Unmanned aerial vehicle zero-value insulator live detection device and method

Abstract

The invention relates to an unmanned aerial vehicle zero-value insulator live detection device and method, an execution module comprises an AI image recognition unit and a detection probe, the detection probe integrates a voltage sensor and a resistance sensor and supports two modes of live resistance detection and distributed voltage detection, the AI image recognition unit is adjacent to the root of the detection probe, and the AI image recognition unit is adjacent to the root of the detection probe. The image acquisition module is used for acquiring insulator steel cap images and outputting positioning signals; the controller mainboard is electrically connected with the detection probe, the rotating mechanism and the AI image recognition unit through shielding cables, and the controller mainboard is used for receiving a positioning signal of the AI image recognition unit, receiving voltage detection data and / or current detection data transmitted by the detection probe, processing the detection data and obtaining a detection result of the state of the insulator. According to the invention, a dual-mode cooperation mechanism of'distributed voltage preliminary screening + charged resistance verification 'is adopted, and AI automatic positioning and mode automatic switching functions are combined, so that the detection efficiency is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of power equipment testing technology, and in particular to a device and method for detecting live insulators of unmanned aerial vehicles (UAVs) with zero values. Background Technology

[0002] With the continuous improvement of power grid voltage levels and the expansion of transmission line coverage, porcelain insulators, as crucial insulation support equipment, directly affect the safety and stability of the power grid. However, insulators exposed to complex and harsh environments for extended periods are highly susceptible to degradation, resulting in "zero-value" insulators. This significantly reduces their insulation performance and increases the risk of serious accidents such as flashover, string failure, and even line breakage and tower collapse. Therefore, research on efficient and accurate zero-value insulator detection technology is of significant engineering importance and urgent practical necessity.

[0003] Currently, existing methods for detecting zero-value insulators both domestically and internationally include the traditional spark gap method, as well as non-contact methods such as infrared imaging, ultraviolet imaging, and electric field distribution. Among these, the spark gap method is simple in principle and convenient to implement, but requires manual tower climbing, resulting in low detection efficiency, high safety risks, and poor environmental adaptability. Infrared imaging struggles to capture temperature changes in internal insulator defects, leading to missed or false detections. The detection sensitivity of ultraviolet imaging is significantly affected by equipment performance and environmental factors such as external light and humidity. While the electric field distribution method has strong anti-interference capabilities, most related testing equipment is still in the experimental verification stage, lacking mature products suitable for engineering sites.

[0004] Furthermore, existing insulator string inspection robots have many limitations: some robots cannot perform live inspections, have low walking efficiency, and poor adaptability to insulator size and shape; some robots are heavy, have complex mechanisms, lack flexibility, and require manual assistance for loading and unloading, failing to fully free up labor; still others are applicable to only a single insulator type, have slow inspection speeds, and cannot meet the needs of large-scale power grid operation and maintenance. Therefore, there is an urgent need to develop an efficient, accurate, safe, and highly adaptable zero-value insulator inspection device. Summary of the Invention

[0005] Therefore, the technical problem to be solved by the present invention is to overcome the technical defects existing in the prior art, and to propose a device and method for detecting zero-value insulators of UAVs. It adopts a dual-mode collaborative mechanism of "distributed voltage screening + live resistance verification" and combines AI automatic positioning and automatic mode switching functions to significantly improve detection efficiency.

[0006] To address the aforementioned technical problems, this invention provides a device for detecting liveness of zero-value insulators in unmanned aerial vehicles (UAVs), comprising: A support rod having a first end and a second end disposed opposite to each other along its length; A mounting bracket is installed on the support rod. The mounting bracket is equipped with a universal quick-release interface and locking buckle adapted to the UAV, which is used to stably mount the detection device on the UAV. A rotating mechanism, which is mounted on the first end of the support rod; The execution module includes an AI image recognition unit and a detection probe. The detection probe is fixedly connected to the end of the rotating mechanism away from the support rod. The detection probe adopts a dual-electrode structure and integrates a voltage sensor and a resistance sensor, supporting two modes: live resistance detection and distributed voltage detection. The AI ​​image recognition unit is fixedly installed at the end of the rotating mechanism away from the support rod. The AI ​​image recognition unit is adjacent to the root of the detection probe and is arranged at an angle of 15° to 30° with the detection probe. The distance between the center of its lens and the insulator steel cap is 5cm to 10cm. It is used to acquire images of the insulator steel cap and output positioning signals. The controller motherboard is installed at the second end of the support rod. The controller motherboard is electrically connected to the detection probe, the rotating mechanism and the AI ​​image recognition unit through shielded cables. The controller motherboard is used to receive the positioning signal of the AI ​​image recognition unit to control the rotating mechanism to drive the detection probe to make precise contact. At the same time, it receives the voltage detection data and / or current detection data transmitted by the detection probe, processes the detection data and obtains the detection result of the insulator status.

[0007] In one embodiment of the present invention, a data transmission module is further included. The data transmission module is mounted on the support rod and is used to transmit the detection data of the detection probe to the controller motherboard.

[0008] In one embodiment of the present invention, the support rod is made of epoxy resin insulating material.

[0009] In one embodiment of the present invention, the surface of the detection probe is coated with an anti-fouling and insulating coating, and its electrode end is provided with an elastic buffer structure with a buffer stroke of 0-5mm. A micro airflow pump is also provided at the root of the detection probe, and the micro airflow pump is used to output compressed air to achieve self-cleaning of the detection probe.

[0010] In one embodiment of the present invention, the controller motherboard includes a signal generator, a data processor, and a parameter storage unit. The signal generator is used to generate multi-frequency detection signals, the data processor is used to execute the core detection algorithm and process various types of detection data, and the parameter storage unit is used to pre-store standard parameters and correction coefficients corresponding to different voltage levels and insulator types.

[0011] Furthermore, the present invention also provides a method for detecting live zero-value insulators of unmanned aerial vehicles based on the detection device described above, comprising the following steps: Step 1: Parameter initialization. After the detection device ascends with the drone and locates, it automatically reads the voltage level of the detection line and the type of insulator string, and loads the corresponding preset parameters from the parameter storage unit to complete the function initialization of the voltage sensor, resistance sensor, signal generator, and data transmission module; Step 2: Preliminary screening of distributed voltage. The AI image recognition unit guides the probe to accurately contact the steel cap of the insulator. Each single contact lasts for 0.5 s. The voltage sensor collects the current insulator voltage value Ux and the voltage values Ux-1 and Ux+1 of the adjacent two insulators at the preset sampling frequency, and synchronously collects the ambient electric field intensity E environment; Step 3: Electric field anti-interference processing. The collected voltage data is corrected through an electric field anti-interference algorithm. The algorithm formula is: U corrected = U collected - K electric field × E environment, where U collected is the original collected voltage of the voltage sensor, E environment is the ambient electric field intensity, and K electric field is the electric field correction coefficient; Step 4: Suspected zero value determination. Double criteria are used to determine the suspected zero value insulators. Meeting any one of the criteria means marking them as suspected zero value insulators and recording their position numbers; Step 5: Verification of live resistance. The controller main board automatically switches to the resistance detection mode. The detection probe maintains a contact pressure of 1.5 N. The signal generator injects a sinusoidal detection signal with an amplitude of 5 V in the order of 1 kHz → 10 kHz → 100 kHz, and the resistance sensor synchronously collects the response current Ix at each frequency; Step 6: Calculation of multi-frequency resistance. The corresponding resistance value Rf = U injected / Ix is calculated based on the injected voltage and the response current at each frequency, and the original resistance value is obtained through a weighted average algorithm; Step 7: Temperature compensation and correction. The ambient temperature T is collected by the temperature sensor. The controller main board automatically matches the temperature correction coefficient K temperature according to the temperature range, and compensates the original resistance value through the formula R corrected = R original × K temperature; Step 8: State grading determination. The insulator state is graded according to the compensated resistance value R corrected; Step 9: Probe self-cleaning. When detecting every 3 insulators or when the contact resistance > 5 Ω, the self-cleaning program is started, and the contact resistance is self-tested after cleaning; Step 10: Loop detection and report generation. Repeat steps 2 - 9 until the detection of the entire string of insulators is completed. The controller main board automatically generates a detection report, and the detection data is stored and uploaded after encryption processing.

[0012] In an embodiment of the present invention, the double criteria in step 4 are specifically: Criterion 1: U corrected < U standard × 50%, where U standard is the standard voltage drop of the insulator corresponding to the voltage level; Criterion 2: U<(Ux-1+Ux+1) / 2×30%.

[0013] In one embodiment of the present invention, the formula for the weighted average algorithm in step 6 is: Roriginal = (0.3 × R1kHz + 0.5 × R10kHz + 0.2 × R100kHz) / 1.0, where R1kHz, R10kHz, and R100kHz are the calculated resistance values ​​at frequencies of 1kHz, 10kHz, and 100kHz, respectively.

[0014] In one embodiment of the present invention, the correspondence between the temperature range in step 7 and the temperature of the correction coefficient K is as follows: The K-temperature value corresponds to the following ranges: -40℃ to -20℃ = 1.20; -19℃ to 0℃ = 1.10; 1℃ to 40℃ = 1.00; and 41℃ to 65℃ = 0.90. In one embodiment of the present invention, the state classification determination criterion in step 8 is: For voltage levels of 500kV and above, an insulator with an R correction of <500MΩ is considered a zero-value insulator; for voltage levels below 500kV, an insulator with an R correction of <300MΩ is considered a zero-value insulator; an insulator with an R correction higher than the zero-value threshold but lower than the standard value by 1.5 times is considered a degraded insulator; and an insulator with an R correction higher than the standard value by 1.5 times is considered a qualified insulator.

[0015] The technical solution of the present invention has the following advantages compared with the prior art: 1. This invention adopts a dual-mode collaborative mechanism of "distributed voltage initial screening + on-line resistance verification", combined with AI automatic positioning and automatic mode switching functions. The comprehensive detection time of a single insulator is only 2 seconds, which significantly improves the detection efficiency and the accuracy rate of zero-value insulator identification is ≥99.5%. 2. This invention is safe and reliable in operation. The drone mounting enables contactless operation, avoiding the risks of falling from heights and electric shock. Multiple protection mechanisms ensure the safety of the power grid and equipment. It is highly adaptable to the environment and scenarios, and can be compatible with insulator disc diameters of 260mm~420mm and voltage levels of 35kV-750kV, meeting the testing requirements of single to quadruple insulator strings. Attached Figure Description

[0016] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0017] Figure 1 This is a schematic diagram of the detection of the UAV zero-value insulator live-line detection device in a parallel state, as proposed in this invention.

[0018] Figure 2 yes Figure 1 A magnified view of part A above.

[0019] Figure 3 yes Figure 1 A magnified view of part B above.

[0020] Figure 4 This is a schematic diagram of the detection of the UAV zero-value insulator live detection device proposed in this invention in a 90° flipped state.

[0021] The attachment markings are as follows: 11. Support rod; 12. Mounting bracket; 13. Rotation mechanism; 141. Detection probe; 15. Controller motherboard. Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0023] Reference Figures 1 to 4 As shown, this embodiment of the invention provides a live-line detection device for zero-value insulators of unmanned aerial vehicles (UAVs), including a support rod 11, a mounting bracket 12, a rotating mechanism 13, an execution module, and a controller motherboard 15. The support rod 11 has a first end and a second end arranged opposite to each other along its length. The mounting bracket 12 is mounted on the support rod 11 and is provided with a universal quick-release interface and locking buckle adapted to the UAV for stably mounting the detection device on the UAV. The rotating mechanism 13 is mounted on the first end of the support rod 11. The execution module includes an AI image recognition unit and a detection probe 141. The detection probe 141 is fixedly connected to the end of the rotating mechanism 13 away from the support rod 11. The detection probe 141 adopts a dual-electrode structure and integrates a voltage sensor and a resistance sensor, supporting two modes: live resistance detection and distributed voltage detection. The AI ​​image recognition unit is fixedly installed at the end of the rotating mechanism 13 away from the support rod 11. The AI ​​image recognition unit is close to the root of the detection probe 141, and is arranged at an angle of 15° to 30° with the detection probe 141. The distance between the center of its lens and the insulator steel cap is 5cm to 10cm. It is used to acquire images of the insulator steel cap and output positioning signals. The controller motherboard 15 is installed at the second end of the support rod 11. The controller motherboard 15 establishes electrical connections with the detection probe 141, the rotating mechanism 13 and the AI ​​image recognition unit through shielded cables. The controller motherboard 15 is used to receive the positioning signals from the AI ​​image recognition unit to control the rotating mechanism 13 to drive the detection probe 141 to make precise contact. At the same time, it receives the voltage detection data and / or current detection data transmitted by the detection probe 141, processes the detection data, and obtains the detection results of the insulator status.

[0024] This invention adopts a dual-mode collaborative mechanism of "distributed voltage screening + on-line resistance verification" and combines AI automatic positioning and automatic mode switching functions. The comprehensive detection time of a single insulator is only 2 seconds, which significantly improves the detection efficiency and the accuracy of zero-value insulator identification is ≥99.5%.

[0025] In this embodiment, the voltage sensor is a high-precision differential voltage sensor with a measurement range of 0-50kV and an accuracy of ±0.1%. This voltage sensor integrates a metal shielding shell and an anti-electromagnetic interference shielding structure, effectively isolating the power frequency electric field and electromagnetic radiation interference around the high-voltage transmission line, ensuring the stability and accuracy of the insulator axial voltage value acquisition. The resistance sensor employs a high input impedance design, with an input impedance ≥100MΩ. Combined with a precision shunt resistor with an accuracy of ±0.01%, it can accurately acquire the response current after multi-frequency detection signal injection (measurement range 0-100μA), significantly reducing measurement errors caused by signal attenuation and external interference, providing reliable data support for the accurate calculation of insulator resistance values.

[0026] In one embodiment, the detection device further includes a data transmission module mounted on the support rod 11. The data transmission module transmits the detection data from the detection probe 141 to the controller motherboard 15. Preferably, the 5G module of the data transmission module supports NR SA / NSA dual-mode, and the LoRa module employs spread spectrum communication technology to ensure data transmission stability in complex environments.

[0027] In one embodiment, the controller motherboard 15 integrates a signal generator, a data processor, and a parameter storage unit. The signal generator generates 1kHz, 10kHz, and 100kHz three-frequency sinusoidal detection signals to provide a stable signal source for live resistance detection. The data processor executes core detection algorithms such as electric field anti-interference, multi-frequency resistance calculation, and temperature compensation, and simultaneously processes various detection data such as voltage, current, and temperature. The parameter storage unit pre-stores standard voltage thresholds, zero-value resistance thresholds, electric field correction coefficients, and temperature correction coefficients for different voltage levels (35kV-750kV), different connection forms (single to quadruple), and different types of insulators (bell-type, anti-pollution type, etc.).

[0028] As a preferred option, the controller motherboard 15 uses an STM32H7 series MCU chip with a processing speed of up to 480MHz. It has a built-in floating-point unit (FPU) and more than 1MB of Flash storage space and more than 256KB of RAM. It supports multi-task parallel processing and can efficiently complete the real-time control of signal generation, data processing and driving mechanism and communication module, meeting the low latency and high precision operation requirements of dual-mode collaborative detection.

[0029] In one embodiment, the support rod 11 is made of epoxy resin insulation material, which has excellent electrical insulation performance, mechanical strength and weather resistance, and withstands a breakdown voltage of ≥1500KV, which can meet the insulation safety requirements for live-line work on 35kV-750kV high-voltage transmission lines. At the same time, the lightweight characteristics of epoxy resin material can effectively reduce the overall weight of the device. Combined with the hollow structure design of the support rod 11, it further meets the requirements for lightweight mounting of the device and adapts to the load limitations of UAVs.

[0030] Furthermore, the aforementioned rotating mechanism 13 is fixedly assembled to the first end of the support rod 11. The rotating mechanism 13 includes a servo motor, an angle sensor, and a limiting mechanism. The output shaft of the servo motor is connected to the detection probe 141 via a keyway-fitted rigid coupling. The rigid coupling is an integrally formed aluminum alloy structure, with stepped inner holes at both ends adapted to the servo motor output shaft and the mounting shaft of the detection probe 141, respectively. The inner hole tolerance grade is H7, ensuring a tight fit with the two shafts. Type A flat keyways are provided at the corresponding inner holes of the servo motor output shaft and the coupling, achieving circumferential fixation and preventing relative rotation. The mounting shaft of the detection probe 141 and the inner hole at the other end of the coupling use the same keyway fit structure to ensure synchronous power transmission. Two radially symmetrical keyways are provided at both ends of the coupling. Each set screw hole, with its internal hexagonal cylindrical end set screw tightened to press against the outer surface of the corresponding shaft, achieves axial positioning and prevents axial movement between the coupling and the two shafts. After assembly, the coaxiality error of the servo motor output shaft, rigid coupling, and detection probe mounting shaft is ≤0.1mm, ensuring smooth and lossless power transmission. An absolute encoder with a resolution ≥1024 lines is used to collect real-time rotation angle data of the rotating mechanism and feed the angle signal back to the controller motherboard 15, forming a closed-loop control. The limit mechanism includes symmetrically arranged mechanical limit blocks and trigger-type limit switches to limit the extreme rotation stroke of the rotating mechanism. Combined with the program control of the controller motherboard 15, it achieves controllable rotation of the rotating mechanism from 0-360°, with a rotation angle control accuracy of ±0.3, meeting the detection angle adjustment requirements of single, double, triple, and quadruple insulator strings.

[0031] In one embodiment, the surface of the detection probe 141 is coated with an anti-fouling insulating coating, and its electrode end is provided with an elastic buffer structure with a buffer stroke of 0-5mm. A micro airflow pump is also provided at the root of the detection probe 141. The micro airflow pump is used to output compressed air to achieve self-cleaning of the detection probe 141.

[0032] In one embodiment, the outer surface of the detection probe 141 is coated with a superhydrophobic, anti-fouling, and insulating coating with a contact angle ≥110°. This coating combines anti-fouling and electrical insulation properties, effectively reducing the residue of dust, oil, frost, and other contaminants on the probe surface and preventing contaminants from affecting the stability of the detection signal. The electrode end of the detection probe is equipped with an elastic buffer structure with a buffer stroke of 0-5mm. The contact pressure can be adaptively adjusted within the range of 0.5~2N, ensuring reliable contact between the electrode and the insulator cap while preventing damage to the insulator surface from rigid contact. A miniature airflow pump is also fixedly installed at the root of the detection probe 141. This miniature airflow pump is a miniature diaphragm pump with a rated operating pressure of 0.3MPa. An axial air passage is pre-reserved inside the detection probe 141. One end of the air passage is connected to the outlet of the miniature airflow pump, and the other end extends to the side of the electrode end with a miniature air hole. The compressed air output by the miniature airflow pump blows the contact surface of the electrode end through the air passage and air hole, achieving the self-cleaning function of the detection probe 141.

[0033] In one embodiment, the mounting bracket 12 adopts a mature structure adapted for UAV mounting in the prior art, and its core function is to achieve stable assembly and reliable connection between the device and the UAV. Specifically, the mounting bracket 12 can be a structure including a connecting base plate, a buffer pad, and a standard quick-release locking assembly. The connecting base plate is fixed to the middle area of ​​the support rod by bolts, and the buffer pad is made of rubber to buffer the vibration transmission during UAV flight. The standard quick-release locking assembly is compatible with the mounting interface of mainstream industrial inspection UAVs, and has quick disassembly and anti-drop locking functions to ensure that the device is firmly connected during UAV flight and inspection operations, meeting the working conditions requirements of outdoor high-voltage transmission line inspection.

[0034] This invention is safe and reliable in operation. The drone-mounted system enables contactless operation, avoiding the risks of falling from heights and electric shock. Multiple protection mechanisms ensure the safety of the power grid and equipment. It is highly adaptable to various environments and scenarios, compatible with insulator disc diameters of 260mm to 420mm and voltage levels of 35kV to 750kV, and meets the testing requirements for single to quadruple insulator strings.

[0035] Corresponding to the above device embodiment, the present invention also provides a method for detecting live zero-value insulators of unmanned aerial vehicles based on the above detection device, the method comprising the following steps: Step 1: Parameter initialization. After the detection device takes off and is positioned with the drone, it automatically reads the voltage level of the detection line and the type of insulator string, loads the corresponding preset parameters from the parameter storage unit, and completes the functional initialization of the voltage sensor, resistance sensor, signal generator and data transmission module. Step 2: Preliminary screening of distributed voltage. The AI image recognition unit guides the probe to precisely contact the steel cap of the insulator, maintaining contact for 0.5 s each time. The voltage sensor collects the current insulator voltage value Ux and the voltage values Ux-1 and Ux+1 of the adjacent two insulators at the preset sampling frequency, and synchronously collects the ambient electric field intensity E_env; Step 3: Electric field anti-interference processing. The collected voltage data is corrected through an electric field anti-interference algorithm. The algorithm formula is: U_corrected = U_collected - K_electric_field × E_env, where U_collected is the original voltage collected by the voltage sensor, E_env is the ambient electric field intensity, and K_electric_field is the electric field correction coefficient; Step 4: Suspected zero-value determination. Double criteria are used to determine suspected zero-value insulators. If either criterion is met, it is marked as a suspected zero-value insulator and its position number is recorded. The double criteria are specifically: Criterion 1: U_corrected < U_standard × 50%, where U_standard is the standard voltage drop of insulators corresponding to the voltage level; Criterion 2: U_corrected < (Ux-1 + Ux+1) / 2 × 30%; Step 5: Verification of live resistance. The controller main board automatically switches to the resistance detection mode. The detection probe maintains a contact pressure of 1.5 N. The signal generator injects a sine detection signal with an amplitude of 5 V in the order of 1 kHz → 10 kHz → 100 kHz, and the resistance sensor synchronously collects the response current Ix at each frequency; Step 6: Multi-frequency resistance calculation. The corresponding resistance value Rf = U_injected / Ix is calculated based on the injected voltage and response current at each frequency. The original resistance value is obtained through a weighted average algorithm. The formula for the weighted average algorithm is: R_original = (0.3 × R1kHz + 0.5 × R10kHz + 0.2 × R100kHz) / 1.0, where R1kHz, R10kHz, and R100kHz are the calculated resistance values at frequencies of 1 kHz, 10 kHz, and 100 kHz respectively; Step 7: Temperature compensation correction. The ambient temperature T is collected using a temperature sensor. The controller main board automatically matches the temperature correction coefficient K_temperature according to the temperature range. The original resistance value is compensated through the formula R_corrected = R_original × K_temperature. The corresponding relationship between the temperature range and the correction coefficient K_temperature is: -40°C to -20°C range corresponds to K_temperature = 1.20; -19°C to 0°C range corresponds to K_temperature = 1.10; 1°C to 40°C range corresponds to K_temperature = 1.00; 41°C to 65°C range corresponds to K_temperature = 0.90; Step 8: Condition Classification Determination. Insulator condition is classified based on the compensated resistance value R. The condition classification criteria are as follows: for voltage levels of 500kV and above, R correction < 500MΩ indicates a zero-value insulator; for voltage levels below 500kV, R correction < 300MΩ indicates a zero-value insulator; R correction above the zero-value threshold but below 1.5 times the standard value indicates a deteriorated insulator; R correction above 1.5 times the standard value indicates a qualified insulator. Step 9: Probe self-cleaning. When testing 3 insulators or when the contact resistance is >5Ω, start the self-cleaning program and perform a contact resistance self-test after cleaning. Step 10: Loop detection and report generation. Repeat steps 2-9 until the entire string of insulators has been tested. The controller motherboard will automatically generate a test report. The test data will be encrypted, stored, and uploaded.

[0036] Taking the testing of a 500kV single-strand insulator string as an example, the specific implementation steps of the testing method of the present invention are as follows: Step 1: Parameter initialization: After the device takes off with the drone, it automatically identifies the line voltage level as 500kV, the insulator string type as single-pair, and loads the preset parameters: standard voltage drop U_standard = 30kV, sampling frequency 100Hz, zero resistance threshold 500MΩ, and completes the initialization of each module function. Step 2: Initial screening of distributed voltage: The AI ​​image recognition unit guides the probe to contact the first insulator steel cap, holds it for 0.5s, and collects Ux=28kV, Ux+1=29kV, while simultaneously collecting the ambient electric field strength E_ambient = 8kV / m; Step 3: Electric field interference suppression: Calculate U correction according to the formula = 28 - 0.015 × 8 = 27.88kV; Step 4: Suspected zero value determination: 27.88kV > 30kV × 50% = 15kV, and there is no complete adjacent voltage data, so it is determined to be a qualified insulator, and the data is recorded; Step 5: Inspect insulators 2-18 sequentially. When inspecting the 12th insulator, collect Ux=12kV, Ux-1=29kV, Ux+1=30kV, ambient value=7.5kV / m, calculate U correction=12-0.015×7.5=11.8875kV<15kV, mark it as a suspected zero-value insulator; Step 6: Switch to resistance detection mode, inject a 5V sine wave signal in the order of 1kHz→10kHz→100kHz, and collect the response currents of 10μA, 12μA, and 15μA respectively. Calculate R1kHz=5V / 10μA=500MΩ, R10kHz=5V / 12μA≈416.67MΩ, R100kHz=5V / 15μA≈333.33MΩ, and the weighted average is R_original=(0.3×500 + 0.5×416.67 + 0.2×333.33)≈425MΩ; Step 7: The temperature sensor collects the ambient temperature T=30℃, the matching temperature K=1.00, and calculates the correction R=425×1.00=425MΩ<500MΩ. It is determined to be a zero-value insulator, and the ground terminal audible and visual alarm is triggered. Step 8: After testing a total of 3 insulators, start the probe self-cleaning program, blow for 0.2 seconds, and check the contact resistance = 3Ω < 5Ω, then continue testing; Step 9: After the entire string of insulators is tested, a test report is generated, showing that a total of 18 insulators were tested, 1 zero-value insulator (the 12th insulator), and no deteriorated insulators. The data is encrypted, stored, and uploaded to the backend system.

[0037] Corresponding to the above method embodiments, this embodiment of the invention also provides a computer device, including: Memory, which is used to store computer programs; A processor, used to execute a computer program, implements the steps of the above-described method for detecting live zero-value insulators of a drone based on the above-described detection device.

[0038] In this embodiment of the invention, the processor may be a central processing unit (CPU), an application-specific integrated circuit, a digital signal processor, a field-programmable gate array, or other programmable logic devices.

[0039] The processor can call programs stored in memory. Specifically, the processor can execute the operations described in the above embodiments of the multi-system coupling assessment method for flooding in coastal cities.

[0040] The memory is used to store one or more programs, which may include program code, including computer operation instructions.

[0041] In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device or other volatile solid-state storage device.

[0042] Corresponding to the above method embodiments, this embodiment of the invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for detecting live zero-value insulators of unmanned aerial vehicles based on the above-described detection device.

[0043] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0044] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0045] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0046] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0047] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A device for detecting liveness of zero-value insulators in unmanned aerial vehicles (UAVs), characterized in that: include: A support rod having a first end and a second end disposed opposite to each other along its length; A mounting bracket is installed on the support rod. The mounting bracket is equipped with a universal quick-release interface and locking buckle adapted to the UAV, which is used to stably mount the detection device on the UAV. A rotating mechanism, which is mounted on the first end of the support rod; The execution module includes an AI image recognition unit and a detection probe. The detection probe is fixedly connected to the end of the rotating mechanism away from the support rod. The detection probe adopts a dual-electrode structure and integrates a voltage sensor and a resistance sensor, supporting two modes: live resistance detection and distributed voltage detection. The AI ​​image recognition unit is fixedly installed at the end of the rotating mechanism away from the support rod. The AI ​​image recognition unit is adjacent to the root of the detection probe and is arranged at an angle of 15° to 30° with the detection probe. The distance between the center of its lens and the insulator steel cap is 5cm to 10cm. It is used to acquire images of the insulator steel cap and output positioning signals. The controller motherboard is installed at the second end of the support rod. The controller motherboard is electrically connected to the detection probe, the rotating mechanism and the AI ​​image recognition unit through shielded cables. The controller motherboard is used to receive the positioning signal of the AI ​​image recognition unit to control the rotating mechanism to drive the detection probe to make precise contact. At the same time, it receives the voltage detection data and / or current detection data transmitted by the detection probe, processes the detection data and obtains the detection result of the insulator status.

2. The unmanned aerial vehicle (UAV) zero-value insulator live-line detection device according to claim 1, characterized in that: It also includes a data transmission module, which is mounted on the support rod and is used to transmit the detection data of the detection probe to the controller motherboard.

3. The unmanned aerial vehicle (UAV) zero-value insulator live-line detection device according to claim 1, characterized in that: The support rod is made of epoxy resin insulating material.

4. The unmanned aerial vehicle (UAV) zero-value insulator live-line detection device according to claim 1, characterized in that: The surface of the detection probe is coated with an anti-fouling and insulating coating, and its electrode end is provided with an elastic buffer structure with a buffer stroke of 0-5mm. A micro airflow pump is also provided at the root of the detection probe, which is used to output compressed air to achieve self-cleaning of the detection probe.

5. The unmanned aerial vehicle (UAV) zero-value insulator live-line detection device according to claim 1, characterized in that: The controller motherboard includes a signal generator, a data processor, and a parameter storage unit. The signal generator is used to generate multi-frequency detection signals, the data processor is used to execute the core detection algorithm and process various types of detection data, and the parameter storage unit is used to pre-store standard parameters and correction coefficients corresponding to different voltage levels and insulator types.

6. A method for detecting live zero-value insulators of unmanned aerial vehicles based on the detection device described in any one of claims 1-5, characterized in that, Includes the following steps: Step 1: Parameter initialization. After the detection device takes off and is positioned with the drone, it automatically reads the voltage level of the detection line and the type of insulator string, loads the corresponding preset parameters from the parameter storage unit, and completes the functional initialization of the voltage sensor, resistance sensor, signal generator and data transmission module. Step 2: Initial screening of distributed voltage. The AI ​​image recognition unit guides the probe to accurately contact the insulator steel cap. Each contact is held for 0.5 seconds. The voltage sensor collects the current insulator voltage value Ux and the voltage values ​​Ux-1 and Ux+1 of the two adjacent insulators at a preset sampling frequency. Simultaneously, the ambient electric field strength E is collected. Step 3: Electric field anti-interference processing. The collected voltage data is corrected through an electric field anti-interference algorithm. The algorithm formula is: U corrected = U collected - K electric field × E environment, where U collected is the original voltage collected by the voltage sensor, E environment is the environmental electric field strength, and K electric field is the electric field correction coefficient; Step 4: Suspected zero value determination. Double criteria are used to determine suspected zero value insulators. If either criterion is met, it is marked as a suspected zero value insulator and its position number is recorded; Step 5: Live resistance verification. The main board of the controller automatically switches to the resistance detection mode. The detection probe maintains a contact pressure of 1.5 N. The signal generator injects a sinusoidal detection signal with an amplitude of 5 V in sequence according to the order of 1 kHz → 10 kHz → 100 kHz. The resistance sensor synchronously collects the response current Ix at each frequency; Step 6: Multi-frequency resistance calculation. The corresponding resistance value Rf = U injected / Ix is calculated based on the injected voltage and response current at each frequency. The original resistance value is obtained through a weighted average algorithm; Step 7: Temperature compensation correction. The environmental temperature T is collected using a temperature sensor. The main board of the controller automatically matches the temperature correction coefficient K temperature according to the temperature range. The original resistance value is compensated through the formula R corrected = R original × K temperature; Step 8: State grading determination. The insulator state is graded according to the compensated resistance value R corrected; Step 9: Probe self-cleaning. When every 3 insulators are detected or the contact resistance > 5 Ω, the self-cleaning program is started. After cleaning, the contact resistance is self-tested; Step 10: Loop detection and report generation. Repeat steps 2 - 9 until the detection of the entire string of insulators is completed. The main board of the controller automatically generates a detection report. The detection data is stored and uploaded after encryption processing.

7. The method for detecting liveness of zero-value insulators in unmanned aerial vehicles according to claim 6, characterized in that, The specific double criteria described in step 4 are: Criterion 1: U corrected < U standard × 50%, where U standard is the standard voltage drop of insulators corresponding to the voltage level; Criterion 2: U corrected < (Ux - 1 + Ux + 1) / 2 × 30%.

8. The method for detecting liveness of zero-value insulators in unmanned aerial vehicles according to claim 6, characterized in that, The formula for the weighted average algorithm described in step 6 is: R original = (0.3 × R1kHz + 0.5 × R10kHz + 0.2 × R100kHz) / 1.0, where R1kHz, R10kHz, and R100kHz are the calculated resistance values at 1 kHz, 10 kHz, and 100 kHz frequencies respectively.

9. The method for detecting liveness of zero-value insulators in unmanned aerial vehicles according to claim 6, characterized in that, The corresponding relationship between the temperature range and the correction coefficient K temperature described in step 7 is: The range of -40°C to -20°C corresponds to K temperature = 1.20; the range of -19°C to 0°C corresponds to K temperature = 1.10; the range of 10. The method for detecting liveness of zero-value insulators in unmanned aerial vehicles according to claim 6, characterized in that, ​ ​

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