Power transmission line distributed monitoring device and method supporting live installation of unmanned aerial vehicle

Abstract

The invention discloses a power transmission line distributed monitoring device and method supporting unmanned aerial vehicle live-line installation. The power transmission line distributed monitoring device comprises a main control module, a man-machine interaction-free module, a clamping mechanism driving module, a sensing module, a signal conditioning module, a data analysis module, a communication module, a time synchronization module and a power supply module. According to the invention, through the man-machine interaction module and the clamping mechanism driving module, the device can be installed and maintained on the power transmission line by the unmanned aerial vehicle in a live-line manner, and a complete technical link from unmanned aerial vehicle live-line installation to fault identification is constructed; the operation and maintenance convenience is greatly improved, and power supply interruption caused by power failure maintenance is avoided; an open-close type current sensor and a capacitive voltage sensor of the sensing module can accurately acquire electric signals of the line and can accurately identify faults of the power transmission line; the power module integrates a solar panel, an electricity taking CT and a large-capacity battery to form a hybrid energy supply system, and it is guaranteed that energy supply of the device is stable and reliable.

Description

Technical Field

[0001] This invention relates to the field of power transmission line fault monitoring technology, specifically to a distributed monitoring device and method for power transmission lines that supports live installation by unmanned aerial vehicles (UAVs). Background Technology

[0002] In the field of distributed fault monitoring for power transmission lines, with the increasing urgency of smart grids for real-time perception of line status, rapid and accurate fault location, and unmanned operation and maintenance, the application of unmanned aerial vehicle (UAV) live-line working technology in scenarios such as power transmission line inspection is gradually maturing, providing technical support for the intelligent deployment of fault monitoring devices. However, while distributed fault monitoring technology has made progress in functional modules such as sensing, energy harvesting, and communication, existing technologies still have certain shortcomings in terms of ease of installation and maintenance, device performance accuracy, and system coordination.

[0003] Firstly, in the installation and maintenance of distributed fault monitoring devices for transmission lines, existing technologies generally rely on manual tower climbing or insulated bucket trucks for power outage operations. This not only affects the reliability of power supply but also faces the dilemma of high risks, low efficiency, and high economic costs associated with high-altitude operations. Although there have been attempts to use drones to assist in hoisting or to cooperate with electric lifting devices, these solutions still require close-range manual operation or rely on pre-installed fixed structures. They have failed to achieve truly fully automated live-line installation by drones, resulting in a serious lack of convenience in the deployment of fault monitoring devices and making it difficult to meet the needs of unmanned operation and maintenance in modern smart grids.

[0004] Secondly, in terms of device performance, the existing fixed or simple open-type current sensors have poor installation flexibility. In particular, the closed magnetic core sensors have significantly reduced measurement accuracy due to the air gap and asymmetry introduced by the mechanical structure, making it difficult to capture high-frequency transient traveling wave signals and seriously affecting the accuracy of fault location.

[0005] In addition, the power acquisition module lacks wide current adaptive capability and cannot work effectively under low load; the communication and time synchronization module has insufficient accuracy, which also restricts the realization of multi-device collaborative positioning, making it difficult to guarantee the accuracy and reliability of fault monitoring.

[0006] Therefore, it is essential to design distributed monitoring devices and methods for power transmission lines that support live installation by drones. Summary of the Invention

[0007] The purpose of this invention is to provide a distributed monitoring device and method for power transmission lines that supports live-line installation by unmanned aerial vehicles (UAVs), thereby addressing the problems mentioned in the background art, such as the reliance on manual power outages for the installation and maintenance of distributed fault monitoring devices for power transmission lines, and the lack of fully automated live-line installation in existing UAV-assisted solutions leading to insufficient deployment convenience. It also addresses the issues of poor installation flexibility of existing current sensors, reduced measurement accuracy due to air gaps and asymmetries introduced by mechanical structures, and difficulty in capturing high-frequency transient traveling wave signals, which affects the accuracy of fault location. Furthermore, it resolves the problems of the lack of wide current adaptive capability in the energy harvesting module and insufficient accuracy of the communication and time synchronization modules, which restrict the collaborative positioning and fault monitoring accuracy and reliability of multiple devices.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] Firstly, a distributed monitoring device for power transmission lines supporting live installation by drones is provided, comprising a main control module, a drone interaction module, a clamping mechanism drive module, a sensing module, a signal conditioning module, a data analysis module, a communication module, a time synchronization module, and a power supply module. The main control module establishes real-time communication connections with the other modules through an internal high-speed bus, uniformly scheduling the work of each module. Specifically, it is responsible for receiving status feedback and data information from each module, sending control commands to each module, coordinating the timing of each module, and ensuring the orderly realization of the overall function of the device.

[0010] The UAV interaction module is used to realize the docking, locking and separation of the device and the UAV mounting host; the clamping mechanism drive module is used to realize the clamping docking, clamping and locking of the device and the wire, and separation during disassembly.

[0011] The sensing module includes an openable current sensor with a compensation coil, a capacitive voltage sensor, and a light intensity sensor. The openable current sensor is equipped with a three-stage compensated RC integrator. The compensation coil compensates for measurement errors caused by the mechanical structure through matching design of turns density, cross-sectional area, and included angle. The three-stage compensated RC integrator achieves accurate integration processing of wideband signals. The capacitive voltage sensor isolates and scales down high-voltage signals through a small capacitor, and a high input impedance buffer circuit is used at the front end to avoid signal attenuation. The light intensity sensor is used to monitor ambient light intensity and assist in the analysis and judgment of fault scenarios.

[0012] The signal conditioning module performs amplification, filtering, adaptive normalization, dynamic compensation, and wavelet packet feature enhancement on the original signal. The preamplifier increases the amplitude of weak signals, the bandpass filter extracts signals in the fault characteristic frequency band, adaptive normalization makes signals of different amplitudes comparable, dynamic compensation corrects distortion during signal transmission, and wavelet packet decomposition enhances the features of high-frequency transient signals, providing high-quality input for subsequent data analysis.

[0013] The data analysis module classifies signals through wavelet packet energy decomposition, feature vector construction, and feature ratio criterion. It obtains the energy distribution of each sub-band through wavelet packet energy decomposition, constructs feature vectors containing low-frequency, mid-frequency, and high-frequency energy, and uses feature ratio criterion to distinguish different signal types such as intrusive waveforms, power outage waveforms, and fault waveforms. The built-in sliding window statistical mechanism allows the classification threshold to be dynamically adjusted according to the operating conditions, ensuring the accuracy of classification.

[0014] The communication module includes a short-range control link and a long-range private network transmission link for command interaction and data uploading. The short-range control link enables command interaction with the UAV during the device installation phase, controlling the actions of each step of the installation process. The long-range private network transmission link uploads fault monitoring data to the operation and maintenance center, and CRC check and adaptive retransmission mechanism ensure the integrity and reliability of data transmission.

[0015] The time synchronization module uses a GNSS receiver and a temperature-compensated crystal oscillator to construct a dual clock source, providing a unified time reference. When the satellite signal is normal, the local crystal oscillator is synchronized with the satellite time through an internal phase-locked loop to ensure high-precision time synchronization. When the satellite signal is unavailable, it switches to the temperature-compensated crystal oscillator and uses an inter-node time correction algorithm to achieve short-term autonomous operation, ensuring the consistency of the time reference among multiple devices and providing an accurate time reference for fault location.

[0016] The power module integrates a solar panel, a power supply CT, and a large-capacity battery to form a hybrid power supply system that supports dynamic switching between multiple modes. The solar panel prioritizes power supply and charges the battery under sunlight conditions. The power supply CT draws energy from the high-voltage conductor when the line load meets the requirements. The large-capacity battery serves as an energy buffer and backup power source.

[0017] As a further technical solution of the present invention, the UAV interaction module integrates a mechanical guiding structure and an electromagnetic drive rigid locking mechanism;

[0018] The mechanical guide structure includes a tapered insert mounted on the mounting machine and a corresponding tapered groove mounted on the device;

[0019] The electromagnetically driven rigid locking mechanism includes a first electromagnet mounted on a mounting machine and a corresponding second electromagnet mounted on a device. The mounting machine also includes a driving mechanism that drives a locking pin. The locking pin extends into the device through an opening on the device. Both the driving mechanism and the locking pin are mounted on a mounting base, which is connected to the mounting machine.

[0020] As a further technical solution of the present invention, the clamping mechanism drive module includes a servo motor, a rotating shaft, a plurality of cam disks and a clamping assembly; one end of the rotating shaft is rotatably connected to the device housing, and the other end passes through the device housing and is driven and connected to the servo motor; the plurality of cam disks are axially fixedly connected to the rotating shaft, and the cam disk includes a cam platform set at the center and a cam groove formed by the cam platform and the side wall of the cam disk, and the trajectory directions of the cam platform and the cam groove are consistent;

[0021] The device housing is also fixedly connected to a limiting shaft. The clamping assembly includes a first clamping jaw, a second clamping jaw, and a clamping jaw, all rotatably connected to the limiting shaft, and their lower ends are all slidably connected in the cam groove. The power-taking CT is disposed inside the first clamping jaw, and the opening and closing current sensor is disposed inside the second clamping jaw.

[0022] The end of the rotating shaft near the servo motor is rectangular, and the shape of the servo motor drive connection end is adapted to the rectangle. The servo motor is mounted on the mounting machine.

[0023] As a further technical solution of the present invention, in the openable current sensor of the sensing module, the compensation coil is disposed at the end of the main coil to satisfy the compensation relationship:

[0024]

[0025] in, To compensate for the included angle of the coil, The included angle of the Rogowski coil. , These represent the turns density of the compensation coil and the turns density of the missing portion of the gap at the end of the Rogowski coil, respectively. To compensate for the cross-sectional area of ​​the coil, This represents the cross-sectional area of ​​the missing portion at the end of the Rogowski coil.

[0026] The transfer function of the three-stage compensated RC integrator is:

[0027]

[0028] in:

[0029]

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036] in, This is the input voltage signal for a three-stage compensated RC integrator. The output voltage signal of the three-stage compensated RC integrator. For complex frequency variables, These are the capacitor parameters of the three-stage compensated RC integrator, and G1, G2, G3, G4, and G5 are the conductances of the corresponding resistors of the three-stage compensated RC integrator.

[0037] Capacitive voltage sensors achieve high-voltage signal isolation and scaling through tiny capacitors, and are equipped with high input impedance buffer circuits and anti-interference filtering units at the front end;

[0038] The light intensity sensor converts ambient light intensity into an electrical signal through a photodiode array. After being corrected by temperature compensation and nonlinear correction circuits, it outputs standardized data.

[0039] As a further technical solution of the present invention, the processing flow of the signal conditioning module includes:

[0040] The first step is to amplify the input signal using a preamplifier;

[0041] The second step is to extract the target frequency band using a bandpass filter. The frequency response function of the filter is:

[0042]

[0043] in, For frequency, For the center frequency, For bandpass filters at frequency Frequency response at that location;

[0044] The third step is to perform fast adaptive normalization in the digital domain, using the following formula:

[0045]

[0046] in, It is a discrete signal sequence obtained by sampling. It is a normalized discrete signal. and These represent the mean and standard deviation within the sliding window, respectively. To prevent small constants with zero denominators;

[0047] The fourth step is to perform dynamic compensation based on the least mean square adaptive algorithm, with the following formula:

[0048]

[0049]

[0050]

[0051] in, This represents the output signal after compensation. This represents the normalized input signal sequence. This indicates the order of the adaptive filter. This represents the weighting coefficients of the k-th order filter at time n; Let be the error signal at time n. Let n be the desired signal at time n. Let μ be the weight vector at time n, and μ be the convergence factor.

[0052] The fifth step involves enhancing the features of the high-frequency abrupt change components through wavelet packet decomposition and outputting the processed signal to the main control module.

[0053] As a further technical solution of the present invention, the signal classification process of the data analysis module includes:

[0054] The first step is to normalize the input signal sequence. Perform wavelet packet energy decomposition and calculate the energy components of each subband:

[0055]

[0056] in, Let l represent the energy component of the k-th subband at the j-th level, where j is the level of wavelet packet decomposition, k is the subband index, and l is the time sampling point index. Let be the wavelet coefficient corresponding to the k-th sub-band of the j-th layer, and t be the time variable, which is the corresponding wavelet coefficient;

[0057] The second step is to construct the energy feature vector. ,in It is the sum of low-frequency energy. This is the sum of intermediate frequency energy. This represents the sum of high-frequency energy.

[0058] The third step is to use the feature ratio criterion for classification:

[0059]

[0060] in, It is the ratio of high-frequency energy to the sum of mid- and low-frequency energy;

[0061] The fourth step involves a built-in sliding window statistical mechanism that uses energy fluctuation variance as the basis for dynamic threshold adjustment. The formula is as follows:

[0062]

[0063] in, This represents the variance of energy fluctuations. The sum of energy in the i-th cycle. The mean of the energy sequence within the sliding window. This indicates the number of energy samples within the sliding window.

[0064] As a further technical solution of the present invention, the short-range control link of the communication module adopts a low-power wireless link to establish a point-to-point connection with the control terminal, and transmits instructions through command framing, CRC check and acknowledgment response mechanism;

[0065] The long-distance private network transmission link of the communication module is accessed through a private network tunnel. Waveform data and status information are packaged and transmitted in frames, supplemented by adaptive retransmission and encryption mechanisms. The generator polynomial of the CRC check algorithm is:

[0066]

[0067] The verification formula is:

[0068]

[0069] in, The data to be verified. To generate polynomials, (·) represents a bitwise reversal operation, and <<32 represents a left shift operation of 32 bits. The result is an XOR operation, and CRC32 is the final verification result.

[0070] As a further technical solution of the present invention, in the hybrid power supply system of the power module, the solar panel prioritizes power supply and charges the battery under sunlight conditions, the power take-off CT draws energy from the high-voltage conductor through a closed-loop power acquisition system, and the large-capacity battery serves as an energy buffer and backup power source; the power module has a built-in power management system that monitors the line load, battery state of charge, ambient light intensity, temperature, and power consumption of each module in real time, and switches the operating mode according to the following rules:

[0071] High-performance mode: When the battery state of charge meets the preset conditions, the line load meets the preset conditions, or when critical events are detected, the drone is installed while powered on, or emergency data acquisition is triggered, the peak power is output.

[0072] Charging mode: When the solar panel receives sufficient sunlight, the line load is low, and the battery's state of charge has not reached the preset value, the battery will be charged first. When the load increases, the mode will switch to high performance mode.

[0073] Low power mode: When the battery state of charge meets the preset conditions, the line load is within the preset range, or the ambient light meets the preset conditions, non-critical sensors and low-priority communication channels are turned off.

[0074] Sleep mode: When the battery state of charge does not meet the preset conditions, the line load is lower than the preset value, or the ambient light is low, most sensors and communication modules are turned off, and only the basic monitoring and wake-up mechanisms are retained.

[0075] As a further technical solution of the present invention, the GNSS receiver of the time synchronization module supports dual-mode time synchronization, and synchronizes the local crystal oscillator through an internal phase-locked loop. The closed-loop transfer function of the phase-locked loop is:

[0076]

[0077] in For phase detector gain, For voltage-controlled oscillator gain, For the gain of the proportional amplifier, , It is a time constant;

[0078] When satellite signals are unavailable, short-term autonomous operation is achieved through a time correction algorithm between temperature-compensated crystal oscillators and interconnect nodes. The correction formula is as follows:

[0079]

[0080]

[0081] in Let be the local time of node i. Let j be the local time of the adjacent node j. The time it takes for node i to receive a signal from node j. The time it takes for node j to receive the signal from node i. The time of node i after correction;

[0082] The time synchronization module has a built-in anomaly detection and drift compensation mechanism. When the local crystal oscillator deviation exceeds the threshold, it will trigger a correction or alarm.

[0083] Secondly, a method for installing distributed monitoring devices for transmission lines is provided, including the following steps:

[0084] S1: Preparation and docking: Using a mechanical guide structure for assisted guidance, the conical insert of the mounting machine is aligned with the conical groove on the device and embedded along the guide trajectory to achieve initial positioning. The device is then mounted on the mounting machine below the UAV. The electromagnetic drive rigid locking mechanism of the mounting machine is activated, energizing the first electromagnet of the mounting machine and the second electromagnet of the device. The two generate an attraction force to achieve initial locking. At the same time, the drive mechanism drives the locking pin to extend into the device, working together to lock the device and the mounting machine. At this time, the rectangular interface drive end of the servo motor on the mounting machine is precisely engaged with the rectangular end of the device's rotating shaft. The device switches to the preset mode, and all clamping components are in the open state.

[0085] S2: Flight patrol and positioning: The drone flies to the vicinity of the installation location of the target power line and adjusts its attitude so that the opening of the device is aligned with the conductor;

[0086] S3: Installation and Locking: The drone slowly moves forward to bring the power line into the opening of the device, and then hovers to stabilize;

[0087] S4: Triggering the installation process: Automatically triggered by remote control command or drone. The servo motor receives the command from the main control module and starts, driving the rotating shaft to rotate at a preset angle. The rotating shaft drives the coaxially fixed cam disk to rotate synchronously. The lower end of the clamping component is in the cam groove. Due to the movement of the cam table, the distance between its lower ends changes, thereby driving the clamping component to rotate around the limit axis. The clamping claw first swings along the cam groove trajectory towards the wire side until it is in contact with the wire surface and hugs it tightly, realizing the initial fixation of the device and the wire. Simultaneously, the first clamping claw closes, and the two parts of its internal power-taking CT are spliced ​​into a complete magnetic ring, which is in contact with the outer insulation layer of the wire to start inductive power taking. The second clamping claw closes synchronously, and the internal open-close current sensor is spliced ​​into a complete detection circuit, and the configured three-level compensation RC integrator enters the working state.

[0088] S5: Detection and Confirmation: The background system checks the device's battery level, signal strength, and signal acquisition function status, and sends a successful installation signal back to the drone;

[0089] S6: Separation and Activation: After receiving the success signal, the UAV releases the electromagnetic drive rigid locking mechanism of the installation mother machine, disconnects the power supply to the first and second electromagnets, and retracts the locking pin, so that the installation mother machine is separated from the device and removed.

[0090] S7: Maintenance and Replacement: When replacement is required, the drone carries the new device to the site, connects to the old device through the reverse process, and instructs the clamping assembly to open the old device and install the new one.

[0091] Compared with existing technologies, the advantages of this distributed monitoring device and method for power transmission lines that supports live installation by drones are:

[0092] The device is docked, locked, and separated from the UAV installation host via an interactive module, while the clamping mechanism drive module clamps, locks, and separates the device from the conductor. This allows the device to be installed and maintained on power transmission lines by the UAV while the line is energized, enabling operations to be carried out without power outages. Simultaneously, the main control module schedules the sensor module to collect line electrical signals and environmental signals. After preprocessing by the signal conditioning module, the data analysis module classifies the signals using wavelet packet energy decomposition and feature ratio criteria, thereby completing the monitoring of transmission line faults. This establishes a complete technical link from UAV live-line installation to fault identification, deeply integrating UAV live-line operation with transmission line fault monitoring, innovating the implementation path of transmission line fault monitoring, and providing technical support for efficient monitoring of transmission line faults.

[0093] With the help of the UAV interaction module and clamping mechanism drive module, and relying on the UAV's flexible operation capabilities, the device can be deployed and maintained while the transmission line is energized, which greatly improves the convenience of operation and maintenance and avoids power outages caused by power outages for maintenance. The sensor module's open-type current sensor and capacitive voltage sensor can accurately collect the line's electrical signals. The signal conditioning module processes the original signal through amplification, filtering, adaptive normalization, dynamic compensation, and wavelet packet feature enhancement. The data analysis module classifies the signal based on the energy feature vector and feature ratio criterion, which can accurately identify transmission line faults, realize timely fault monitoring and early warning, ensure the stable operation of the transmission line, and improve the intelligence level of transmission line fault monitoring.

[0094] The power module integrates a solar panel, a current collector (CT), and a high-capacity battery to form a hybrid power supply system. It can dynamically switch operating modes according to line load, sunlight, and other factors to ensure stable and reliable power supply to the device. The time synchronization module uses a GNSS receiver and a temperature-compensated crystal oscillator to construct a dual clock source, ensuring a unified time reference for fault monitoring and making fault monitoring data time-consistent. It has broad scenario adaptability and can be applied in various transmission line fault monitoring scenarios, promoting the practical application and large-scale development of transmission line fault monitoring technology. Attached Figure Description

[0095] Figure 1 This is a schematic diagram of the overall structure of the present invention;

[0096] Figure 2 This is a schematic diagram of the structure of the UAV interaction module and the clamping mechanism drive module of the present invention;

[0097] Figure 3 This is a cross-sectional view of the UAV interaction module and clamping mechanism drive module of the present invention;

[0098] Figure 4 for Figure 3 Enlarged view of the local structure of region A in the middle;

[0099] Figure 5 This is a schematic diagram of the first clamping gripper closing and the clamping claw opening of the present invention;

[0100] Figure 6 This is a flowchart illustrating the operation of the clamping mechanism drive module of the present invention.

[0101] Figure 7 This is a schematic diagram of the opening and closing current sensor structure of the present invention;

[0102] Figure 8 This is a diagram of the three-stage compensation RC integrator circuit of the present invention;

[0103] Figure 9 This is a flowchart of the signal conditioning process of the present invention;

[0104] Figure 10 This is a flowchart of the data analysis process of the present invention;

[0105] Figure 11 This is a schematic diagram of the method flow of the present invention;

[0106] In the diagram: 1. Main control module; 2. UAV interaction module; 21. Conical insert; 22. Conical groove; 23. First electromagnet; 24. Second electromagnet; 25. Drive mechanism; 26. Locking pin; 27. Mounting base; 3. Clamping mechanism drive module; 31. Servo motor; 32. Rotating shaft; 33. Cam plate; 331. Cam platform; 332. Cam groove; 34. Clamping assembly; 341. First clamping claw; 342. Second clamping claw; 343. Clamping claw; 35. Limiting shaft; 36. Power supply CT; 4. Sensing module; 5. Signal conditioning module; 6. Data analysis module; 7. Communication module; 8. Time synchronization module; 9. Power supply module; 41. Opening current sensor; 42. Capacitive voltage sensor; 43. Light intensity sensor; 91. Solar panel; 92. High-capacity battery; 93. Power management system. Detailed Implementation

[0107] 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.

[0108] Please see the appendix Figure 1 - Appendix Figure 10The present invention provides an embodiment 1: a distributed monitoring device for power transmission lines that supports live installation by drones, comprising a main control module 1, a drone interaction module 2, a clamping mechanism drive module 3, a sensing module 4, a signal conditioning module 5, a data analysis module 6, a communication module 7, a time synchronization module 8, and a power supply module 9; the main control module 1 establishes real-time communication connections with the other modules through an internal high-speed bus, uniformly schedules the work of each module, and is specifically responsible for receiving status feedback and data information from each module, sending control commands to each module, coordinating the timing of each module, and ensuring the orderly realization of the overall function of the device;

[0109] The UAV interaction module 2 is used to realize the docking, locking, and separation of the device and the UAV mounting host. The UAV interaction module 2 integrates a mechanical guiding structure and an electromagnetic drive rigid locking mechanism. The mechanical guiding structure includes a conical insert 21 set on the mounting host and a corresponding conical groove 22 set on the device. The electromagnetic drive rigid locking mechanism includes a first electromagnet 23 set on the mounting host and a corresponding second electromagnet 24 set on the device. The mounting host is also equipped with a drive mechanism 25, which drives a locking pin 26. The locking pin 26 extends into the device through an opening on the device. Both the drive mechanism 25 and the locking pin 26 are mounted on a mounting base 27, which is connected to the mounting host. The clamping mechanism drive module 3 is used to realize the clamping docking, locking, and separation of the device and the wire during disassembly. The clamping mechanism drive module 3 includes a servo motor 31, a rotating shaft 32, several cam disks 33, and a clamping assembly 3. 4; One end of the rotating shaft 32 is rotatably connected to the device housing, and the other end passes through the device housing and is driven by the servo motor 31; Several cam disks 33 are axially fixedly connected to the rotating shaft 32. The cam disk 33 includes a cam platform 331 set in the center and a cam groove 332 formed by the cam platform 331 and the side wall of the cam disk 33. The trajectory directions of the cam platform 331 and the cam groove 332 are consistent; A limit shaft 35 is also fixedly connected to the device housing. The clamping assembly 34 includes a first clamping claw 341, a second clamping claw 342 and a clamping claw 343, all rotatably connected to the limit shaft 35, and their lower ends are all slidably connected in the cam groove 332; A power-taking CT 36 is set inside the first clamping claw 341, and an openable current sensor 41 is set inside the second clamping claw 342; The end of the rotating shaft 32 near the servo motor 31 is rectangular, and the shape of the drive connection end of the servo motor 31 is adapted to the rectangle. The servo motor 31 is mounted on the mounting machine.

[0110] Sensing module 4 includes an openable current sensor 41 with a compensation coil, a capacitive voltage sensor 42, and a light intensity sensor 43. The openable current sensor 41 is equipped with a three-stage compensated RC integrator. The compensation coil, through a matching design of turns density, cross-sectional area, and included angle, compensates for measurement errors caused by the mechanical structure. The three-stage compensated RC integrator achieves accurate integration processing of wideband signals. The capacitive voltage sensor 42 uses a small capacitor to isolate and scale down high-voltage signals, and a high-input-impedance buffer circuit at the front end prevents signal attenuation. The light intensity sensor 43 is used to monitor ambient light intensity, assisting in the analysis and judgment of fault scenarios. In the openable current sensor 41 of sensing module 4, the compensation coil is located at the end of the main coil, satisfying the following compensation relationship:

[0111]

[0112] in, To compensate for the included angle of the coil, The included angle of the Rogowski coil. , These represent the turns density of the compensation coil and the turns density of the missing portion of the gap at the end of the Rogowski coil, respectively. To compensate for the cross-sectional area of ​​the coil, This represents the cross-sectional area of ​​the missing portion at the end of the Rogowski coil.

[0113] The transfer function of the three-stage compensated RC integrator is:

[0114]

[0115] in:

[0116]

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123] in, This is the input voltage signal for a three-stage compensated RC integrator. The output voltage signal of the three-stage compensated RC integrator. For complex frequency variables, These are the capacitor parameters of the three-stage compensated RC integrator, and G1, G2, G3, G4, and G5 are the conductances of the corresponding resistors of the three-stage compensated RC integrator.

[0124] The capacitive voltage sensor 42 achieves high voltage signal isolation and scaling through a small capacitor, and is equipped with a high input impedance buffer circuit and an anti-interference filter unit at the front end.

[0125] The light intensity sensor 43 converts ambient light intensity into an electrical signal through a photodiode array, and outputs standardized data after being corrected by a temperature compensation and nonlinear correction circuit.

[0126] Signal conditioning module 5 performs amplification, filtering, adaptive normalization, dynamic compensation, and wavelet packet feature enhancement on the original signal. The preamplifier boosts the amplitude of weak signals, the bandpass filter extracts signals from fault characteristic frequency bands, adaptive normalization makes signals of different amplitudes comparable, dynamic compensation corrects distortion during signal transmission, and wavelet packet decomposition enhances the characteristics of high-frequency transient signals, providing high-quality input for subsequent data analysis. The processing flow of signal conditioning module 5 includes:

[0127] The first step is to amplify the input signal using a preamplifier;

[0128] The second step is to extract the target frequency band using a bandpass filter. The frequency response function of the filter is:

[0129]

[0130] in, For frequency, For the center frequency, For bandpass filters at frequency Frequency response at that location;

[0131] The third step is to perform fast adaptive normalization in the digital domain, using the following formula:

[0132]

[0133] in, It is a discrete signal sequence obtained by sampling. It is a normalized discrete signal. and These represent the mean and standard deviation within the sliding window, respectively. To prevent small constants with zero denominators;

[0134] The fourth step is to perform dynamic compensation based on the least mean square adaptive algorithm, with the following formula:

[0135]

[0136]

[0137]

[0138] in, This represents the output signal after compensation. This represents the normalized input signal sequence. This indicates the order of the adaptive filter. This represents the weighting coefficients of the k-th order filter at time n; Let be the error signal at time n. Let n be the desired signal at time n. Let μ be the weight vector at time n, and μ be the convergence factor.

[0139] The fifth step is to enhance the features of the high-frequency abrupt change components through wavelet packet decomposition and output the processed signal to the main control module 1.

[0140] Data analysis module 6 classifies signals through wavelet packet energy decomposition, feature vector construction, and feature ratio criterion. It obtains the energy distribution of each sub-band through wavelet packet energy decomposition, constructs feature vectors containing low-frequency, mid-frequency, and high-frequency energy, and uses the feature ratio criterion to distinguish different signal types such as intrusive waveforms, power outage waveforms, and fault waveforms. The built-in sliding window statistical mechanism allows the classification threshold to be dynamically adjusted according to operating conditions, ensuring classification accuracy. The signal classification process of data analysis module 6 includes:

[0141] The first step is to normalize the input signal sequence. Perform wavelet packet energy decomposition and calculate the energy components of each subband:

[0142]

[0143] in, Let l represent the energy component of the k-th subband at the j-th level, where j is the level of wavelet packet decomposition, k is the subband index, and l is the time sampling point index. Let be the wavelet coefficient corresponding to the k-th sub-band of the j-th layer, and t be the time variable, which is the corresponding wavelet coefficient;

[0144] The second step is to construct the energy feature vector. ,in It is the sum of low-frequency energy. This is the sum of intermediate frequency energy. This represents the sum of high-frequency energy.

[0145] The third step is to use the feature ratio criterion for classification:

[0146]

[0147] in, It is the ratio of high-frequency energy to the sum of mid- and low-frequency energy;

[0148] The fourth step involves a built-in sliding window statistical mechanism that uses energy fluctuation variance as the basis for dynamic threshold adjustment. The formula is as follows:

[0149]

[0150] in, This represents the variance of energy fluctuations. The sum of energy in the i-th cycle. The mean of the energy sequence within the sliding window. This indicates the number of energy samples within the sliding window;

[0151] Communication module 7 includes a short-range control link and a long-range private network transmission link for command interaction and data upload. The short-range control link enables command interaction with the UAV during the device installation phase, controlling each step of the installation process. The long-range private network transmission link uploads fault monitoring data to the operation and maintenance center, and CRC check and adaptive retransmission mechanism ensure the integrity and reliability of data transmission. The short-range control link of communication module 7 uses a low-power wireless link to establish a point-to-point connection with the control terminal, and transmits commands through command framing, CRC check and acknowledgment mechanism.

[0152] The long-distance private network transmission link of communication module 7 uses a private network access tunnel to package waveform data and status information into frames for transmission, supplemented by adaptive retransmission and encryption mechanisms; the generator polynomial of the CRC check algorithm is:

[0153]

[0154] The verification formula is:

[0155]

[0156] in, The data to be verified. To generate polynomials, (·) represents a bitwise reversal operation, and <<32 represents a left shift operation of 32 bits. The result is an XOR operation, and the CRC32 result is the final verification result.

[0157] The time synchronization module 8 employs a GNSS receiver and a temperature-compensated crystal oscillator to construct a dual clock source, providing a unified time reference. When the satellite signal is normal, the local crystal oscillator is synchronized with the satellite time synchronization through an internal phase-locked loop, ensuring high-precision time synchronization. When the satellite signal is unavailable, it switches to the temperature-compensated crystal oscillator and achieves short-term autonomous operation through an inter-node time correction algorithm, ensuring the consistency of the time reference among multiple devices and providing an accurate time reference for fault location. The GNSS receiver of the time synchronization module 8 supports dual-mode time synchronization, synchronizing the local crystal oscillator through an internal phase-locked loop. The closed-loop transfer function of the phase-locked loop is:

[0158]

[0159] in For phase detector gain, For voltage-controlled oscillator gain, For the gain of the proportional amplifier, , It is a time constant;

[0160] When satellite signals are unavailable, short-term autonomous operation is achieved through a time correction algorithm between temperature-compensated crystal oscillators and interconnect nodes. The correction formula is as follows:

[0161]

[0162]

[0163] in Let be the local time of node i. Let j be the local time of the adjacent node j. The time it takes for node i to receive a signal from node j. The time it takes for node j to receive the signal from node i. The time of node i after correction;

[0164] The timing module 8 has a built-in anomaly detection and drift compensation mechanism. When the local crystal oscillator deviation exceeds the threshold, it will trigger a correction or alarm.

[0165] Power module 9 integrates solar panel 91, power CT36, and large-capacity battery 92 to form a hybrid power supply system that supports dynamic switching between multiple modes. Solar panel 91 prioritizes power supply and battery charging under sunlight conditions. Power CT36 draws energy from the high-voltage conductor when the line load meets requirements. The large-capacity battery 92 serves as an energy buffer and backup power source. In the hybrid power supply system of power module 9, solar panel 91 prioritizes power supply and battery charging under sunlight conditions. Power CT36 draws energy from the high-voltage conductor through a closed-loop power acquisition system. The large-capacity battery 92 serves as an energy buffer and backup power source. Power module 9 has a built-in power management system 93 that monitors line load, battery state of charge, ambient light intensity, temperature, and power consumption of each module in real time, switching operating modes according to the following rules:

[0166] High-performance mode: When the battery state of charge meets the preset conditions, the line load meets the preset conditions, or when critical events are detected, the drone is installed while powered on, or emergency data acquisition is triggered, the peak power is output.

[0167] Charging mode: When the solar panel receives sufficient sunlight, the line load is low, and the battery charge status has not reached the preset value, the battery will be charged first. When the load increases, the mode will switch to high performance mode.

[0168] Low power mode: When the battery state of charge meets the preset conditions, the line load is within the preset range, or the ambient light meets the preset conditions, non-critical sensors and low-priority communication channels are turned off.

[0169] Sleep mode: When the battery state of charge does not meet the preset conditions, the line load is lower than the preset value, or the ambient light is low, most sensors and communication modules 7 are turned off, and only the basic monitoring and wake-up mechanism is retained.

[0170] Please see the appendix Figure 11 The present invention provides an embodiment 2: a method for installing a distributed monitoring device for power transmission lines, comprising the following steps:

[0171] S1: Preparation and docking: Using the mechanical guide structure for auxiliary guidance, the conical insert 21 of the mounting machine is aligned with the conical groove 22 on the device and embedded along the guide trajectory to achieve initial positioning. The device is then mounted on the mounting machine below the UAV. The electromagnetic drive rigid locking mechanism of the mounting machine is activated, energizing the first electromagnet 23 of the mounting machine and the second electromagnet 24 of the device. The two generate an attraction force to achieve initial locking. At the same time, the locking pin 26 is driven into the device through the drive mechanism 25 to work together to lock the device and the mounting machine. At this time, the rectangular interface drive end of the servo motor 31 on the mounting machine is precisely engaged with the rectangular end of the rotating shaft 32 of the device. The device switches to the preset mode, and all clamping components 34 are in the open state.

[0172] S2: Flight patrol and positioning: The drone flies to the vicinity of the installation location of the target power line and adjusts its attitude so that the opening of the device is aligned with the conductor;

[0173] S3: Installation and Locking: The drone slowly moves forward to bring the power line into the opening of the device, and then hovers to stabilize;

[0174] S4: Triggering the installation process: The installation process is triggered automatically by remote control command or drone. Servo motor 31 receives the command from main control module 1 and starts to drive rotating shaft 32 to rotate at a preset angle. The rotating shaft drives the coaxial fixed cam disk 33 to rotate synchronously. The lower end of clamping component 34 is in cam groove 332. Due to the movement of cam table 331, the distance between its lower ends changes, thereby driving clamping component 34 to rotate around limit shaft 35. Clamping claw 343 first swings along the cam groove trajectory towards the wire side until it is attached to the wire surface and hugs it tightly, realizing the initial fixation of the device and the wire. Simultaneously, the first clamping claw 341 closes, and the two parts of the power CT36 inside it are spliced ​​into a complete magnetic ring, which is attached to the outer insulation layer of the wire to start induction power collection. The second clamping claw 342 closes synchronously, and the open and close current sensor 41 inside it is spliced ​​into a complete detection circuit. The configured three-level compensation RC integrator enters the working state.

[0175] S5: Detection and Confirmation: The background system checks the device's battery level, signal strength, and signal acquisition function status, and sends a successful installation signal back to the drone;

[0176] S6: Separation and Activation: After the UAV receives the success signal, it releases the electromagnetic drive rigid locking mechanism of the installation mother machine, disconnects the power supply to the first electromagnet 23 and the second electromagnet 24, and retracts the locking pin 26, so that the installation mother machine is separated from the device and removed.

[0177] S7: Maintenance and Replacement: When replacement is required, the drone carries the new device to the site, connects to the old device through the reverse process, and instructs to open the clamping assembly 34 to remove the old device and install the new one.

[0178] In summary, this invention enables the device to dock and lock with the UAV installation host through the UAV interaction module 2, and to clamp and lock with the conductor through the clamping mechanism drive module 3. This allows the device to be installed and maintained on the power transmission line by the UAV while it is powered on, without the need for power outages. Simultaneously, the main control module 1 schedules the sensing module 4 to collect line electrical signals and environmental signals. After preprocessing by the signal conditioning module 5, the data analysis module 6 performs signal classification through wavelet packet energy decomposition and feature ratio criteria, thereby completing the monitoring of power transmission line faults. This invention constructs a complete technical link from UAV live-line installation to fault identification, deeply integrating UAV live-line operation with power transmission line fault monitoring, innovating the implementation path of power transmission line fault monitoring, and providing technical support for efficient monitoring of power transmission line faults.

[0179] With the help of the UAV interaction module 2 and the clamping mechanism drive module 3, and relying on the UAV's flexible operation capabilities, the deployment and maintenance of the device can be completed while the transmission line is energized, which greatly improves the convenience of operation and maintenance and avoids power outages caused by power outages for maintenance. The opening and closing current sensor 41 and the capacitive voltage sensor 42 of the sensing module 4 can accurately collect the line electrical signals. The signal conditioning module 5 processes the original signal through amplification, filtering, adaptive normalization, dynamic compensation and wavelet packet feature enhancement. The data analysis module 6 classifies the signal based on the energy feature vector and feature ratio criterion, which can accurately identify transmission line faults, realize timely monitoring and early warning of faults, ensure the stable operation of the transmission line, and improve the intelligent level of transmission line fault monitoring.

[0180] The power module 9 integrates a solar panel 91, a power CT36, and a high-capacity battery 92 to form a hybrid power supply system. It can dynamically switch working modes according to line load, sunlight, etc., to ensure stable and reliable power supply to the device. The time synchronization module 8 uses a GNSS receiver and a temperature-compensated crystal oscillator to construct a dual clock source to ensure a unified time reference for fault monitoring and make fault monitoring data time consistent. It has a wide range of scene adaptability and can be applied in various transmission line fault monitoring scenarios, promoting the practical application and large-scale development of transmission line fault monitoring technology.

[0181] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A distributed monitoring device for power transmission lines that supports live installation by unmanned aerial vehicles (UAVs), characterized in that: It includes a main control module (1), a drone interaction module (2), a clamping mechanism drive module (3), a sensing module (4), a signal conditioning module (5), a data analysis module (6), a communication module (7), a time synchronization module (8), and a power supply module (9); the main control module (1) establishes a real-time communication connection with the other modules through an internal high-speed bus to uniformly schedule the work of each module; The UAV interaction module (2) is used to realize the docking, locking and separation of the device and the UAV mounting machine; the clamping mechanism drive module (3) is used to realize the clamping docking, clamping and locking of the device and the wire and the separation during disassembly. The sensing module (4) includes an open-close current sensor (41) with a compensation coil, a capacitive voltage sensor (42) and a light intensity sensor (43). The open-close current sensor (41) is equipped with a three-level compensation RC integrator. The signal conditioning module (5) performs amplification, filtering, adaptive normalization, dynamic compensation and wavelet packet feature enhancement processing on the original signal; The data analysis module (6) classifies signals through wavelet packet energy decomposition, feature vector construction, and feature ratio criterion. The communication module (7) includes a short-distance control link and a long-distance private network transmission link, used for command interaction and data upload; The time synchronization module (8) uses a GNSS receiver and a temperature-compensated crystal oscillator to construct a dual clock source, providing a unified time reference; The power module (9) integrates a solar panel (91), a power CT (36), and a large-capacity battery (92) to form a hybrid power supply system that supports dynamic switching of multiple modes.

2. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: The UAV interaction module (2) integrates a mechanical guidance structure and an electromagnetic drive rigid locking mechanism; The mechanical guide structure includes a tapered insert (21) disposed on the mounting machine and a corresponding tapered groove (22) disposed on the device; The electromagnetic drive rigid locking mechanism includes a first electromagnet (23) mounted on the mounting machine and a second electromagnet (24) mounted on the device. The mounting machine is also provided with a drive mechanism (25), which drives a connecting locking pin (26). The locking pin (26) extends into the device through an opening on the device. Both the drive mechanism (25) and the locking pin (26) are mounted on a mounting base (27), which is connected to the mounting machine.

3. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: The clamping mechanism drive module (3) includes a servo motor (31), a rotating shaft (32), several cam disks (33), and a clamping assembly (34); one end of the rotating shaft (32) is rotatably connected to the outer shell of the device, and the other end passes through the outer shell of the device and is driven by the servo motor (31); several cam disks (33) are axially fixedly connected to the rotating shaft (32), and the cam disk (33) includes a cam platform (331) set in the center, and a cam groove (332) formed by the cam platform (331) and the side wall of the cam disk (33), and the trajectory direction of the cam platform (331) and the cam groove (332) is consistent; A limiting shaft (35) is also fixedly connected to the outer casing of the device. The clamping assembly (34) includes a first clamping claw (341), a second clamping claw (342), and a clamping claw (343), all of which are rotatably connected to the limiting shaft (35), and their lower ends are all slidably connected in the cam groove (332). The power CT (36) is disposed inside the first clamping claw (341), and the opening and closing current sensor (41) is disposed inside the second clamping claw (342). The end of the rotating shaft (32) near the servo motor (31) is rectangular, and the shape of the drive connection end of the servo motor (31) is adapted to the rectangle. The servo motor (31) is mounted on the mounting machine.

4. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: In the opening and closing current sensor (41) of the sensing module (4), the compensation coil is located at the end of the main coil to satisfy the compensation relationship: in, To compensate for the included angle of the coil, The included angle of the Rogowski coil. , These represent the turns density of the compensation coil and the turns density of the missing portion of the gap at the end of the Rogowski coil, respectively. To compensate for the cross-sectional area of ​​the coil, This represents the cross-sectional area of ​​the missing portion at the end of the Rogowski coil. The transfer function of the three-stage compensated RC integrator is: in: in, This is the input voltage signal for a three-stage compensated RC integrator. The output voltage signal of the three-stage compensated RC integrator. For complex frequency variables, These are the capacitor parameters of the three-stage compensated RC integrator, and G1, G2, G3, G4, and G5 are the conductances of the corresponding resistors of the three-stage compensated RC integrator. The capacitive voltage sensor (42) achieves high voltage signal isolation and scaling through a small capacitor, and is equipped with a high input impedance buffer circuit and an anti-interference filter unit at the front end. The light intensity sensor (43) converts ambient light intensity into an electrical signal through a photodiode array, and outputs standardized data after being corrected by a temperature compensation and nonlinear correction circuit.

5. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: The processing flow of the signal conditioning module (5) includes: The first step is to amplify the input signal using a preamplifier; The second step is to extract the target frequency band using a bandpass filter. The frequency response function of the filter is: in, For frequency, For the center frequency, For bandpass filters at frequency Frequency response at that location; The third step is to perform fast adaptive normalization in the digital domain, using the following formula: in, It is a discrete signal sequence obtained by sampling. It is a normalized discrete signal. and These represent the mean and standard deviation within the sliding window, respectively. To prevent small constants with zero denominators; The fourth step is to perform dynamic compensation based on the least mean square adaptive algorithm, with the following formula: in, This represents the output signal after compensation. This represents the normalized input signal sequence. This indicates the order of the adaptive filter. This represents the weighting coefficients of the k-th order filter at time n; Let be the error signal at time n. Let n be the desired signal at time n. Let μ be the weight vector at time n, and μ be the convergence factor. The fifth step is to enhance the features of the high-frequency abrupt change components through wavelet packet decomposition and output the processed signal to the main control module (1).

6. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: The signal classification process of the data analysis module (6) includes: The first step is to normalize the input signal sequence. Perform wavelet packet energy decomposition and calculate the energy components of each subband: in, Let l represent the energy component of the k-th subband at the j-th level, where j is the level of wavelet packet decomposition, k is the subband index, and l is the time sampling point index. Let be the wavelet coefficient corresponding to the k-th sub-band of the j-th layer, and t be the time variable, which is the corresponding wavelet coefficient; The second step is to construct the energy feature vector. ,in It is the sum of low-frequency energy. This is the sum of intermediate frequency energy. This represents the sum of high-frequency energy. The third step is to use the feature ratio criterion for classification: in, It is the ratio of high-frequency energy to the sum of mid- and low-frequency energy; The fourth step involves a built-in sliding window statistical mechanism that uses energy fluctuation variance as the basis for dynamic threshold adjustment. The formula is as follows: in, This represents the variance of energy fluctuations. The sum of energy in the i-th cycle. The mean of the energy sequence within the sliding window. This indicates the number of energy samples within the sliding window.

7. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: The short-range control link of the communication module (7) establishes a point-to-point connection with the control terminal using a low-power wireless link, and transmits instructions through command framing, CRC check and acknowledgment mechanism; The long-distance private network transmission link of the communication module (7) is accessed through a private network tunnel, and the waveform data and status information are packaged and transmitted in frames, supplemented by adaptive retransmission and encryption mechanisms; the generator polynomial of the CRC check algorithm is: The verification formula is: in, The data to be verified. To generate polynomials, (·) represents a bitwise reversal operation, and <<32 represents a left shift operation of 32 bits. The result is an XOR operation, and CRC32 is the final verification result.

8. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: In the hybrid power supply system of the power module (9), the solar panel (91) prioritizes power supply and charges the battery under sunlight conditions, the power CT (36) draws energy from the high-voltage conductor through a closed-loop power acquisition system, and the large-capacity battery (92) serves as an energy buffer and backup power source; the power module (9) has a built-in power management system (93) that monitors the line load, battery state of charge, ambient light intensity, temperature, and power consumption of each module in real time, and switches the working mode according to the following rules: High-performance mode: When the battery state of charge meets the preset conditions, the line load meets the preset conditions, or when critical events are detected, the drone is installed while powered on, or emergency data acquisition is triggered, the peak power is output. Charging mode: When the solar panel (91) receives sufficient sunlight, the line load is low, and the battery charge status has not reached the preset value, the battery is charged first. When the load increases, the mode is switched to high performance mode. Low power mode: When the battery state of charge meets the preset conditions, the line load is within the preset range, or the ambient light meets the preset conditions, non-critical sensors and low-priority communication channels are turned off. Sleep mode: When the battery charge state does not meet the preset conditions, the line load is lower than the preset value, or the ambient light is low, most sensors and communication modules are turned off (7), and only the basic monitoring and wake-up mechanism is retained.

9. The distributed monitoring device for power transmission lines supporting live installation by unmanned aerial vehicles (UAVs) according to claim 1, characterized in that: The GNSS receiver of the time synchronization module (8) supports dual-mode time synchronization and synchronizes with the local crystal oscillator through an internal phase-locked loop. The closed-loop transfer function of the phase-locked loop is: in For phase detector gain, For voltage-controlled oscillator gain, For the gain of the proportional amplifier, , It is a time constant; When satellite signals are unavailable, short-term autonomous operation is achieved through a time correction algorithm between temperature-compensated crystal oscillators and interconnect nodes. The correction formula is as follows: in Let be the local time of node i. Let j be the local time of the adjacent node j. The time it takes for node i to receive a signal from node j. The time it takes for node j to receive the signal from node i. The time of node i after correction.

10. A method for installing a distributed monitoring device for transmission lines, characterized in that: Includes the following steps: S1: Preparation and docking: Using the mechanical guide structure for auxiliary guidance, the conical insert (21) of the mounting machine is aligned with the conical groove (22) on the device and embedded along the guide trajectory to achieve initial positioning. The device is mounted on the mounting machine under the UAV. The electromagnetic drive rigid locking mechanism of the mounting machine is activated, and the first electromagnet (23) of the mounting machine and the second electromagnet (24) of the device are energized. The two generate an attraction force to achieve initial locking. At the same time, the locking pin (26) is driven by the drive mechanism (25) to extend into the device and work together to lock the device and the mounting machine. At this time, the rectangular interface drive end of the servo motor (31) on the mounting machine is precisely engaged with the rectangular end of the rotating shaft (32) of the device. The device is switched to the preset mode and the clamping components (34) are all in the open state. S2: Flight patrol and positioning: The drone flies to the vicinity of the installation location of the target power line and adjusts its attitude so that the opening of the device is aligned with the conductor; S3: Installation and Locking: The drone slowly moves forward to bring the power line into the opening of the device, and then hovers to stabilize; S4: Triggering the installation process: The servo motor (31) receives the command from the main control module (1) and starts to drive the rotating shaft (32) to rotate at a preset angle. The rotating shaft drives the coaxial fixed cam disk (33) to rotate synchronously. The lower end of the clamping assembly (34) is in the cam groove (332). Due to the movement of the cam table (331), the distance between its lower ends changes, thereby driving the clamping assembly (34) to rotate around the limit shaft (35). The clamping claw (343) first swings along the cam groove trajectory towards the wire side until it is attached to the wire surface and hugs it tightly, realizing the initial fixation of the device and the wire. Simultaneously, the first clamping claw (341) closes, and the two parts of the power CT (36) inside it are spliced ​​into a complete magnetic ring, which is attached to the outer insulation layer of the wire to start induction power. The second clamping claw (342) closes synchronously, and the open and close current sensor (41) inside it is spliced ​​into a complete detection circuit. The configured three-level compensation RC integrator enters the working state. S5: Detection and Confirmation: The background system checks the device's battery level, signal strength, and signal acquisition function status, and sends a successful installation signal back to the drone; S6: Separation and Activation: After the UAV receives the success signal, it releases the electromagnetic drive rigid locking mechanism of the installation mother machine, disconnects the power supply to the first electromagnet (23) and the second electromagnet (24), and retracts the locking pin (26) to separate the installation mother machine from the device and remove it. S7: Maintenance and Replacement: When replacement is required, the drone carries the new device to the site, connects to the old device through the reverse process, and instructs to open the clamping assembly (34) to remove the old device and install the new one.

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