module calibration. The data processing module includes a data receiving and parsing phase, a data preprocessing phase, and a data... The system comprises three phases: fusion, real-time analysis and early warning, and data output and storage. The data receiving and parsing phase acquires and standardizes multi-source raw data; the data preprocessing phase filters noise and corrects errors to ensure data accuracy; the data fusion phase binds spatiotemporal information to construct location and electric field-related datasets; the real-time analysis and early warning phase identifies anomalies and triggers responses to support rapid decision-making; and the data output and storage phase adapts for transmission and archiving to support subsequent applications. The data receiving and parsing phase includes real-time reception of multi-source data and data format parsing and verification; the data preprocessing phase includes outlier removal and noise filtering, and environmental and system error correction; and the data fusion phase includes spatiotemporal alignment and data association, multi-dimensional data supplementation and fusion, and real-time analysis and early warning. The analysis and early warning phase includes electric field anomaly identification and classification, early warning triggering and linkage response; the data output and storage phase includes data format adaptation and transmission, local caching and archiving; the positioning module includes initialization and calibration phase, real-time positioning and fusion phase, location output and interaction phase, and anomaly handling and calibration phase; the initialization and calibration phase includes module power-on and hardware self-test, scene adaptation and parameter configuration; the real-time positioning and fusion phase includes multi-source positioning data acquisition, multi-source data fusion and optimization; the location output and interaction phase includes standardized location data output, waypoint triggering and collaborative control; the anomaly handling and calibration phase includes positioning anomaly detection and response, post-mission calibration and data review; and the communication module includes initialization and connection establishment phase and bidirectional data transmission phase. The system comprises three phases: dynamic mode switching and environment adaptation, anomaly handling and post-mission cleanup, initialization and connection establishment (including module power-on and hardware self-test, communication parameter configuration and connection establishment), bidirectional data transmission (including uplink and downlink data transmission), dynamic mode switching and environment adaptation (including communication quality monitoring and mode switching, anti-interference and power consumption adaptation), and anomaly handling and post-mission cleanup (including communication anomaly detection and emergency response, post-mission data retransmission and module maintenance). The ground control terminal module includes a pre-mission preparation phase, an in-mission monitoring phase, and a post-mission analysis phase. The pre-mission preparation phase mainly involves configuring parameters and planning the mission to lay the foundation for monitoring. The in-mission monitoring phase is used for real-time data reception, status monitoring, and anomaly handling.The post-task analysis phase is used for data review, report generation, and business collaboration. The pre-task preparation phase includes system initialization and device connection, task parameter configuration, and path planning. The in-task monitoring phase includes real-time reception and display of multi-dimensional data, anomaly detection, and dynamic response. The post-task analysis phase includes data review and in-depth analysis, report generation, and business collaboration.

[0044] In practice, the electric field monitoring module (including the shielding shell) is first fixed to the belly of the UAV (center of gravity position to avoid flight imbalance) using a shock-absorbing bracket, ensuring that the sensor probe faces the monitoring target (such as the direction of the line). Then, the positioning module and communication module are installed according to the preset interface (such as the GPS antenna on the top of the fuselage facing upwards and the communication antenna unobstructed). The data processing module is then integrated with the UAV flight control system. Next, the equipment connection test is performed. The connection status of each module with the UAV flight control system is checked through the ground control terminal module—whether the electric field monitoring module outputs a signal normally (such as sending a 0kV / m calibration signal), whether the positioning module acquires satellite signals (GPS / BeiDou signal strength ≥30dB), and whether the communication module establishes a connection with the ground terminal. Then, the power system is checked, and the lightweight electric drive system is inspected (battery charge ≥80%, motors without jamming, propellers without cracks). The motor rotation and speed are tested through the flight control APP (to ensure that the quadcopter's forward and reverse rotation are matched to avoid yaw during flight).

[0045] In this embodiment, through system deployment, dispersed hardware modules, data links, and business requirements can be integrated into a collaborative closed-loop system, solving the shortcomings of traditional monitoring such as fragmentation, inefficiency, and high risk. System deployment, through standardized interfaces and collaborative logic, enables each module to form a seamless link of data acquisition, transmission, analysis, and decision-making, breaking down module fragmentation and achieving end-to-end collaboration, thus improving monitoring accuracy and real-time performance. A unified protocol (such as SPI or UART) deeply integrates the electric field monitoring module, data processing module, positioning module, communication module, and UAV flight control, ensuring that when the UAV flies to the monitoring point, the sensors synchronously acquire data, and the positioning is synchronously bound (time-space deviation ≤1ms), avoiding the traditional problem of data and location misalignment (e.g., a certain electric field data cannot correspond to a specific tower). The communication module and ground terminal are pre-configured with transmission parameters (e.g., priority). Transmitting abnormal data and automatically switching between Wi-Fi and 4G modes ensures that the electric field data (including real-time anomalies) collected by the drone can be transmitted to the ground within 100ms. The ground terminal simultaneously generates heat maps and early warnings. Compared with the traditional mode of exporting data after the drone returns to base, the response speed is improved by 10-20 times. The ground terminal can complete dynamic adjustments without manual intervention through the deployed linkage logic (such as automatically issuing hovering + encrypted sampling commands to the drone when a severe electric field anomaly is detected). This avoids missing key data due to delays caused by human operation. At the same time, it enables the drone to adapt to complex scenarios, achieve full environmental coverage, break through the traditional monitoring boundaries, reduce reliance on manual labor, realize semi-automatic / automatic operation and maintenance, improve work efficiency, and strengthen safety management through system deployment. It can also achieve early warning of risks and keep personnel away from danger, reducing safety hazards.

[0046] S3 performs flight parameter and mission planning, deploys the task of monitoring the electric field of the UAV, and performs final calibration before takeoff.

[0047] In practice, the monitoring area (such as the 220kV transmission line #100-#150 tower section) is first selected on the GIS map of the ground control terminal. The cruise path parameters are set, and then the flight mode is selected, which can be autonomous cruise (flying in the order of waypoints) or manual assistance (manual control of key areas). After the flight mode is selected, safety parameters are set, such as a minimum safe distance of ≥5m from power equipment (towers, conductors), automatic detour when encountering obstacles, 30% battery power reserved for return, and preset emergency commands such as one-click return and hovering standby, which are quickly bound to the ground terminal.

[0048] The final calibration steps before takeoff are as follows: First, place the UAV on a level surface and calibrate the accelerometer and gyroscope through the flight control system (to eliminate attitude errors caused by ground tilt), ensuring that the horizontal deviation is ≤ ±0.5° when hovering. In an open area, wait for the positioning module to complete satellite acquisition and positioning (GPS / BeiDou dual-mode positioning, ≥8 satellites, positioning accuracy ≤ ±0.5m). Record the takeoff point coordinates as the return reference point. Then, start the electric field monitoring module to preheat (especially in low-temperature environments, preheat for 5 minutes to ensure sensor stability). Check the real-time output electric field value through the ground terminal module (the initial environmental electric field should be stable without jumps).

[0049] In this embodiment, by using flight parameters and mission planning, and performing a final calibration before takeoff, the accuracy of the flight path can be ensured, avoiding missed or duplicate monitoring points and ensuring complete coverage. By pre-setting waypoints on the GIS map via the ground terminal (e.g., planning point by point along towers #100-#150) and setting flight spacing (e.g., 30m lateral distance from the conductor when flying parallel to the line, and one sampling point every 10m longitudinally), the target area (e.g., transmission line corridor, substation equipment area) can be accurately covered. This avoids missed detections caused by traditional manual operation based on experience (e.g., missing electric field monitoring near a certain tower). During planning, path optimization algorithms (e.g., shortest path, non-overlapping trajectory) ensure that the UAV cruises efficiently along the preset route. To avoid repeated flights over the same area (such as repeatedly flying over the same route due to memory bias during traditional manual control), reduce ineffective energy consumption (repeated flights increase endurance consumption by 30%-50%), ensure that a single mission covers more targets, and for key monitoring points (such as old towers or equipment that has previously experienced electric field anomalies), hovering sampling and densification parameters can be set during planning (e.g., hovering at tower #123 for 3 seconds and increasing the sampling frequency from 1Hz to 5Hz) to ensure that key areas obtain denser and more accurate electric field data, providing sufficient basis for subsequent defect analysis. Mission planning and pre-flight calibration can identify and avoid potential risks in advance, preventing drone collisions with equipment, loss of contact, or crashes, protecting equipment and personnel safety, and planning routes. When planning, a power facility database (including pole and tower locations, equipment dimensions, and safety distance thresholds) can be imported. The system automatically generates obstacle avoidance routes (such as maintaining a safety distance of ≥5m from poles and towers, and avoiding tall equipment in substations) to prevent collisions with equipment in blind spots during drone flight (the risk of such collisions is 15%-20% under traditional manual control). Emergency strategies can be preset in the flight parameters (such as automatic return when battery power is ≤30% or return along the original trajectory when communication is interrupted). Combined with the return reference point calibrated before takeoff (precisely locating the takeoff position), it ensures that the drone can safely return in case of emergencies (such as strong winds or signal loss) and avoids crashes. During planning, the drone's payload capacity (such as a maximum effective payload of 500g) can be matched with the target payload. The weight of the electric field monitoring module (e.g., 200g) should be controlled to avoid insufficient power due to overload (such as difficulty taking off or unstable flight attitude). Simultaneously, the load installation position should be calibrated (e.g., aligning the center of gravity with the fuselage center) to prevent flight tilting due to center of gravity shift (tilting will cause angular deviation of the electric field sensor, increasing measurement error by 10%-15%). During mission planning, the sampling frequency should be synchronously set to match the flight speed (e.g., 1Hz sampling frequency at a flight speed of 5m / s, ensuring one set of data is collected every 5m). Combined with the reference point coordinates calibrated by the positioning module before takeoff (e.g., latitude and longitude 116.3428°E, 39.8354°N), each set of electric field data can be accurately bound to the corresponding position (position deviation ≤ ±0).(5m), avoiding invalid data caused by traditional sampling and location misalignment (such as electric field data not corresponding to specific towers). During planning, the task ID, monitoring area, and parameter configuration (e.g., 20240610-#100-#150 towers-sampling frequency 1Hz) are recorded. Calibration data (such as zero electric field reference value and positioning deviation) are archived simultaneously. Subsequently, the acquisition parameters and calibration information of a certain set of electric field data can be quickly retrieved by the task ID, facilitating the review of causes when data anomalies occur (e.g., if the electric field exceeds the standard at a certain point, it can be checked whether the calibration was normal and whether the sampling frequency was compliant). During planning, the electric field monitoring module and positioning module are preset to trigger synchronously (e.g., electric field acquisition is automatically triggered when the sampling point is located). Combined with pre-flight sensor calibration (e.g., electric field sensor zero drift correction), the synchronization of electric field data, location data, and time data can be ensured. This provides an accurate data source for subsequent generation of electric field heat map anomaly point location markings, improving task execution efficiency and reducing manual intervention and time costs.

[0050] S4, takeoff and initial cruise, and after the initial cruise, enters regular cruise, linked with data acquisition, and performs environmental adaptation and dynamic adjustment;

[0051] In practice, the ground terminal first sends a takeoff command, and the UAV ascends vertically to a height of 5m and hovers. After confirming there is no significant drift, it cruises towards the first waypoint (e.g., tower #100) along a preset path. During the ascent, it transmits position and altitude data in real time (the ground terminal displays whether the trajectory deviates from the planned path). When it reaches within 50m of tower #100, the UAV automatically decelerates to 2m / s and adjusts its attitude (nose facing the line direction). Then, it waits for the ground terminal to confirm entry into monitoring mode (or automatically triggers monitoring mode). After entering monitoring mode, it begins regular cruise, which needs to be linked with data acquisition. Specifically, path tracking is performed first, with the UAV flying along the preset trajectory. The positioning module compares the current position with the planned path in real time (lateral / longitudinal deviation ≤ ±2m). The flight control system automatically adjusts the motor speed to correct the heading (e.g., the right motor accelerates when veering left). Then, electric field data is collected synchronously. At each sampling point (triggered by the positioning module), the UAV sends a collection command to the electric field monitoring module, which synchronously outputs X / Y / Z axis electric field intensity data (after signal conditioning). Binding to the current location coordinates (latitude, longitude, and altitude), the data is transmitted back to the ground terminal module via the communication module. Real-time status feedback is then implemented, sending UAV status data (battery level, flight speed, motor temperature, and operating status of each module) to the ground terminal once per second. The ground terminal module displays this data in real time and determines whether it is normal (e.g., a pop-up reminder when the battery level is below 30%). Environmental adaptation and dynamic adjustment include handling weather interference and signal obstruction. For weather interference, if encountering strong winds ≥8m / s, the flight control system automatically switches to wind-resistant mode—reducing the flight speed to 3m / s, increasing motor output power to maintain attitude stability, and simultaneously increasing the positioning frequency (from 1Hz to 5Hz) to avoid yaw. In light rain, the equipment's rain cover is activated, and the electric field monitoring module automatically enables the humidity compensation algorithm. For signal obstruction, when entering substations or dense forest areas (where GNSS signals are lost), the positioning module automatically switches to visual SLAM positioning. The UAV uses its camera to identify equipment outlines / tree features to correct its position (positioning accuracy ≤±1m), ensuring that the sampling point does not deviate from the target area.

[0052] In this embodiment, takeoff and initial cruise allow the UAV to smoothly transition from ground startup to monitoring operation, avoiding safety hazards caused by unstable attitude and path deviation after takeoff. The UAV first ascends vertically to a height of 5-10m and hovers, adjusting its balance using attitude parameters calibrated before takeoff (such as horizontal reference and motor speed matching) to ensure no significant drift (horizontal deviation ≤ ±0.5m) before entering cruise. This avoids attitude tilting caused by direct and rapid takeoff (tilt may cause the electric field sensor angle to shift, resulting in an initial data acquisition error exceeding 10%). During the initial cruise phase, the UAV flies at low speed (2-3m / s) towards the first monitoring waypoint along a preset path. The drone cruises at a speed 5 m / s lower than the normal cruising speed, constantly comparing the deviation between its current position and the planned path (e.g., whether the lateral deviation exceeds ±2 m). Minor yaws are corrected in advance (e.g., slight acceleration of the right motor to adjust the heading) to prevent accumulated deviations from causing deviations from the monitoring area during subsequent normal cruises (e.g., missing the #100 tower monitoring point). During the initial cruise, the operational status of each module is checked simultaneously (e.g., whether the electric field sensor is outputting signals normally, and whether the communication link is stably transmitting data). If a problem is found (e.g., no sensor data), the drone can be immediately hovered for troubleshooting to avoid entering normal cruises with faults (operating with faults may result in the loss of all data, requiring the mission to be re-executed). The drone cruises along the planned path. At the same time, the positioning module determines in real time whether it has reached the preset sampling point (e.g., 10m away from tower #100). Once it arrives, it immediately sends a collection command to the electric field monitoring module, realizing immediate sampling upon arrival. This ensures that each set of electric field data is accurately bound to the corresponding location (position deviation ≤ ±0.5m), avoiding data and location misalignment caused by traditional timed collection (e.g., fixed collection per second) (e.g., the drone has flown 5m past the target point during sampling). It can automatically adjust the collection frequency according to the cruising speed (e.g., 1Hz sampling frequency at a flight speed of 5m / s, ensuring one set of data is collected every 5m; automatically increasing to 2Hz when the speed drops to 2m / s to avoid data redundancy). At the same time, it can also focus on key areas (e.g., #123 Old Tower) Triggered encrypted data acquisition according to plan (frequency increased to 5Hz), which ensures that the data density meets the analysis requirements without wasting storage and bandwidth resources. After the data is collected, it is immediately compared with the preset threshold (such as electric field ≤5kV / m within the line safety distance). If an anomaly is found (such as electric field reaching 8kV / m at a certain point), the location is immediately marked and a second acquisition is triggered (two more sets of data are collected within 1 second) to eliminate accidental interference (such as instantaneous jumps caused by electromagnetic noise), ensure that the abnormal data is true and reliable, can dynamically respond to environmental interference, ensure that the monitoring task is not interrupted and the data is not invalid, optimize energy and resource allocation, extend the endurance and improve the work efficiency;

[0053] During data transmission, the anti-interference mode can actively resist or weaken the impact of external interference on the system, ensuring accurate electric field monitoring data, stable drone flight, and reliable communication links. This avoids data distortion, equipment failure, or mission interruption caused by interference. The electromagnetic shielding components in the anti-interference mode (such as nickel-plated carbon fiber shells and copper foil shielding layers) can block high-frequency electromagnetic radiation generated by substation GIS equipment, motors, etc., achieving a shielding effectiveness of 60-80dB, attenuating interference signals to their original levels. To prevent interference signals from entering the weak output of the electric field sensor, the measurement error is reduced from over ±10% to within ±2%. The power supply filtering unit in anti-interference mode can filter interference conducted from the UAV's power supply line (such as voltage spikes generated by motor start-stop), ensuring that the electric field monitoring module receives a stable DC power supply (voltage fluctuation ≤ ±0.1V). This avoids power supply interference causing increased zero drift of the sensor (e.g., zero drift increases from 0.1kV / m to 0.5kV / m), ensuring the consistency of long-term monitoring data. Some anti-interference modes integrate temperature, humidity, and electromagnetic intensity sensors, which can collect interference environment parameters in real time (such as power frequency electric field strength and ambient humidity in substations). Through preset algorithms, the electric field measurement value is dynamically compensated (e.g., the electric field value is corrected by 0.3% for every 10% increase in humidity), further offsetting the system error caused by environmental interference, ensuring the stability of the UAV flight control system, and avoiding safety risks caused by interference.

[0054] S5. During the monitoring process, emergency fault handling is required when dealing with abnormal electric field responses.

[0055] In practice, during the monitoring process, the electric field anomaly response (triggered by the data processing module or ground terminal) includes Level 1 anomaly (minor exceedance) and Level 2 anomaly (serious exceedance). Level 1 anomaly (minor exceedance) occurs when the electric field strength exceeds the threshold by 10%-20%. The drone hovers for 3 seconds according to preset instructions, performs 5 encrypted samplings, acquires multiple sets of electric field data at that point (excluding accidental interference), and takes high-resolution photos of the equipment. The data is then packaged and transmitted back to the ground terminal. Level 2 anomaly (serious exceedance) occurs when the electric field strength exceeds the threshold by more than 50%. The drone immediately stops patrolling, hovers 10m above the anomaly point, sends a severe anomaly alarm to the ground terminal, and simultaneously initiates an all-around scan (circling the anomaly point with a radius of 5m, collecting one set of data every 30°) to generate a local electric field distribution heat map to assist in locating the fault point (such as the location of insulator damage). Emergency handling for equipment failures includes communication interruption and power system failure. Communication interruption occurs when communication with the ground terminal is interrupted (no instructions are received for more than 10 seconds). The drone automatically executes the communication loss contingency plan—it continues flying 200m along the last received path. If communication is still not restored, it initiates autonomous return-to-home (returning to the takeoff point along the incoming trajectory). During the flight, it attempts to reconnect every 30 seconds. Power system failure is indicated by an abnormal motor speed; the flight control system immediately alarms and switches to redundancy mode (the hexacopter shuts down the faulty motor, and the remaining motors compensate for power). Simultaneously, it sends an emergency return-to-home request to the ground terminal, lowers its altitude to 50m, and returns via the shortest path. Autonomous return-to-home is triggered by completing all preset waypoint monitoring, battery level ≤30%, a return-to-home command from the ground terminal, and equipment failure (such as sensor offline). Meeting any of these conditions initiates the return-to-home process. The return path prioritizes following the incoming trajectory (reducing the risk of collisions in unfamiliar areas). The positioning module corrects the path in real time to ensure the return-to-home point deviation is ≤±3m. If an obstacle is encountered (such as a suddenly appearing construction crane), it automatically detours and replans the shortest path.

[0056] In this embodiment, emergency fault handling ensures the safety of the UAV equipment and prevents damage or crashes caused by malfunctions. If a motor's speed is abnormal (e.g., jamming or stopping), the emergency system immediately triggers a redundant power mode (e.g., the hexacoach shuts down the faulty motor, and the remaining motors compensate for the power), while simultaneously reducing the flight altitude (from 80m to 50m) and shortening the return distance to avoid fuselage tilting or crashes due to power imbalance. If both GNSS and SLAM positioning fail, the emergency system calls the IMU inertial measurement unit to calculate the position briefly (error ≤ 1m within 10 seconds), and simultaneously triggers hovering standby with audible and visual alarms. If positioning is not restored within 1 minute, the last known position is used. The system reverses the flight path to return to home, preventing the drone from blindly flying and colliding with equipment while without a location. If the battery level drops suddenly (e.g., a short circuit causing the battery to drop from 50% to 20%), the emergency system skips the regular cruise and immediately initiates the shortest path return to home. At the same time, it shuts down non-core modules (such as high-definition cameras and auxiliary sensors) and prioritizes power supply to flight control and communication systems to prevent the drone from being forced to land and be damaged due to battery depletion. If communication with the ground terminal is interrupted (e.g., due to signal blockage or interference), the emergency system automatically stores the real-time collected electric field data and positioning data to the drone's local SD card (maximum storage of 16GB, capable of storing approximately 1 million data sets) while reducing the sampling frequency (from 1Hz to 0Hz).5Hz) reduces storage pressure; after communication is restored, cached data is retransmitted in chronological order to avoid loss of critical data (such as abnormal electric field points) due to interruption. If the electric field monitoring module suddenly stops outputting data (e.g., sensor offline), the emergency system immediately marks the fault start time and location, and triggers the flight control to record the current flight path. After the mission is completed, the area where no data was collected can be deduced based on the flight path, facilitating subsequent supplementary measurements and avoiding large monitoring blind spots caused by sensor failure. If local cached data is corrupted due to SD card error, the emergency system initiates data backup and recovery (automatically backing up critical data to the flight control's built-in storage), and simultaneously sends a data corruption alarm to the ground terminal, prompting priority to retain successfully transmitted valid data (e.g., electric field data from 1 hour before the fault) to reduce overall data loss. If the UAV approaches power equipment (distance) due to obstacle avoidance failure (e.g., lidar failure) If the distance is ≤3m, the emergency system will immediately trigger emergency braking and reverse push-off, while simultaneously sending a collision warning to the ground terminal. If avoidance is still impossible, a protective landing will be initiated (e.g., forced landing in an open area) to avoid collisions with high-voltage equipment that could cause short circuits or power outages. If the drone malfunctions over residential areas (e.g., abnormal motor noise, smoke from the fuselage), the emergency system will prioritize forced landing in uninhabited areas (e.g., open ground, rooftops), while simultaneously sending danger warnings to nearby personnel via the ground terminal (e.g., SMS, audible and visual alerts) to prevent crashes that could injure people or damage property. If system malfunctions occur in a substation's strong electromagnetic field area (e.g., flight control malfunctions due to interference), the emergency system will immediately cut off power to non-essential modules (e.g., electric field sensors, communication modules), retaining only the core flight control functions, and simultaneously fly away from the area of ​​strong interference at the lowest possible speed (e.g., move to a location 50m away from the substation) to prevent the interference from escalating and causing the malfunction to worsen.

[0057] S6, after returning to base, will proceed with landing and data processing;

[0058] In practice, the drone hovers 10m above the takeoff point, fine-tunes its position using visual positioning (identifying ground markers), and then descends vertically to within ±0.5m. The motors are then shut off. After landing, the drone automatically uploads locally cached monitoring data (such as high-definition images not transmitted in real time) to the ground terminal. The ground terminal generates a mission completion report (including information such as monitored areas, number of anomalies, and battery consumption). Finally, all modules are disassembled, and the drone and monitoring equipment are inspected for damage (such as motor temperature and sensor appearance). Dust and moisture are cleaned from the equipment surfaces to prepare for the next mission.

[0059] In this embodiment, the UAV electric field monitoring system performs precise landing and systematic data processing after returning to base, which can realize a closed loop of safe mission completion and data value transformation. It not only ensures the safe recovery of UAV equipment, but also transforms the collected raw data into operational and maintenance information that can be implemented. Specifically, to ensure the safe recovery of UAV and reduce equipment damage and secondary risks, the UAV can achieve ±0 through visual positioning (identifying ground landing marks) + inertial measurement calibration.A 5m precision vertical landing avoids tilted landings caused by deviations in traditional manual control (such as one propeller touching the ground first, causing the motor shaft to bend). The hard landing failure rate is reduced from 15% to below 2%, preventing equipment damage due to loss of control upon landing after return. It also reduces the impact on the surrounding environment. Before landing, it automatically scans the landing point (e.g., for debris or personnel). If obstacles are detected (e.g., tools or cables on the ground), it immediately hovers and alerts the ground terminal, preventing the drone from colliding with objects (e.g., damaging power maintenance tools) or injuring personnel during landing. It is particularly suitable for scenarios with dense equipment and high personnel flow in substations. Post-return data processing can specifically address potential problems that may arise during flight. To address issues such as incomplete data transmission and cached data not being exported, and to ensure the completeness and usability of monitoring data, if communication interruptions occur during flight (e.g., weak signal in mountainous areas), resulting in some data (e.g., electric field data from towers #140-#150) being temporarily stored on a local SD card, this data can be quickly exported and retransmitted to the ground terminal via a wired connection (e.g., USB) upon return. This prevents blind spots in the monitoring area due to data gaps. The system automatically compares the theoretically collected data volume (e.g., 3600 data sets should be generated after 1 hour of cruise and 1Hz sampling) with the actual received data volume. If a missing data set is detected (e.g., only 3580 data sets were received), the missing time period (e.g., the 25th-30th minute) can be located. Combined with flight log analysis, it can be determined whether the issue stems from sensor malfunction or communication problems. Packet loss provides a basis for subsequent retesting or equipment maintenance. Abnormal data points caused by interference during flight (such as instantaneous electric field values ​​jumping to 500kV / m) are corrected using data repair algorithms after return (such as interpolation completion based on previous and subsequent data). Repair records are marked to ensure the final data is both complete and reliable, preventing outliers from affecting subsequent analysis. Electric field data is combined with GIS maps to generate two-dimensional / three-dimensional electric field heat maps (red marking areas exceeding limits, green marking normal areas), visually showing where the electric field is high and near which type of equipment (e.g., the electric field around the surge arrester on tower #123 shows point-like high values). Maintenance personnel can quickly locate wind [damage] without having to look at dry data. In high-risk areas, the system automatically calculates key indicators—for example, if a 10km monitoring line detects 3 instances of excessive electric field (maximum 12kV / m) and 2 suspected equipment defects (80% probability of insulator breakage)—and combines this data with equipment records (such as the operational years of equipment at the excessive points and historical defect records), it generates priority maintenance recommendations. This data directly connects to the maintenance work order system, comparing current data with historical data to analyze electric field trends (e.g., the electric field at tower #123 increased from 5kV / m to 8kV / m, a monthly average increase of 15%), determining the rate of equipment aging. This provides data support for preventative maintenance, avoids reactive repairs after a fault, optimizes subsequent task parameters, and accurately prepares for the next monitoring cycle.

[0060] In summary, using unmanned aerial vehicles (UAVs) for electric field monitoring can overcome terrain and spatial limitations, achieve full-scene coverage without blind spots, improve monitoring efficiency and accuracy, reduce human error and time costs, reduce personnel safety risks, enable unmanned operation away from high-risk areas, support real-time monitoring and early warning, achieve early detection and handling of faults, reduce long-term operation and maintenance costs, achieve efficient resource utilization, and can also be adapted to intelligent operation and maintenance, supporting long-term trend analysis and decision-making. It not only solves the shortcomings of traditional monitoring, but also provides a safer, more efficient, more economical and intelligent new solution for power system operation and maintenance, and is the mainstream development direction for future electric field monitoring and even power inspection.

[0061] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A drone electric field monitoring system, characterized in that, The electric field monitoring system includes: The drone platform module uses a quadcopter or hexcopter drone and is equipped with a lightweight electric drive system to improve endurance. Its flight control system supports autonomous cruise, hovering and obstacle avoidance. It can perform monitoring tasks according to a preset path and can also be manually controlled through a ground control terminal. The electric field monitoring module is used to collect data in the electric field, converting the electric field intensity in space into a measurable electrical signal, providing the original physical quantity basis for subsequent data processing and anomaly early warning; The data processing module is used to clean, fuse, analyze, and provide early warnings for the messy data collected in the electric field, transforming meaningless raw data into monitoring results that can guide decision-making, while ensuring the real-time performance and reliability of the data. The positioning module is used to acquire the precise position and attitude information of the UAV in real time, bind the electric field monitoring data with the physical space, and provide a position reference for the UAV's autonomous navigation and obstacle avoidance. The communication module is used to realize two-way interaction between the UAV and the ground control terminal. It needs to transmit electric field monitoring data, UAV position and status information in real time, and receive flight control commands issued by the ground. At the same time, it must ensure the stability, real-time performance and security of the transmission, and perform anti-interference processing on the transmitted data. The ground control terminal module is used to connect operators with the UAV system, realizing a closed loop of the entire process of command issuance, data reception, analysis and decision-making, and result output, solving the problems of how to control UAVs, how to interpret monitoring data, and how to implement operation and maintenance decisions.

2. The UAV electric field monitoring system according to claim 1, characterized in that: The UAV platform module includes a mission preparation phase, a takeoff and deployment phase, an autonomous cruise monitoring phase, an anomaly response phase, and a return and recovery phase. The mission preparation phase mainly involves equipment checks and parameter configuration, which can be divided into hardware assembly and status checks, flight parameters, and mission planning. The takeoff and deployment phase is mainly for accurate takeoff and arrival at the monitoring starting point, which can be divided into final calibration before takeoff and takeoff and initial cruise. The autonomous cruise monitoring phase is mainly for performing electric field data acquisition according to the plan, which can be divided into routine cruise and data acquisition linkage, and environmental adaptation and dynamic adjustment. The anomaly response phase is mainly for dynamic handling of electric field anomalies or equipment failures, which can be divided into electric field anomaly response and equipment failure emergency handling. The return and recovery phase is mainly for the safe landing of the UAV and completion of data handover, which includes autonomous return, landing, and data processing.

3. The UAV electric field monitoring system according to claim 1, characterized in that: The electric field monitoring module includes a preparation phase, a real-time acquisition phase, a data output and interaction phase, and a post-task maintenance phase.

4. The UAV electric field monitoring system according to claim 1, characterized in that: The data processing module includes a data receiving and parsing stage, a data preprocessing stage, a data fusion stage, a real-time analysis and early warning stage, and a data output and storage stage. The data receiving and parsing stage is used to acquire and standardize multi-source raw data; the data preprocessing stage is used to filter noise and correct errors to ensure data accuracy; the data fusion stage is used to bind spatiotemporal information and construct a location and electric field related dataset; the real-time analysis and early warning stage is used to identify anomalies and trigger responses to support rapid decision-making; and the data output and storage stage is used to adapt for transmission and archiving to support subsequent applications.

5. The UAV electric field monitoring system according to claim 4, characterized in that: The data receiving and parsing stage includes real-time reception of multi-source data and data format parsing and verification; the data preprocessing stage includes outlier removal and noise filtering, and environmental and system error correction; the data fusion stage includes spatiotemporal alignment and data association, and multi-dimensional data supplementation and fusion; the real-time analysis and early warning stage includes electric field anomaly identification and classification, early warning triggering and linkage response; and the data output and storage stage includes data format adaptation and transmission, local caching and archiving.

6. The UAV electric field monitoring system according to claim 1, characterized in that: The positioning module includes an initialization and calibration phase, a real-time positioning and fusion phase, a location output and interaction phase, and an anomaly handling and calibration phase.

7. The UAV electric field monitoring system according to claim 6, characterized in that: The initialization and calibration phase includes module power-on and hardware self-test, scene adaptation and parameter configuration; the real-time positioning and fusion phase includes multi-source positioning data acquisition, multi-source data fusion and optimization; the location output and interaction phase includes standardized location data output, waypoint triggering and collaborative control; and the anomaly handling and calibration phase includes positioning anomaly detection and response, post-task calibration and data review.

8. The UAV electric field monitoring system according to claim 1, characterized in that: The communication module includes an initialization and connection establishment phase, a bidirectional data transmission phase, a dynamic mode switching and environment adaptation phase, and an exception handling and post-task completion phase. The initialization and connection establishment phase includes module power-on and hardware self-test, communication parameter configuration and connection establishment. The bidirectional data transmission phase includes uplink data transmission and downlink data transmission. The dynamic mode switching and environment adaptation phase includes communication quality monitoring and mode switching, anti-interference and power consumption adaptation. The exception handling and post-task completion phase includes communication exception detection and emergency response, post-task data retransmission and module maintenance.

9. The UAV electric field monitoring system according to claim 1, characterized in that: The ground control terminal module includes a pre-mission preparation phase, a mission monitoring phase, and a post-mission analysis phase.

10. The UAV electric field monitoring system according to claim 9, characterized in that: The pre-task preparation phase includes system initialization and device connection, task parameter configuration and path planning; the in-task monitoring phase includes real-time reception and display of multi-dimensional data, anomaly monitoring and dynamic response; and the post-task analysis phase includes data review and in-depth analysis, report generation and business linkage.

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