Distributed precise positioning online monitoring device for hidden dangers in high-voltage lines

Abstract

The present application relates to the technical field of power monitoring, and discloses a distributed precise positioning online monitoring device for hidden dangers of high-voltage lines, comprising a lower shell, an upper shell being installed on the top of the lower shell, magnetic buckles being provided inside the lower shell and the upper shell, and chucks being rotated inside the lower shell and the upper shell; inner rings being provided inside the lower shell and the upper shell, support blocks being fixed on both sides of the lower shell and the upper shell, a PLC module being provided between the inner ring and the support block, a slide groove being provided inside the chuck, clamping blocks distributed in a ring array being provided inside the chuck, the clamping blocks all sliding inside the slide groove, and a limit plate being fixed at one end of the clamping block. Through the coordination between the clamping blocks, the clamping disc and the limit plate, the device can be adapted to cables of different thicknesses for installation, and the device can also be quickly installed by drone, without the need for manual high-altitude operations, thereby increasing the scope of application of the device and reducing the operating risk of the device.

Description

Technical Field

[0001] The present invention relates to the technical field of power monitoring, and in particular to a distributed precise positioning online monitoring device for hidden dangers in high-voltage lines. Background Art

[0002] As power systems expand and high-voltage lines cover more areas, existing high-voltage line monitoring technology primarily relies on traditional sensor equipment and manual inspections for fault detection and location. Existing monitoring equipment often uses a single sensor, such as a traveling wave current sensor, temperature sensor, or vibration sensor, to acquire fault signals and transmit them to a monitoring platform for analysis. While this technology can monitor the status of high-voltage lines to a certain extent, its dependence on environmental conditions makes it difficult to provide high-precision positioning results in complex and changing environments.

[0003] It can be seen that the existing technology has certain limitations in some aspects, especially in terms of equipment adaptability, safety and efficiency. Most of the existing equipment is unable to adapt to cables of different thicknesses, which leads to certain difficulties and limitations during installation and inability to achieve unified adaptation. In addition, the installation and maintenance of the equipment mostly rely on manual labor, especially when high-altitude operations are required, there are high operational risks. In harsh climatic conditions, such as heavy snow, freezing and other conditions, the equipment is easily affected by external weather factors, and the outer casing is prone to water accumulation or ice, thereby affecting the normal operation of the equipment. Furthermore, the sensors and monitoring equipment in the existing technology are often difficult to effectively deal with interference and signal attenuation in complex environments, resulting in low fault location accuracy and an inability to meet the changing needs of power line environments. Therefore, how to improve the scope of application of the equipment, reduce the risks of high-altitude operations, and improve the operating capabilities of the equipment in extreme environments have become problems that need to be urgently solved in current technology. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a distributed and precise online monitoring device for hidden dangers in high-voltage lines, which solves the problems of insufficient adaptability, poor operational safety and low fault location accuracy of existing high-voltage line monitoring equipment in complex environments.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a distributed precise positioning online monitoring device for hidden dangers in high-voltage lines, comprising a lower shell, an upper shell is installed on the top of the lower shell, magnetic buckles are provided inside the lower shell and the upper shell, and chucks are rotated inside the lower shell and the upper shell; inner rings are installed inside the lower shell and the upper shell, support blocks are fixed on both sides of the lower shell and the upper shell, a PLC module is provided between the inner ring and the support block, a slide groove is provided inside the chuck, and clamping blocks distributed in a ring array are provided inside the chuck, the clamping blocks all slide inside the slide groove, and a limiting plate is fixed at one end of the clamping block. The limiting plate is fixed with a fixing plate 1 on the side away from the clamping block, and a telescopic rod is installed on one side of the fixing plate 1, a support block is installed inside the chuck, and a double-headed motor is provided on the top of the support block, and a rotating column is rotated inside the support block, and the output end of the double-headed motor is fixed to one side of the rotating column, and a connecting rod 1 slides inside the other side of the rotating column, and a threaded column is fixed on one end of the connecting rod 1 away from the rotating column, and a connecting rod 2 is fixed on one end of the threaded column away from the connecting rod 1, and a gear slides on the outer wall of the connecting rod 2, and a gear ring is installed on the side of the chuck away from the clamping block, and the gear ring is meshed with the gear, and a connecting component is provided on one side of the gear.

[0006] Preferably, the connecting assembly includes a connecting rod three, the connecting rod three rotates on the side of the gear away from the connecting rod two, and a protruding cylindrical rotation at one end of the connecting rod three has a fixed plate two, and the fixed plate two is fixed inside the inner ring.

[0007] Preferably, a cam is fixed to the outer wall of the rotating column.

[0008] Preferably, pull plates are fixed to the outer walls of the lower shell and the upper shell.

[0009] Preferably, the threaded column is threaded inside the chuck.

[0010] Preferably, the PLC module includes:

[0011] Multiple sensor units, each used to collect environmental data and line status data at different locations on the high-voltage line; a data processing unit connected to the multiple sensor units, used to receive data sent by the multiple sensor units, perform data processing, and accurately locate the fault location based on the time difference inversion method, fractal correction factor and multi-scale wave equation; a communication module connected to the data processing unit, used to send the fault location results, fault type and other related data processed by the data processing unit to the background monitoring platform via wireless communication;

[0012] The background monitoring platform is connected to the communication module and receives data from the communication module through wireless communication. It is used to diagnose and analyze faults, generate fault handling instructions, and notify relevant personnel to perform maintenance.

[0013] Preferably, the plurality of sensor units include:

[0014] Traveling wave current sensor, which is used to collect traveling wave current signals in high-voltage lines;

[0015] Vibration sensor, which is used to collect mechanical vibration signals near the high-voltage line;

[0016] A temperature sensor is used to collect temperature change data on the circuit surface;

[0017] The multiple sensor units process the collected signals through a data fusion algorithm and output comprehensive fault information for further analysis and processing by the data processing unit.

[0018] Preferably, the data processing unit uses a time difference inversion method, a fractal correction factor, a multi-scale wave equation and an adaptive optimization algorithm to perform fault location;

[0019] In the data processing unit, the time difference inversion method includes the arrival time difference of the fault signal measured by multiple sensors, the signal propagation path is determined by the time difference inversion method, and the fault point location is calculated based on the time difference information;

[0020] The fractal correction factor is used to dynamically correct the propagation speed. The correction factor is adjusted according to the influence of terrain and climate environmental factors to ensure accurate positioning. The calculation formula of the time difference inversion method is:

[0021]

[0022] Where Δt i,j is the time difference between sensors i and j, indicating the signal propagation time difference from the fault point to sensors i and j; d i,j is the spatial distance between sensors i and j, indicating the physical distance between the fault point and the two sensors; v is the signal propagation speed, usually the propagation speed of electromagnetic waves in the medium; ∈(x) is the fractal correction factor, indicating the influence of terrain, climate or other environmental factors on signal propagation, which varies according to the location (x).

[0023] Preferably, the multi-scale wave equation in the data processing unit is used to describe the signal propagation process. The wave equation takes into account the changes in the signal propagation path in the power line due to terrain and climate change. The modified form of the wave equation is:

[0024]

[0025] in, is the Laplace operator, which represents the second-order derivative in space and is used to describe the expansion and change of the signal in space; u(x,t) is the displacement of the signal, usually referring to the signal strength or current value at position x; v is the propagation speed of the signal, usually referring to the propagation speed of electromagnetic waves or other fluctuations; S(t) is the time scale factor, which represents the time scale change during the signal propagation process and is used to adjust the propagation speed to take into account the influence of environmental factors; The second-order time derivative of the signal u represents the acceleration or rate of change of the signal over time; For time t 2 The second-order partial derivative is usually used to describe the rate of change of a signal or physical quantity over time; f(x, t) is an external disturbance source, which represents the external force or excitation source that affects the propagation of the signal.

[0026] Preferably, the background monitoring platform performs fault type analysis based on the received real-time data, generates processing instructions, and sends the fault processing instructions to relevant personnel via SMS, email, or application notification to perform fault repair and emergency response.

[0027] The present invention provides a distributed, precise positioning and online monitoring device for high-voltage line hidden dangers. It has the following beneficial effects:

[0028] 1. The present invention enables the equipment to adapt to cables of different thicknesses for installation through the coordination between components such as the clamping block, the clamping disc and the limit plate. At the same time, the equipment can also be quickly installed by drone, without the need for manual high-altitude operations. This solves the problems that the equipment cannot adapt to cables of different thicknesses for uniform use and that the operations of high-altitude workers are too dangerous, thereby increasing the scope of application of the equipment and reducing the operating risks of the equipment.

[0029] 2. The present invention cooperates with components such as a rotating column, a cam and a telescopic rod, so that when the equipment encounters extreme snowy weather, the corresponding equipment can knock on the casing through the repeatedly rotating cam and repeatedly extending the telescopic rod, thereby achieving an acceptable vibration amplitude for the components, solving the problem of the casing easily accumulating rainwater and snowflakes, causing the casing to freeze and affect operation, thereby improving the equipment's ability to operate in extreme environments.

[0030] 3. The present invention adopts a technical solution that combines multi-sensor data fusion with fractal correction, and utilizes the collaborative work of traveling wave current sensors, vibration sensors and temperature sensors to monitor and locate high-voltage line faults in real time and accurately. It also ensures that fault information obtained from different angles can be effectively integrated, thereby improving the accuracy and robustness of positioning; at the same time, it ensures efficient signal propagation calculation and precise positioning even in complex environments, thereby enabling adaptive adjustment in a changing power line environment, reducing errors, and improving the accuracy and timeliness of fault location. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A perspective view of the present invention;

[0032] Figure 2 It is a schematic diagram of the expansion of the present invention;

[0033] Figure 3 is a cross-sectional view of the lower shell of the present invention;

[0034] Figure 4 for Figure 3 Enlarged view of point A in the middle;

[0035] Figure 5 This is a schematic diagram of the bottom structure of the inner ring of the present invention;

[0036] Figure 6 This is a schematic diagram of the right side structure of the threaded column of the present invention;

[0037] Figure 7 This is a PLC module position distribution diagram of the present invention;

[0038] Figure 8 Schematic diagram of the PLC module of the present invention.

[0039] Among them, 1. Lower shell; 2. Upper shell; 3. Magnetic buckle; 4. Clamp; 5. Clamp block; 6. Limit plate; 7. Slide; 8. Fixed plate 1; 9. Telescopic rod; 10. Inner ring; 11. Support block; 12. Double-headed motor; 13. Rotating column; 14. Connecting rod 1; 15. Threaded column; 16. Connecting rod 2; 17. Cam; 18. Gear; 19. Fixed plate 2; 20. Connecting rod 3; 21. Pull plate; 22. Gear ring; 23. PLC module. DETAILED DESCRIPTION

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] Example 1:

[0042] Please see the attached Figure 1 -Attached Figure 7, an embodiment of the present invention provides a distributed precise positioning online monitoring device for hidden dangers in high-voltage power lines, including a lower shell 1, an upper shell 2 is installed on the top of the lower shell 1, magnetic buckles 3 are provided inside the lower shell 1 and the upper shell 2, and a chuck 4 is rotated inside the lower shell 1 and the upper shell 2; an inner ring 10 is installed inside the lower shell 1 and the upper shell 2, support blocks 11 are fixed on both sides of the lower shell 1 and the upper shell 2, a PLC module 23 is provided between the inner ring 10 and the support block 11, a slide groove 7 is provided inside the chuck 4, and clamping blocks 5 distributed in a ring array are provided inside the chuck 4, and the clamping blocks 5 all slide inside the slide groove 7, one end of the clamping block 5 is fixed with a limit plate 6, and a fixed plate 8 is fixed on the side of the limit plate 6 away from the clamping block 5, and a telescopic rod 9 is installed on one side of the fixed plate 8, a support block 11 is installed inside the chuck 4, a double-headed motor 12 is provided on the top of the support block 11, and the support block 11 rotates inside. There is a rotating column 13, the output end of the double-headed motor 12 is fixed on one side of the rotating column 13, and a connecting rod 14 is sliding inside the other side of the rotating column 13. A threaded column 15 is fixed to the end of the connecting rod 14 away from the rotating column 13, and a connecting rod 2 16 is fixed to the end of the threaded column 15 away from the connecting rod 14. A gear 18 slides on the outer wall of the connecting rod 2 16, and a gear ring 22 is installed on the side of the chuck 4 away from the clamping block 5. The gear ring 22 is engaged with the gear 18, and a connecting assembly is provided on one side of the gear 18; the connecting assembly includes a connecting rod three 20, and the connecting rod three 20 rotates on the side of the gear 18 away from the connecting rod two 16. The raised cylindrical rotation at one end of the connecting rod three 20 has a fixed plate two 19, and the fixed plate two 19 is fixed inside the inner ring 10; a cam 17 is fixed to the outer wall of the rotating column 13; a pull plate 21 is fixed to the outer walls of the lower shell 1 and the upper shell 2; the threaded column 15 is threaded inside the chuck 4.

[0043] Specifically, during the device installation process, a drone can first be used to precisely transport the clamping plate 21 to the designated installation location. Once the plate 21 is clamped and stably delivered to the target location by the drone, the tightness of the drone's grip can be adjusted to control the degree of opening and closing between the lower shell 1 and the upper shell 2. At this point, after transporting to the designated location, the cable can be positioned at the center of the device, and the closing of the lower shell 1 and the upper shell 2 can be further controlled by the plate 21. This ensures magnetic attraction between the magnetic buckles 3, allowing the lower shell 1 and the upper shell 2 to be completely closed and the cable to be securely wrapped between them.

[0044] At the same time, the cable is not only wrapped between the lower shell 1 and the upper shell 2, but also positioned in the circular hole in the middle of the chuck 4. In this structure, the two sides of the support block 11 are made of rubber material for extrusion and deformation, which fits the cable tightly, effectively blocks the gap, and prevents external environmental factors from interfering with the equipment. In order to further enhance stability, the double-headed motor 12 is started to drive the rotating column 13 to rotate. During the rotation of the rotating column 13, the connecting rod 14 is driven by the rotating column 13, so that the threaded column 15 also rotates synchronously. Due to the thread design, the rotation of the threaded column 15 drives the connecting rod 14 to slide along the inside of the rotating column 13, and the connecting rod 2 16 also rotates with the threaded column 15 to maintain synchronization.

[0045] During this process, both connecting rod 14 and connecting rod 2 16 are equipped with limit bars to ensure that their sliding motion does not interfere with the free rotation of threaded post 15 and gear 18. As gear 18 rotates, it engages with the tooth marks of gear ring 22, driving the gear ring 22 to rotate along with it, thereby causing the entire circular chuck 4 to rotate to a certain extent. The chuck 4 is mounted between the lower shell 1 and the upper shell 2, allowing for moderate rotation within its respective mounting positions to prevent disengagement, thus ensuring stable operation of the chuck 4.

[0046] The rotation of the chuck 4 is achieved through the provision of a chute 7 and a curved channel, allowing the clamping block 5 to slide within the constraints of the limit plate 6. This design effectively prevents the clamping block 5 from rotating with the chuck 4, limiting the movement of the clamping block 5 toward and away from each other only when the position of the chute 7 changes. Furthermore, the telescopic rod 9 and the fixing plate 8 work together to ensure that the clamping block 5 does not change position with the rotation of the chuck 4, further ensuring that the cable is clamped and secure, ensuring that the cable is fixed during equipment installation.

[0047] Throughout the entire process, the threaded column 15 is precisely adjusted as it rotates, ensuring the stability of the device. Even when the double-ended motor 12 is not working, the stable rotation of the threaded column 15 ensures that the clamping block 5 always maintains the clamping effect on the cable, preventing the cable from coming loose.

[0048] And when the rotating column 13 rotates, the corresponding cam 17 will rotate with the rotating column 13 as the center of the circle, and then through the eccentric setting, one end of the soft rubber head will continuously hit the position of the upper shell 2. At the same time, if the rotating column 13 rotates back and forth repeatedly, the corresponding telescopic rod 9 will also be continuously in a telescopic state, so that one end of the soft rubber head of the telescopic rod 9 can continuously hit the lower shell 1 or the upper shell 2 and cooperate with the cam 17 to cause the lower shell 1 or the upper shell 2 to vibrate slightly, so that in extremely cold weather, the device can prevent rainwater from accumulating and freezing through this vibration, and snowflakes can also be shaken off to a certain extent when it snows.

[0049] Example 2:

[0050] Please see the attached Figure 8 , the PLC module 23 includes:

[0051] Multiple sensor units, each used to collect environmental data and line status data at different locations on the high-voltage line; a data processing unit connected to the multiple sensor units, used to receive data sent by the multiple sensor units, perform data processing, and accurately locate the fault location based on the time difference inversion method, fractal correction factor and multi-scale wave equation; a communication module connected to the data processing unit, used to send the fault location results, fault type and other related data processed by the data processing unit to the background monitoring platform via wireless communication;

[0052] The backend monitoring platform is connected to the communication module and receives data from the communication module through wireless communication. It is used to diagnose and analyze faults, generate fault handling instructions, and notify relevant personnel to perform maintenance.

[0053] Multiple sensor units include:

[0054] Traveling wave current sensor, which is used to collect traveling wave current signals in high-voltage lines;

[0055] Vibration sensor, which is used to collect mechanical vibration signals near the high-voltage line;

[0056] A temperature sensor is used to collect temperature change data on the circuit surface;

[0057] Multiple sensor units process the collected signals through data fusion algorithms and output comprehensive fault information for further analysis and processing by the data processing unit;

[0058] The data processing unit uses time difference inversion method, fractal correction factor, multi-scale wave equation and adaptive optimization algorithm to locate faults;

[0059] In the data processing unit, the time difference inversion method includes the arrival time difference of the fault signal measured by multiple sensors, determines the signal propagation path through the time difference inversion method, and calculates the fault point location based on the time difference information;

[0060] The fractal correction factor is used to dynamically correct the propagation speed. The correction factor is adjusted according to the influence of terrain and climate environmental factors to ensure accurate positioning. The calculation formula of the time difference inversion method is:

[0061]

[0062] Where Δt i,j is the time difference between sensors i and j, indicating the signal propagation time difference from the fault point to sensors i and j; d i,jis the spatial distance between sensors i and j, indicating the physical distance between the fault point and the two sensors; v is the signal propagation speed, usually the propagation speed of electromagnetic waves in the medium; ∈(x) is the fractal correction factor, indicating the influence of terrain, climate or other environmental factors on signal propagation, which varies according to the location (x);

[0063] The multiscale wave equation in the data processing unit is used to describe the signal propagation process. The wave equation takes into account the changes in the signal propagation path in the power line caused by terrain and climate change. The modified form of the wave equation is:

[0064]

[0065] in, is the Laplace operator, which represents the second-order derivative in space and is used to describe the expansion and change of the signal in space; u(x,t) is the displacement of the signal, usually referring to the signal strength or current value at position x; v is the propagation speed of the signal, usually referring to the propagation speed of electromagnetic waves or other fluctuations; S(t) is the time scale factor, which represents the time scale change during the signal propagation process and is used to adjust the propagation speed to take into account the influence of environmental factors; The second-order time derivative of the signal u represents the acceleration or rate of change of the signal over time; For time t 2 The second-order partial derivative is usually used to describe the rate of change of a signal or physical quantity over time; f(x, t) is the external disturbance source, which represents the external force or excitation source that affects the propagation of the signal;

[0066] The backend monitoring platform analyzes the fault type based on the real-time data received, generates processing instructions, and sends the fault processing instructions to relevant personnel via SMS, email, or application notifications for fault repair and emergency response.

[0067] Specifically, in this invention, multiple sensor units are core components of a distributed, online monitoring system for accurately locating hidden dangers in high-voltage lines. Each sensor unit works closely with other system modules to achieve real-time monitoring and precise location of high-voltage line faults. Each sensor unit collects real-time status data from the high-voltage line, including current signals, mechanical vibration, temperature, and other information. This data is processed using a data fusion algorithm to provide reliable evidence for fault location.

[0068] Typically, sensor units include, but are not limited to, traveling wave current sensors, vibration sensors, and temperature sensors. The selection and configuration of each sensor are optimized based on actual monitoring requirements and line characteristics, ensuring efficient and stable operation of the monitoring system in complex environments. Multiple sensor units are typically installed at various locations along a transmission line, working together to provide comprehensive data support.

[0069] In this embodiment, a traveling wave current sensor is used to collect the traveling wave current signal in real time. This sensor is primarily used to detect current fluctuations caused by faults in high-voltage lines, particularly those resulting from lightning strikes, tree obstructions, or equipment failures. When a fault occurs, the traveling wave current signal generates instantaneous current pulses, which the sensor transmits to a data processing unit for further analysis by the fault location system.

[0070] Specifically, traveling wave current sensors use high-frequency sampling technology to rapidly record and transmit transient traveling wave signals generated by faults or external factors in high-voltage lines. Rapid sampling within the sensor unit allows it to quickly capture current fluctuations. Using time inversion, the sensor calculates the propagation time difference, ultimately determining the precise location of the fault.

[0071] Alternatively, vibration sensors are used to monitor mechanical vibrations in the environment surrounding transmission lines, particularly those caused by external forces such as wind disturbances or wind deflection. These sensors can effectively detect the vibration amplitude of transmission lines, especially when external factors such as wind, snow, or animal disturbances act on the lines. These sensors can capture minute vibration changes in real time and provide feedback to the data processing unit.

[0072] When vibration signals are collected in conjunction with traveling wave current signals, fault location accuracy can be improved. In some embodiments, the collaboration between the vibration sensor and the traveling wave current sensor can better identify whether the fault is caused by external forces, thereby improving the accuracy and robustness of the system.

[0073] Furthermore, in this embodiment, the temperature sensor is used to collect data on temperature changes on the transmission line surface. This is particularly true in winter, when line faults may occur due to ice or snow accumulation. The temperature sensor can accurately measure line surface temperature changes and provide timely feedback on potential danger signals, such as whether ice or snow is accumulating on the line.

[0074] Temperature sensors can provide important early warning information for potential problems, such as ice accumulation or wire damage caused by high temperatures, enabling early warning and location of potential issues before they become more severe. By integrating data from other sensors, the output of temperature sensors can be combined with current and vibration data to further improve the accuracy of fault identification.

[0075] In one possible implementation, multiple sensor units transmit collected data to a data processing unit via wireless communication. The data processing unit performs a comprehensive analysis of the collected data and applies time-of-flight inversion, fractal correction factors, multiscale wave equations, and adaptive optimization algorithms to accurately locate the fault. Sensor data is rapidly transmitted to the data processing unit via a wireless communication network, ensuring real-time and accuracy.

[0076] On this basis, the time difference inversion method is used to further calculate the exact location of the fault based on the fault signal propagation time difference measured by the sensor. The calculation formula of the time difference inversion method is:

[0077]

[0078] in:

[0079] Where Δt i,j is the time difference between sensors i and j, indicating the signal propagation time difference from the fault point to sensors i and j; d i,j is the spatial distance between sensors i and j, indicating the physical distance between the fault point and the two sensors; v is the signal propagation speed, usually the propagation speed of electromagnetic waves in the medium; ∈(x) is the fractal correction factor, indicating the influence of terrain, climate or other environmental factors on signal propagation, which varies according to the location (x).

[0080] By further processing the time difference inversion and combining it with the fusion of sensor data, the data processing unit can achieve accurate fault location, especially in complex environments, and can effectively eliminate errors caused by environmental factors.

[0081] In this embodiment, the layout and configuration of the multiple sensor units is not limited to a single configuration. In some embodiments, the sensor units can be flexibly adjusted based on the length of the line, environmental characteristics, and specific installation locations. By deploying multiple sensor units at different locations, the operating status of the high-voltage line can be comprehensively monitored, ensuring full coverage and high-precision fault location.

[0082] At the same time, collaboration between sensor units provides stronger data support for fault diagnosis. For example, when multiple sensors detect abnormal signals at the same location, the data processing unit prioritizes the combined results of these signals, increasing the accuracy and reliability of fault location. This allows the system to quickly identify the nature and location of the fault by fusing data from multiple points, enabling timely remediation measures to prevent further equipment damage or accidents.

[0083] As a core component of the distributed, precise online monitoring system for high-voltage line hidden dangers, the data processing unit is responsible for receiving and processing data from multiple sensor units. The data processing unit not only accurately calculates the fault location but also dynamically adjusts based on the collected data. Its mission is to comprehensively analyze the signals collected by the various sensor units, utilizing a variety of advanced algorithms to accurately locate and analyze the nature of the fault.

[0084] Typically, wireless communication is used to transmit data between the data processing unit and multiple sensor units. The data processing unit processes the traveling current, vibration, and temperature signals collected by the sensors, accurately analyzing the data using techniques such as time-of-flight inversion, fractal correction factors, and multiscale wave equations, thereby efficiently locating the fault location.

[0085] In this embodiment, the data processing unit receives signals from the traveling wave current sensor, vibration sensor, and temperature sensor and first performs preliminary data cleaning and noise removal. It then uses the time difference inversion method to calculate the fault location based on the signal propagation time difference measured by the sensors. During this process, the data processing unit also considers the influence of environmental factors and dynamically adjusts the propagation speed by introducing a fractal correction factor ∈(x).

[0086] As an option, the data processing unit also uses multiscale wave equations to model signal propagation, further improving the accuracy of signal propagation calculations in complex environments. The use of multiscale wave equations can take into account the propagation effects of signals at different spatial and temporal scales, making the processing more accurate. The calculation formula is:

[0087]

[0088] in, is the spatial second-order derivative of the signal u at position x and time t; v is the propagation speed of the signal; S(t) is the time scale factor, which represents the time scale adjustment during the signal propagation process; is the second-order derivative of the signal u with respect to time, indicating the acceleration or rate of change of the signal; f(x, t) is the external disturbance source, indicating the external factors that may affect the propagation of the signal; For time t2 Take the second-order partial derivative.

[0089] In one possible implementation, a data processing unit uses this wave equation to analyze current, vibration, and temperature signals in real time, ensuring accurate modeling of signal propagation at different scales. This multi-scale modeling technique effectively addresses potential signal variations in complex environments, particularly in mountainous and forested terrain, eliminating signal propagation errors caused by environmental variations.

[0090] Specifically, the data processing unit integrates data from multiple sensors in time and space, analyzing the time differences and fluctuations in signal propagation to accurately determine the fault location. Furthermore, the data processing unit compares the received signals with historical data models to optimize fault location results, further improving the system's fault detection rate and location accuracy.

[0091] Optionally, the data processing unit can be equipped with an adaptive optimization algorithm, such as particle swarm optimization (PSO), to continuously adjust system parameters to reduce positioning errors. In practice, as sensor data is continuously updated, the data processing unit can optimize parameter settings in real time, allowing the system to better adapt to changing environmental conditions.

[0092] In some embodiments, the data processing unit dynamically selects the most appropriate optimization algorithm for fault location based on current environmental conditions, sensor data, and historical data. For example, when environmental factors change dramatically, the system can automatically adjust the parameters in the wave equation to ensure the stability and reliability of the location results.

[0093] As a crucial component of the distributed, precise online monitoring system for high-voltage line hidden dangers, the communication module is responsible for transmitting the fault location results and related data calculated by the data processing unit to the backend monitoring platform in real time. The communication module plays a crucial role, not only carrying out the system's real-time data transmission tasks but also ensuring the rapid transfer and efficient sharing of monitoring information. Working closely with the aforementioned sensor unit and data processing unit, the communication module ensures the real-time responsiveness and efficiency of the entire system.

[0094] Typically, the communication module serves as a bridge for information transmission within a system. It transmits data from multiple sensor units to the data processing unit via wireless communication. This processed data and fault location information are then transmitted to the backend monitoring platform. Due to the unique environment and long spans of high-voltage lines, the design of the communication module requires strong anti-interference capabilities and stability.

[0095] In this embodiment, the communication module utilizes wireless communication technologies, such as GPRS, Wi-Fi, or 5G network protocols, to ensure reliable and real-time data transmission. Specifically, the communication module can select the appropriate communication protocol based on actual environmental conditions and system requirements. For example, in long-distance, high-speed transmission scenarios, 5G technology can ensure low latency and high bandwidth for data transmission. In more complex environments, however, low-power wide-area network (LPWAN) technologies, such as NB-IoT or LoRaWAN, may be preferred.

[0096] As an option, the communication module can also be designed with wireless network redundancy to ensure that if one communication channel fails, the system can still continue to transmit data through the backup channel, ensuring high reliability and continuity of the monitoring system. This redundancy design can improve the stability of the system in special environments or extreme conditions.

[0097] Specifically, the main functions of the communication module include:

[0098] Data transmission: The fault location, fault type and real-time monitoring data of related signals calculated in the data processing unit are sent to the background monitoring platform through wireless communication.

[0099] Signal coding and encryption: To ensure data security during transmission, the communication module supports signal coding and encryption technology. Encryption protocols are used during data transmission to prevent data from being stolen or tampered with during transmission.

[0100] Real-time guarantee: The communication module can ensure the real-time nature of fault information. The system can respond quickly when a fault occurs and transmit the fault information to the background monitoring platform through the communication module, ensuring that relevant personnel can obtain fault diagnosis and processing instructions in a timely manner.

[0101] In some embodiments, the communication module automatically adjusts the transmission method based on the priority and volume of the received data. For high-priority emergency fault information, the communication module can prioritize transmission over high-speed, low-latency channels such as 5G networks. For general monitoring data, low-power, low-bandwidth communication channels can be selected to reduce network load.

[0102] In one possible implementation, the communication module can also support data compression technology to reduce the amount of data transmitted, thereby improving transmission speed and bandwidth utilization. Data compression technology is particularly important for low-frequency and redundant data, such as periodic environmental monitoring data, and can significantly improve the overall transmission efficiency of the system.

[0103] In another possible implementation, the communication module can also include multiple wireless communication interfaces that can automatically switch based on actual environmental conditions and network coverage. For example, if a communication interface fails, the system can continue data transmission through the backup interface, ensuring continuity and high availability of the monitoring system.

[0104] The communication module and the data processing unit communicate via a data transmission protocol. Typically, these modules utilize common wireless communication protocols, such as MQTT or HTTP, to ensure efficient data exchange and rapid data transmission to the backend monitoring platform. Data is encoded and verified during transmission according to predefined protocols to ensure reliability and integrity.

[0105] Specifically, the communication module transmits data from the data processing unit to the backend monitoring platform at specified intervals, based on system settings. For fault location results, the communication module immediately packages the fault location, fault type, and related data and sends them to the backend monitoring platform after the data processing unit completes calculations. Upon receiving the data, the backend monitoring platform immediately analyzes the fault information, generates processing instructions, and notifies relevant personnel to perform fault repairs.

[0106] The primary function of the backend monitoring platform is to process and analyze data transmitted from multiple sensor units and data processing units. It not only receives and stores large amounts of sensor data but also performs real-time analysis and processing based on this data, enabling immediate diagnosis of fault types, locating fault points, and providing appropriate troubleshooting recommendations. As the core of the system, the efficiency and stability of the backend monitoring platform directly impact the overall performance of the monitoring system.

[0107] In this embodiment, the background monitoring platform is connected to the communication module via wireless communication, and receives the fault location results, fault types and related monitoring data transmitted from the data processing unit. After further processing by the background monitoring platform, these data will generate a fault diagnosis report and automatically generate processing instructions based on the fault type. Specifically, the fault location results received by the background monitoring platform include: the fault point. As an option, the background monitoring platform can compare and analyze the received data with historical monitoring data to check whether there are repetitive faults or potential risks. Based on this analysis, the background monitoring platform can not only quickly diagnose existing faults, but also predict potential fault risks, thereby providing the system with an early warning function to help maintenance personnel prevent faults and perform equipment maintenance in advance. Specifically, the background monitoring platform uses its powerful data analysis capabilities to automatically identify the fault type and possible fault source, and send real-time fault handling notifications to staff.

[0108] In some embodiments, the backend monitoring platform further combines historical data, real-time monitoring data, and external environmental factors, using artificial intelligence algorithms to predict fault trends. This allows the platform to issue early warnings when potential faults emerge that haven't yet fully manifested, thereby avoiding system downtime or even larger-scale failures. For example, by analyzing sensor data, the backend monitoring platform can detect abnormal current fluctuations. Combined with temperature and vibration data, it can infer potential problems like line overheating and equipment aging, allowing for proactive maintenance measures.

[0109] Specifically, the backend monitoring platform utilizes efficient data processing algorithms to classify and locate faults. After receiving fault location results from the data processing unit via the communication module, the backend monitoring platform further analyzes the data according to a predefined algorithm, calculating the specific location of the fault and confirming the fault type (e.g., lightning strike, tree obstruction, wind deviation), and verifying the location results based on historical data. The backend platform also displays real-time location information through a visual interface, helping operations and maintenance personnel intuitively understand the fault location and impact range.

[0110] In one possible implementation, the backend monitoring platform not only identifies the fault type but also generates an emergency response plan through data interaction. Using this emergency response plan, the backend monitoring platform can generate real-time repair instructions, notifying inspectors or operators to perform on-site remediation. These repair instructions are sent to relevant personnel via SMS, email, or app notifications, ensuring that the fault is addressed promptly and effectively.

[0111] Furthermore, the backend monitoring platform can interface with external intelligent operation and maintenance systems to provide fault location and early warning data. This functionality enables power system operators to directly view fault information, diagnose, and make decisions on the backend platform. Furthermore, these diagnostic and analysis results from the backend monitoring platform serve as the basis for subsequent maintenance and overhaul work, ensuring the reliability and safety of high-voltage lines.

[0112] Specifically, the background monitoring platform includes the following functional modules:

[0113] Fault diagnosis module: Analyzes the received fault signals, automatically determines the fault type such as lightning strike, tree obstacle, wind deviation, external force damage, etc., and generates a fault report.

[0114] Positioning analysis module: Based on the fault location information provided by the data processing unit and combined with environmental factors, the fault point is accurately determined and a fault distribution map is drawn.

[0115] Early warning and notification module: When potential failure risks or abnormalities are detected, the background monitoring platform will issue an early warning through the alarm system and promptly send the failure information to relevant personnel via SMS, email, etc.

[0116] Historical data comparison module: Compare historical fault data with current data to check whether there are potential repeated faults in the system and make trend predictions.

[0117] As another possible implementation, the backend monitoring platform can also perform remote control based on the fault diagnosis results. For example, through the platform's remote control function, the backend monitoring platform can remotely adjust the operating parameters of the equipment in certain situations to prevent further deterioration of the fault.

[0118] Working principle: When the equipment is being installed, the position of the clamping plate 21 can be clamped by the drone to transport it to the designated installation position. At the same time, the degree of opening and closing between the lower shell 1 and the upper shell 2 can be controlled by the tightness of the drone's clamping. At this time, when it is transported to the designated position, the cable is allowed to heal the middle position of the equipment, and the pulling plate 21 is controlled to close the lower shell 1 and the upper shell 2, so that the magnetic buckle 3 can be magnetically attracted together, so that the lower shell 1 and the upper shell 2 can be closed and the cable can be wrapped in the middle position. At this time, in addition to being located between the lower shell 1 and the upper shell 2, the cable is also located in the round hole in the middle of the chuck 4. At this time, the two sides of the support block 11 are deformed by the extrusion of the rubber material, so that it fits tightly with the cable, blocks the gap, and prevents the external environment from affecting the equipment. At the same time, the double-headed motor 12 starts to run, so that the rotating column 13 is driven to rotate. The rotating rotating column 13 will drive the threaded column 15 to rotate synchronously through the connecting rod 14. When the threaded column 15 rotates, it will drive the connecting rod 14 to slide inside the rotating column 13 due to the thread relationship. At the same time, the connecting rod 2 16 will also rotate with the threaded column 15, and while rotating, it will synchronize with the connecting rod 14 inside the gear 18. Sliding, connecting rod 14 and connecting rod 2 16 are both provided with limit strips, which can slide without affecting their ability to drive the threaded column 15 and gear 18 to rotate respectively. When gear 18 rotates, the corresponding connecting rod 3 20 rotates together with gear 18, and then under the restriction of fixed plate 2 19, the rotation effect is stable. At the same time, the rotating gear 18 will mesh with the tooth marks between the gear ring 22, allowing the gear ring 22 to drive the chuck 4 combined into a whole circle to rotate to a certain extent. The chuck 4 is respectively provided at the position of the lower shell 1 and the upper shell 2, which can be installed at their respective positions. The chuck 4 rotates to a certain extent and does not completely separate as a whole. The chuck 4 that rotates together can slide under the limit of the limit plate 6 through the setting of the curved channel of the slide groove 7, and the telescopic rod 9 set also limits the clamping block 5 from rotating with the chuck 4 through the fixed plate 8. It will only move closer and disperse due to the change in the position of the slide groove 7, so that the cable can be clamped by the clamping block 5, thereby stabilizing the installation position of the equipment. At the same time, the rotation of the threaded column 15 can ensure that it is stable, and the double-headed motor 12 will not loosen the clamping block 5 that clamps the cable even if it is not working.

[0119] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A distributed, precise positioning, online monitoring device for hidden dangers in high-voltage lines, comprising a lower shell (1), characterized in that: The top of the lower shell (1) is provided with an upper shell (2), and magnetic buckles (3) are provided inside the lower shell (1) and the upper shell (2), and a chuck (4) is rotated inside the lower shell (1) and the upper shell (2); an inner ring (10) is provided inside the lower shell (1) and the upper shell (2), and support blocks (11) are fixed on both sides of the lower shell (1) and the upper shell (2), and a PLC module (23) is provided between the inner ring (10) and the support block (11), and a slide groove (7) is provided inside the chuck (4), and clamping blocks (5) distributed in a ring array are provided inside the chuck (4), and the clamping blocks (5) all slide inside the slide groove (7), and a limiting plate (6) is fixed at one end of the clamping block (5), and a fixing plate (8) is fixed on the side of the limiting plate (6) away from the clamping block (5), and the fixing plate (8) is fixed on the side of the limiting plate (6) away from the clamping block (5). A telescopic rod (9) is installed on the side, a support block (11) is installed inside the chuck (4), a double-headed motor (12) is provided on the top of the support block (11), a rotating column (13) is rotated inside the support block (11), the output end of the double-headed motor (12) is fixed on one side of the rotating column (13), a connecting rod (14) is slid inside the other side of the rotating column (13), a threaded column (15) is fixed on the end of the connecting rod (14) away from the rotating column (13), a connecting rod (16) is fixed on the end of the threaded column (15) away from the connecting rod (14), a gear (18) is slid on the outer wall of the connecting rod (16), a gear ring (22) is installed on the side of the chuck (4) away from the clamping block (5), the gear ring (22) is meshed with the gear (18), and a connecting component is provided on one side of the gear (18); The PLC module (23) comprises: Multiple sensor units, each used to collect environmental data and line status data at different locations on the high-voltage line; a data processing unit connected to the multiple sensor units, used to receive data sent by the multiple sensor units, perform data processing, and accurately locate the fault location based on the time difference inversion method, fractal correction factor, and multi-scale wave equation; The data processing unit uses a time difference inversion method, a fractal correction factor, a multi-scale wave equation and an adaptive optimization algorithm to locate the fault; In the data processing unit, the time difference inversion method includes the arrival time difference of the fault signal measured by multiple sensors, the signal propagation path is determined by the time difference inversion method, and the fault point location is calculated based on the time difference information; The fractal correction factor is used to dynamically correct the propagation speed. The correction factor is adjusted according to the influence of terrain and climate environmental factors to ensure accurate positioning. The calculation formula of the time difference inversion method is: Where Δt i,j is the time difference between sensors i and j, indicating the signal propagation time difference from the fault point to sensors i and j; d i,j is the spatial distance between sensors i and j, indicating the physical distance between the fault point and the two sensors; v is the signal propagation speed, usually the propagation speed of electromagnetic waves in the medium; ∈(x) is the fractal correction factor, indicating the influence of terrain, climate or other environmental factors on signal propagation, which varies according to the location (x); The multi-scale wave equation in the data processing unit is used to describe the signal propagation process. The wave equation takes into account the changes in the signal propagation path in the power line due to terrain and climate change. The modified form of the wave equation is: in, is the Laplace operator, which represents the second-order derivative in space and is used to describe the expansion and change of the signal in space; u(x,t) is the displacement of the signal, usually referring to the signal strength or current value at position x; v is the propagation speed of the signal, usually referring to the propagation speed of electromagnetic waves or other fluctuations; S(t) is the time scale factor, which represents the time scale change during the signal propagation process and is used to adjust the propagation speed to take into account the influence of environmental factors; The second-order time derivative of the signal u represents the acceleration or rate of change of the signal over time; For time t 2 The second-order partial derivative is usually used to describe the rate of change of a signal or physical quantity over time; f(x, t) is an external disturbance source, which represents the external force or excitation source that affects the propagation of the signal.

2. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 1 is characterized in that: The connecting assembly includes a connecting rod three (20), and the connecting rod three (20) rotates on the side of the gear (18) away from the connecting rod two (16). A protruding cylinder at one end of the connecting rod three (20) rotates with a fixed plate two (19), and the fixed plate two (19) is fixed inside the inner ring (10).

3. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 1 is characterized in that: A cam (17) is fixed to the outer wall of the rotating column (13).

4. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 1 is characterized in that: Pull plates (21) are fixed to the outer walls of the lower shell (1) and the upper shell (2).

5. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 1 is characterized in that: The threaded column (15) is threaded inside the chuck (4).

6. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 1 is characterized in that: The PLC module (23) further comprises: The communication module is connected to the data processing unit and is used to send the fault location results, fault types and other related data processed by the data processing unit to the background monitoring platform through wireless communication; The background monitoring platform is connected to the communication module and receives data from the communication module through wireless communication. It is used to diagnose and analyze faults, generate fault handling instructions, and notify relevant personnel to perform maintenance.

7. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 1 is characterized in that: The plurality of sensor units include: Traveling wave current sensor, which is used to collect traveling wave current signals in high-voltage lines; Vibration sensor, which is used to collect mechanical vibration signals near the high-voltage line; A temperature sensor is used to collect temperature change data on the circuit surface; The multiple sensor units process the collected signals through a data fusion algorithm and output comprehensive fault information for further analysis and processing by the data processing unit.

8. The distributed precise positioning online monitoring device for hidden dangers of high-voltage lines according to claim 6 is characterized in that: The background monitoring platform analyzes the fault type based on the received real-time data, generates processing instructions, and sends the fault processing instructions to relevant personnel via SMS, email, or application notification to perform fault repair and emergency response.

Images