Adaptive wire diameter planning method for high-voltage bare wire solid insulation coating robot

Abstract

The application discloses a kind of high-voltage bare conductor solid insulation covering robot self-adapting line diameter planning method, it is related to high-voltage bare conductor insulation covering robot technical field, including environment investigation and wire pretreatment, clean up obstacle on wire;Through double sensing measurement unit along the wire circumference multi-point sampling, actual line diameter is obtained after rejecting outlier;Matching corresponding width solid insulation material and scientific preheating;According to line diameter and environmental temperature, self-adapting adjustment covering process parameters;Robot advances along preplanned path and hot melt covering, real-time monitoring covering state and environmental change, dynamically correct parameter;After completing covering, verify quality by vision, thickness and withstand voltage test, store complete operation data and optimize mapping table.The application solves the problems of inaccurate traditional line diameter measurement, poor process parameter adaptation, etc., through accurate measurement, adaptive parameter adjustment and full-dimensional quality verification, improves the covering accuracy and the qualified rate, adapts to complex working environment.

Description

Technical Field

[0001] This invention relates to the field of high-voltage bare conductor insulation coating robot technology, and more particularly to an adaptive wire diameter planning method for high-voltage bare conductor solid insulation coating robot. Background Technology

[0002] High-voltage bare conductors in overhead power distribution lines are widely distributed in various scenarios such as cities, villages, forest areas, and fishponds. Their insulation upgrade is a key link in ensuring the safe and stable operation of the power grid and reducing the fault tripping rate. Traditional methods of bare conductor insulation treatment mainly rely on manual live-line work or power outages to replace insulated conductors. Manual live-line work involves direct exposure to the high-voltage environment, posing extremely high safety risks to workers, and is greatly limited by terrain, climate, and other environmental factors. It is also extremely difficult to carry out such work in complex scenarios such as fishponds, forest areas, and building complexes. While power outages can ensure insulation effectiveness, they can cause large-scale power outages, affecting industrial production and residents' lives, and incurring high socio-economic costs.

[0003] With the application of robotics in power operation and maintenance, insulation coating robots are gradually replacing manual labor in the insulation modification of bare conductors. However, existing technologies still have many shortcomings. First, the accuracy of wire diameter measurement is insufficient. Most robots use a single sensor for single-point measurement, failing to fully consider the irregularity of the conductor cross-section, resulting in large measurement errors. This leads to inappropriate widths of the matching solid insulation material—either too wide, causing waste, or too narrow, failing to completely cover the conductor. Second, the process parameters lack adaptive adjustment capabilities. Existing methods mostly use fixed parameters such as forming temperature and travel speed, without adjusting based on dynamic factors such as actual wire diameter, ambient temperature, and conductor climbing angle. This easily leads to uneven insulation layer thickness, loose adhesion, air bubbles, and wrinkles in different wire diameters or complex environments, affecting insulation quality. Furthermore… The existing insulation coating robots suffer from several problems. First, the preheating process lacks scientific planning and is highly susceptible to environmental temperature fluctuations. Insufficient heat melting at low temperatures and overheating at high temperatures lead to material adhesion, both reducing the coating effect. Second, their path planning and anomaly handling capabilities are weak. They cannot avoid obstacles such as poles and fittings in real time, and their response to abnormal situations like foreign objects or material breakage is delayed, easily causing work interruptions or coating defects. Third, the quality verification system is incomplete, relying mainly on visual inspection of surface condition, lacking thickness testing and withstand voltage testing. This fails to ensure insulation performance meets standards, and incomplete data storage hinders quality traceability and subsequent process optimization. These issues mean that the existing insulation coating robots cannot meet the high-quality operation and maintenance requirements of the power industry in terms of operational quality stability, environmental adaptability, and efficiency, thus restricting the large-scale implementation of bare conductor insulation retrofitting. Summary of the Invention

[0004] The present invention proposes an adaptive wire diameter planning method for a robot for solid insulation coating of high-voltage bare conductors, in order to solve the problems mentioned in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an adaptive wire diameter planning method for a robot for solid insulation coating of high-voltage bare conductors, comprising the following steps: The process involves environmental inspection and conductor pretreatment of the high-voltage bare conductor work area, clearing obstacles from the conductor; multi-point adaptive measurement of the bare conductor using a wire diameter measurement module on the robot to obtain the actual wire diameter data; matching the corresponding width of solid insulation material by calling a preset wire diameter-material specification mapping table based on the wire diameter; adaptively adjusting the wrapping process parameters according to the wire diameter, ambient temperature, and work scenario; controlling the robot to move along the conductor and perform hot melt wrapping operations, monitoring the wrapping status in real time; dynamically adjusting process parameters to adapt to changes in the work environment; and verifying the insulation layer quality after wrapping, outputting a qualified insulation wrapping result.

[0006] Furthermore, the wire diameter measurement step adopts a dual-sensor symmetrical arrangement measurement method, selecting at least 3 measurement points along the circumference of the conductor, sampling each measurement point 5 times consecutively, and taking the average value after removing outliers as the actual wire diameter data.

[0007] Furthermore, the material matching step establishes a mapping table of wire diameter and material specifications. When the wire diameter is 9mm~14mm, an insulating material with a width of 30mm~40mm is matched; when the wire diameter is 14mm~18mm, an insulating material with a width of 40mm~50mm is matched; and when the wire diameter is 18mm~22mm, an insulating material with a width of 50mm~60mm is matched.

[0008] Furthermore, the coating process parameters include initial forming temperature, working forming temperature, cutting blade temperature and robot travel speed. The initial forming temperature and working forming temperature are increased by 5°C to 8°C respectively, and the cutting blade temperature is always 20°C to 30°C higher than the working forming temperature.

[0009] Furthermore, the dynamic adjustment step utilizes the gyroscope and visual monitoring module mounted on the robot to detect the climbing angle and travel posture of the guide wire in real time.

[0010] Furthermore, the quality verification step involves dual verification through visual inspection and thickness inspection. Visual inspection shows that the insulation layer surface is smooth and free of bubbles and wrinkles. Thickness inspection uses an ultrasonic sensor to randomly select 6 inspection points along the covered section. The insulation layer thickness of the 10kV voltage level conductor needs to reach 1.0±0.05mm, and the thickness of the 35kV voltage level conductor needs to reach 2.5±0.05mm.

[0011] Furthermore, the real-time monitoring step also includes foreign object detection and anomaly warning. When foreign objects that have not been cleaned are detected on the wire or when material breakage or abnormal temperature occurs during the wrapping process, the robot is immediately controlled to stop and an early warning signal is issued. After the fault is cleared, the wrapping operation continues from the fault point.

[0012] Furthermore, the material adaptation process also includes a material preheating step, with the preheating time adjusted according to the ambient temperature: 10-15 minutes for ambient temperatures of 5℃~15℃, 5-8 minutes for ambient temperatures of 15℃~30℃, and 3-5 minutes for ambient temperatures of 30℃~40℃.

[0013] Furthermore, the robot's movement steps adopt a combination of path pre-planning and real-time correction. The initial movement path is planned based on the traverse data, and obstacles are identified through the vision module during the operation, and the movement trajectory is automatically adjusted.

[0014] Furthermore, the method also includes a data storage and traceability step, which records wire diameter measurement data, material specifications, process parameters, operation time, and quality inspection results to form a complete operation data archive, supporting subsequent queries and quality traceability, while updating the valid data to the wire diameter and parameter mapping table.

[0015] Compared with existing technologies, the beneficial effects of this invention are: The adaptive wire diameter planning method for solid insulation coating robots for high-voltage bare conductors proposed in this invention addresses the pain points of existing technologies and achieves precision, intelligence, and high quality in bare conductor insulation coating through multi-dimensional technological innovation, resulting in significant overall technical effects.

[0016] This method employs a dual-sensor measurement unit consisting of a laser displacement sensor and a contact sensor, combined with circumferential multi-point sampling and a 3σ outlier elimination algorithm, significantly improving the accuracy of wire diameter measurement. The measurement error is controlled within ±0.03mm, providing reliable data support for subsequent material matching and process parameter adjustments, thus avoiding material waste or insufficient coverage caused by inaccurate wire diameter measurement. By establishing a graded matching wire diameter-material specification mapping table, solid insulation materials of corresponding widths are accurately matched according to different wire diameters. Simultaneously, the preheating time is adaptively calculated based on ambient temperature to ensure that the material completely covers the conductor after heat melting with a reasonable overlap, guaranteeing insulation integrity while avoiding resource waste.

[0017] The innovative adaptive adjustment model for the coating process parameters incorporates wire diameter and ambient temperature into the parameter calculations. It accurately derives the initial forming temperature, working forming temperature, and travel speed through formulas. Simultaneously, it dynamically adjusts the process parameters and coating pressure based on the conductor's climbing angle. This ensures uniform insulation layer thickness and tight adhesion even in complex terrain and environments, effectively solving the coating defects caused by traditional fixed parameters. The path planning combines UAV aerial pre-planning with real-time visual correction, accurately identifying and avoiding obstacles such as poles and fittings, ensuring continuous and uninterrupted operation. The anomaly monitoring module responds quickly to foreign objects, material breakage, and abnormal temperatures, providing timely shutdown warnings and reducing the risk of operational failure.

[0018] The quality verification process integrates visual inspection, thickness measurement, and withstand voltage testing to comprehensively assess the surface condition, thickness accuracy, and electrical performance of the insulation layer, ensuring that the insulation effect meets the requirements of different voltage levels such as 10kV and 35kV. The complete storage and traceability of work data not only provides a basis for quality control but also continuously optimizes the wire diameter-parameter mapping table through a weighted average method, improving the adaptive planning accuracy of subsequent operations. Overall, this method achieves uninterrupted, safe, efficient, and high-quality insulation coating of high-voltage bare conductors, significantly reducing safety risks for operators and maintenance costs. It is adaptable to various complex working environments and provides reliable technical support for the insulation transformation of bare conductors in distribution networks, demonstrating significant practical value and promotional significance. Attached Figure Description

[0019] Figure 1 This is a schematic block diagram of the adaptive wire diameter planning method for the high-voltage bare conductor solid insulation coating robot proposed in this invention; Figure 2 A comparison chart of wire diameter measurement accuracy; Figure 3 Comparison chart of the effects of adapting coating process parameters for different wire diameters; Figure 4 A graph showing the relationship between ambient temperature and material preheating time; Figure 5 This is a comparison chart of the coating quality pass rates; Figure 6 This is a comparison chart of abnormal response times. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0022] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The invention will now be described in further detail with reference to the accompanying drawings.

[0023] Reference Figures 1 to 6 An adaptive wire diameter planning method for a robot that performs solid insulation coating on high-voltage bare conductors includes the following steps: An environmental inspection was conducted on the high-voltage bare conductor work area, checking wind speed, humidity, and temperature to ensure wind speed ≤5, relative humidity ≤80%, and temperature 5℃~40℃. Foreign objects and protruding obstacles on the conductor were removed to ensure the surface was free of impurities that could affect the coating. Using a dual-sensor measurement unit consisting of a laser displacement sensor and a contact sensor mounted on a robot, five measurement points were evenly selected along the circumference of the conductor. Each measurement point was sampled eight times consecutively. Outliers were removed using the 3σ criterion, and the result was calculated using a formula... Calculate the actual wire diameter data, where This refers to the actual diameter of the conductor. For the effective number of samples, For the first The wire diameter value of the first effective sample is used; based on the wire diameter data, a preset wire diameter-material specification mapping table is called to match the corresponding width of solid insulation material; an adaptive adjustment model for the coating process parameters is introduced to calculate the initial forming temperature, working forming temperature and robot travel speed according to the wire diameter and ambient temperature; the robot is controlled to move along the pre-planned path of the conductor and perform hot melt coating operation, and the insulation layer coating adhesion and surface condition are monitored in real time through a vision monitoring module and pressure sensor; the process parameters are dynamically corrected according to environmental changes and coating status; after the coating is completed, the insulation layer quality is verified through visual inspection, thickness inspection and withstand voltage test, and qualified insulation coating results are output and complete operation data is stored.

[0024] In this invention, the laser displacement sensor in the dual-sensor measurement unit has a measurement accuracy of ±0.03mm, the contact sensor has a measurement range of 9mm~22mm, the sampling frequency is 10Hz, and the five measurement points are located at 0°, 72°, 144°, 216°, and 288° of the conductor circumference, respectively, to ensure full coverage of the conductor cross-section. The outlier judgment standard in the 3σ criterion is the sampling data that exceeds the mean ±3 times the standard deviation, and the effective sampling number n≥6, to ensure the accuracy and reliability of the wire diameter measurement.

[0025] In this invention, the wire diameter-material specification mapping table adopts a graded matching rule: when the wire diameter is 9mm~12mm, a solid insulation material with a width of 35mm is matched; when the wire diameter is 12mm~16mm, a solid insulation material with a width of 45mm is matched; when the wire diameter is 16mm~19mm, a solid insulation material with a width of 52mm is matched; and when the wire diameter is 19mm~22mm, a solid insulation material with a width of 58mm is matched. The material width is 26mm~36mm larger than the corresponding wire diameter to ensure that the material completely covers the conductor after heat melting and the overlap is controlled within 3mm~5mm, avoiding waste and insufficient coverage.

[0026] In this invention, the formula for calculating the initial molding temperature in the adaptive adjustment model of the coating process parameters is as follows: ,in This is the initial molding temperature. The baseline initial temperature is 85℃. The wire diameter correction factor is 6℃ / mm. This is the actual wire diameter. The baseline diameter is 14mm. The ambient temperature correction factor is 1.2℃ / ℃. This refers to the actual ambient temperature. The baseline ambient temperature is 25℃; the working molding temperature is... = +15℃, cutting blade temperature = At +25℃, the formula for calculating the robot's travel speed is: ,in For travel speed, The baseline speed is 1.5 m / min. The speed correction factor is 0.08 m / (min・mm) to ensure that the process parameters are accurately matched with the wire diameter and ambient temperature.

[0027] In this invention, the dynamic correction step uses a three-axis gyroscope mounted on the robot to detect the climbing angle α of the conductor in real time. When α < 15°, the initial process parameters are maintained; when 15° ≤ α < 30°, the traveling speed is reduced by 20% and the covering pressure is increased by 12%; when α ≥ 30°, the traveling speed is reduced by 40% and the covering pressure is increased by 25%. At the same time, the bonding status of the insulation layer is monitored in real time through a vision module. When the bonding degree is lower than 95%, the working forming temperature is further adjusted and increased by 3°C to 5°C to ensure that the insulation layer and the conductor are tightly bonded without bubbles or slippage.

[0028] In this invention, during the quality verification steps, visual inspection uses a high-definition industrial camera to photograph the surface of the insulation layer. The surface smoothness is determined by image grayscale analysis, and the absence of bubbles, wrinkles, and cracks indicates compliance. Thickness inspection uses an ultrasonic thickness gauge to select one inspection point every 0.5m along the covered section. Three measurements are taken along the circumference of each inspection point, and the average value is calculated. The insulation layer thickness of the 10kV voltage level conductor must meet 1.0±0.05mm, and the thickness of the 35kV voltage level conductor must meet 2.5±0.05mm. The withstand voltage test uses the DC withstand voltage method. The test voltage for the 10kV conductor is 20kV, and the test voltage for the 35kV conductor is 66kV. The continuous test time is 1min, and the absence of breakdown or flashover indicates compliance.

[0029] In this invention, the foreign object detection step uses a laser rangefinder sensor with a detection range of 0.1m to 1m. When a foreign object with a diameter ≥3mm or a length ≥50mm is detected on the wire, the robot is immediately stopped and an audible and visual warning is issued through the remote control terminal, while the fault location is recorded. Material fracture detection uses a tension sensor to monitor the material conveying tension in real time. When the tension suddenly exceeds the normal range of ±50%, it is determined that the material has fractured, and the robot is stopped and prompted to replace the material. The temperature anomaly judgment standard is that the deviation between the actual temperature and the set temperature exceeds ±8℃, ensuring timely detection and handling of operational anomalies.

[0030] In this invention, the material preheating step employs a constant-temperature preheating chamber, with the preheating temperature set at 45℃±5℃, and the preheating time determined by the formula... Calculation, where Preheating time (unit: min). Ambient temperature (unit: °C), when the ambient temperature is 5 °C =7min, at 15℃ =5min, at 25℃ =3min, at 35℃ =2min, to ensure that the material reaches the best hot melt fluidity after preheating, and to avoid poor bonding of the coating layer due to the material temperature being too low.

[0031] In this invention, the path pre-planning is based on the conductor routing data obtained by drone aerial photography. The shortest travel path is planned using the A* algorithm. During the operation, the vision module uses the YOLO target detection algorithm to identify obstacles such as poles and fittings at a distance of ≥1.5m. When an obstacle is detected, the travel trajectory is automatically adjusted to maintain a horizontal safety distance of not less than 0.8m and a vertical safety distance of not less than 0.5m between the robot and the obstacle. At the same time, the wrapping path is corrected to ensure the continuity and integrity of the insulation layer and to avoid obstacles affecting the wrapping quality.

[0032] In this invention, the information recorded in the data storage and traceability step includes the operation date, operation route number, environmental parameters (wind speed, humidity, temperature), original and actual wire diameter measurement data, material specifications (width, batch), process parameters (initial forming temperature, working forming temperature, cutting blade temperature, travel speed), operation length, and various quality inspection data. The storage format is JSON, and it supports exporting and querying via a remote control terminal. Simultaneously, the effective wire diameter-process parameter matching data for each operation is updated to the wire diameter-parameter mapping table using a weighted average method. The update formula is as follows: ,in For the updated parameters, Weights are assigned to historical data. The historical average parameter As the current data weight, Continuously optimize the accuracy of adaptive planning based on the current operating parameters.

[0033] The following two examples further illustrate the specific implementation of this system: Example 1: Insulation Covering Operation for Bare Conductors in 10kV Urban Distribution Network

[0034] This embodiment is applied to the insulation upgrade of 10kV high-voltage bare conductors in urban power distribution networks. The work area is distributed on both sides of urban streets, passing through buildings and green belts. There are obstacles such as poles and hardware along the conductor. The ambient temperature is 25℃, the relative humidity is 65%, the wind speed is level 3, the actual conductor diameter is 14mm, and there is no obvious climbing angle. It is necessary to achieve uninterrupted power supply and high-precision insulation covering work, fully implement all the technical processes of this method, and ensure the safe and stable operation of urban power distribution networks.

[0035] During implementation, the first steps were environmental inspection and conductor pretreatment. Before operation, portable environmental monitoring equipment was used to test the environmental parameters of the work area, confirming a wind force of level 3, relative humidity of 65%, and temperature of 25℃, meeting the operating conditions of wind force ≤ level 5, relative humidity ≤ 80%, and temperature 5℃~40℃. Workers, wearing insulated protective gear, used insulated rods to clean plastic film, branches, and other foreign objects from the bare conductors, focusing on removing protruding impurities from the conductor surface to ensure a smooth and unobstructed surface, avoiding any impact on robot movement and the covering effect. Simultaneously, the work route was surveyed to confirm that the conductors had no obvious bends, did not cross dangerous areas, and that the distance between the work starting point and the tower was 2.5m, meeting safety requirements.

[0036] The wire diameter measurement step utilizes a dual-sensor measurement unit mounted on the robot. A laser displacement sensor and a contact sensor are symmetrically installed at the front end of the robot's covering mechanism, covering a measurement range of 9mm to 22mm. The laser displacement sensor achieves a measurement accuracy of ±0.03mm and a sampling frequency of 10Hz. After the robot is deployed, five measurement points (0°, 72°, 144°, 216°, and 288°) are evenly selected along the circumference of the conductor. Each measurement point is sampled eight times consecutively. After data collection, outliers are removed using the 3σ criterion. One set of data exceeding ±3 times the standard deviation of the mean is discarded, retaining seven sets of valid data. The actual wire diameter is calculated to be 14mm, with the measurement error controlled within ±0.03mm, ensuring accurate and reliable wire diameter data.

[0037] Based on the measured wire diameter of 14mm, a preset wire diameter-material specification mapping table was used to match a 45mm wide solid insulation material. The material width is 31mm larger than the wire diameter to ensure complete coverage of the conductor after heat fusion with an overlap controlled within 4mm, avoiding material waste and ensuring insulation integrity. A material preheating step was then performed using the robot's built-in constant-temperature preheating chamber, with a preheating temperature set at 45℃ and a preheating time of 3 minutes calculated based on an ambient temperature of 25℃, ensuring optimal heat fusion fluidity and preventing insufficient heat fusion leading to a loose coating. During material installation, the solid insulation material was loaded into the tray, and the width of the "U-shaped groove" was adjusted to fit the 45mm material, ensuring both sides of the material were fully inserted into the groove, with the material head extending beyond the initial die head. A special double-sided adhesive mark was used to align the line with the outer edge of the initial die head.

[0038] The coating process parameters were calculated using an adaptive adjustment model. The baseline initial temperature was 85℃, the wire diameter correction factor was 6℃ / mm, the ambient temperature correction factor was 1.2℃ / ℃, the baseline wire diameter was 14mm, and the baseline ambient temperature was 25℃. The final determined initial forming temperature was 85℃, the working forming temperature was 100℃, and the cutting blade temperature was 125℃. The robot's travel speed was set to a baseline of 1.5m / min with a speed correction factor of 0.08m / (min・mm). Since the actual wire diameter matched the baseline wire diameter, the travel speed was set to 1.5m / min. Simultaneously, the adhesive application system was checked. Sealant was added to the tank, and the air pump, air tank, and adhesive sealing foam were connected to ensure proper sealing at both ends of the wire.

[0039] The path pre-planning step utilizes aerial data of the conductor's orientation obtained from drone photography. The A* algorithm is used to plan the shortest path, defining the robot's trajectory from the start to the end of the operation and avoiding obstacles such as poles and fittings along the route. During operation, the robot's vision module employs the YOLO object detection algorithm to identify obstacles in real time at a distance of 1.8m. When a pole or fitting is detected at a distance of 0.8m, the robot automatically adjusts its trajectory, maintaining a horizontal safety distance of 0.8m and a vertical safety distance of 0.5m to ensure smooth obstacle avoidance without affecting the continuity of the coverage.

[0040] The robot was activated and moved along a pre-planned path to perform hot-melt coating. During the movement, a visual monitoring module captured real-time images of the insulation layer coating process, while a pressure sensor monitored the coating pressure to ensure a tight bond between the insulation layer and the conductor. Since the conductor in the work area had no significant incline angle, the gyroscope detected an incline angle α < 15°, maintaining the initial process parameters unchanged. During real-time monitoring, a laser rangefinder continuously detected foreign objects on the conductor, and a tension sensor monitored the material conveying tension. No foreign objects, material breakage, or abnormal temperatures were detected, and the operation proceeded smoothly.

[0041] After the coating is completed, a quality verification process is performed. Visual inspection uses a high-definition industrial camera to photograph the insulation layer surface. Image grayscale analysis determines that the surface is smooth, free of bubbles, wrinkles, and cracks. Thickness measurement uses an ultrasonic thickness gauge, selecting one measurement point every 0.5m along the coated section. Three measurements are taken along the circumference at each measurement point, and the average value is calculated. The measured insulation layer thickness is consistently within the range of 1.0±0.05mm. The withstand voltage test uses the DC withstand voltage method, applying a test voltage of 20kV for 1 minute. No breakdown or flashover occurs, indicating successful quality verification. Finally, data storage is performed, recording the operation date, line number, environmental parameters, wire diameter measurement data, material specifications, process parameters, operation length, and quality inspection results. The data is stored in JSON format, supporting subsequent queries and traceability. The valid data is also updated in the wire diameter-parameter mapping table.

[0042] Table 1. Performance Comparison of 10kV Urban Distribution Network Operation Manual Method and Traditional Method Core performance indicators Method of the present invention Traditional methods Wire diameter measurement error ≤±0.03mm ±0.2mm Material utilization rate 95% 80% Insulation layer pass rate 99.5% 88% Job interruption rate 0.5% 8% Quality traceability capability Complete traceability No traceability Table 1 shows the data from the actual measurement results of the wrapping operation of 10 sections of 10kV bare conductors in this embodiment, covering different operation sections of the urban power distribution network. Traditional methods use a single sensor to measure wire diameter at a single point, resulting in large errors leading to improper material matching and a utilization rate of only 80%. Furthermore, fixed process parameters result in an insulation layer qualification rate as low as 88%. The operation is easily interrupted due to foreign objects, obstacles, etc., with an interruption rate of up to 8%, and there is no complete data storage, making quality traceability impossible. This invention, through dual-sensor multi-point measurement, adaptive parameter adjustment, intelligent path planning, and complete quality verification, significantly improves the accuracy of wire diameter measurement, material utilization rate, and insulation layer qualification rate, reduces the operation interruption rate, and simultaneously achieves full quality traceability, comprehensively meeting the high-quality operation and maintenance needs of urban power distribution networks. Example 2: Insulation Covering Operation for Bare Conductors in 35kV Forest Distribution Network

[0043] This embodiment is applied to the insulation upgrade of 35kV high-voltage bare conductors in forest areas. The work area is located in a mountainous forest area, where the conductors cross forest land and there are obstacles such as trees and towers along the route. The ambient temperature is 15℃, the relative humidity is 70%, the wind speed is level 4, and the slope angle of some sections of the conductors reaches 30°. The actual measured conductor diameter is 20mm. It is necessary to achieve efficient and safe insulation covering work in complex terrain and environment, fully implement all the technical processes of this method, and ensure the insulation performance and operational stability of the forest area power distribution network.

[0044] During the implementation process, the first step was to conduct an environmental survey and pre-treatment of the conductors. Before the operation, environmental monitoring equipment confirmed that the wind force was level 4, the relative humidity was 70%, and the temperature was 15℃, meeting the requirements for the working environment. Workers wore insulated protective gear and used insulated poles to remove branches, vines, and other foreign objects from the conductors, focusing on removing moss and impurities from the conductor surface to ensure the conductors were free of obstructions. The work route was surveyed to confirm that the maximum incline angle of the conductors was 30°, the conductor diameter was uniform without significant abrupt changes, the distance between the work starting point and the tower was 2.2m, and flammable vegetation around the work area was cleared to avoid safety hazards caused by the thermal melting operation.

[0045] The wire diameter measurement employs a dual-sensor unit, with a laser displacement sensor and a contact sensor working in tandem. Sampling is performed at five measurement points along the conductor's circumference: 0°, 72°, 144°, 216°, and 288°. Each measurement point is sampled eight times consecutively. Two sets of abnormal data are eliminated using the 3σ criterion, retaining six sets of valid data. The calculated actual wire diameter is 20mm, with a measurement error of ±0.02mm, meeting high-precision measurement requirements. Based on the wire diameter-material specification mapping table, a 20mm wire diameter is matched with a 58mm wide solid insulation material. The material width is 38mm larger than the wire diameter, with an overlap controlled at 5mm to ensure insulation integrity.

[0046] Material preheating utilizes a constant-temperature preheating chamber, set at 45℃. Based on an ambient temperature of 15℃, the preheating time is calculated to be 5 minutes, ensuring the material is fully preheated in a low-temperature environment to achieve optimal heat-melting. During material installation, adjust the feeding "U-shaped groove" to fit the 58mm material, load the material into the tray and secure it, ensuring smooth and unobstructed material transport. Apply the specially formulated double-sided adhesive in the center, aligning the short end with the material head, with the material head extending beyond the die head to the marked line.

[0047] The coating process parameters were calculated using an adaptive adjustment model. The baseline initial temperature was 85℃, the wire diameter correction factor was 6℃ / mm, the ambient temperature correction factor was 1.2℃ / ℃, the baseline wire diameter was 14mm, the baseline ambient temperature was 25℃, the actual wire diameter was 20mm, and the ambient temperature was 15℃. The final determined initial forming temperature was 97℃, the working forming temperature was 112℃, and the cutting blade temperature was 137℃. The robot's travel speed baseline was 1.5m / min, with a speed correction factor of 0.08m / (min・mm), resulting in a calculated travel speed of 1.06m / min. After the adhesive coating system was assembled, the air passages were checked for unobstructed flow to ensure effective adhesive sealing at both ends of the wire.

[0048] Path pre-planning is based on aerial data of forest guide lines taken by drones, using the A* algorithm to plan a path that avoids trees and steep slopes. During operation, the vision module identifies obstacles such as trees and poles in real time at a distance of 1.5m. When a tree obstacle is detected, the robot automatically adjusts its trajectory to maintain a safe distance of more than 0.8m. When the robot reaches an uphill section, the three-axis gyroscope detects an uphill angle α=30°, and the robot reduces its speed by 40% to 0.64m / min according to preset rules, while increasing the covering pressure by 25%. At the same time, the vision module monitors the adhesion of the insulation layer to ensure that the adhesion is maintained at more than 95%, without slippage or air bubbles.

[0049] During real-time monitoring, the laser rangefinder detected a 2mm diameter foreign object on the conductor, which did not reach the warning threshold, and the robot continued to move normally. The tension sensor monitored the material conveying tension in real time, maintaining stability without sudden changes. The temperature sensor monitored the forming temperature, and the deviation from the set temperature was within ±3℃, with no abnormalities. After the operation was completed, quality verification was performed. Visual inspection showed that the insulation layer surface was smooth, without bubbles or wrinkles. Thickness was measured using an ultrasonic thickness gauge, and the measured thickness was within the range of 2.5±0.05mm. The withstand voltage test applied a 66kV DC voltage for 1 minute without breakdown, and the quality verification was qualified. The data storage step recorded complete operation information, including environmental parameters, wire diameter data, process parameters, and quality inspection results, in JSON format. This data was also updated to the wire diameter-parameter mapping table to optimize the accuracy of subsequent operations.

[0050] Table 2. Performance Comparison of Traditional and Manual Methods for 35kV Forest Distribution Network Operations Core performance indicators Method of the present invention Traditional methods Complex environment adaptability 98% 75% Slope climbing operation qualification rate 99% 80% Insulation layer thickness uniformity ±0.05mm ±0.1mm Abnormal response time ≤1s ≥5s Work efficiency 1.06 m / min 0.8 m / min Table 2 shows the data from actual measurements of insulation wrapping operations on eight sections of 35kV bare conductors in forest areas, covering complex scenarios such as uphill sections and densely wooded areas. Traditional methods have poor adaptability in complex forest environments, easily leading to insulation layer detachment and uneven thickness during uphill operations, with a pass rate of only 80%, and delayed anomaly response, resulting in low operational efficiency. This invention significantly improves adaptability to complex environments and the pass rate through environmental adaptive parameter adjustment, uphill section process optimization, rapid anomaly response, and intelligent path planning. The insulation layer thickness uniformity is significantly better than traditional methods, and the operational efficiency is improved by 32.5%. This effectively solves the technical challenges of insulation wrapping of bare conductors in forest areas and provides reliable support for the insulation transformation of power distribution networks in complex scenarios.

[0051] Reference Figure 2 This figure visually demonstrates the high-precision advantage of this method for wire diameter measurement. Traditional single-sensor, single-point measurement does not consider the irregularity of the conductor cross-section, resulting in measurement errors generally exceeding 0.12mm. This leads to material matching deviations; excessive width results in waste, while insufficient coverage leads to inadequate insulation. This method employs dual-sensor units with 5-point circumferential sampling, combined with the 3σ criterion to eliminate outliers, controlling the error within ±0.03mm. This provides a precise data foundation for material specification matching and process parameter adjustment, ensuring the adaptability of insulation coverage from the source, avoiding insulation quality problems caused by measurement errors, and adapting to the measurement needs of bare conductors of different diameters.

[0052] Reference Figure 3 This diagram highlights the core value of the adaptive adjustment model for process parameters. Traditional fixed process parameters, without dynamic adjustment based on wire diameter, result in insulation thickness deviations of 0.08-0.10 mm for different wire diameters, easily leading to uneven thickness and loose bonding. This method accurately calculates the forming temperature and travel speed using a wire diameter-temperature correction formula, matching the process requirements of different wire diameters. Thickness deviations are controlled within ±0.03 mm, ensuring that the insulation thickness of 10kV / 35kV voltage level conductors meets standards. This effectively solves defects such as bubbles and wrinkles caused by poor parameter adaptation, improving the consistency and reliability of insulation coating.

[0053] Reference Figure 4This diagram clearly illustrates the scientific planning logic of material preheating time. Traditional material preheating uses a fixed time, which leads to insufficient heat melting at low temperatures, resulting in a loose coating layer, and overheating at high temperatures, causing material adhesion. This method uses a preheating time calculation formula to dynamically adjust the preheating time according to the ambient temperature. At 5℃, 7 minutes of preheating ensures material fluidity, while at 40℃, only 1.5 minutes is needed to avoid overheating, keeping the material in an optimal heat-melting state. This ensures a tight bond between the insulation layer and the conductor, significantly reducing the coating defect rate caused by improper material preheating and adapting to operational needs in different climatic environments.

[0054] Reference Figure 5 This figure visually demonstrates the improvement in insulation quality achieved by this method. Traditional methods, due to issues with measurement, parameters, and preheating, achieve a pass rate of only 82%-85%, with insulation layers prone to problems such as insufficient thickness, surface wrinkles, and breakdown during withstand voltage tests. This method, through precise wire diameter measurement, adaptive process parameters, scientific preheating planning, and comprehensive quality verification, achieves a wire diameter pass rate of 98%-99%, improving the overall pass rate by more than 15%. Comprehensive quality verification covers visual, thickness, and withstand voltage tests, fully ensuring the surface condition, thickness accuracy, and electrical performance of the insulation layer, meeting the stringent standards for high-voltage bare conductor insulation retrofitting.

[0055] Reference Figure 6 This diagram highlights the superior efficiency of this method in handling anomalies. Traditional methods suffer from delayed anomaly detection, with response times exceeding 2.5 seconds, easily leading to work interruptions, expansion of coating defects, and even equipment damage. This method utilizes multiple modules, including laser ranging, tension sensing, and visual inspection, for real-time monitoring. Anomaly response time is controlled within 0.2-0.5 seconds, allowing for immediate shutdown and early warning, timely removal of faults such as foreign objects and material breakage, and resumption of work from the point of interruption after fault resolution, avoiding rework of the entire coating section. This rapid anomaly response significantly reduces the risk of work failure, improves the continuity and stability of robot operations, and is suitable for complex working environments with high-voltage lines.

[0056] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An adaptive wire diameter planning method for a robot that performs solid insulation coating on high-voltage bare conductors, characterized in that, Includes the following steps: Conduct environmental inspections and pre-treatment of the high-voltage bare conductor work area, and clear obstacles from the conductors; The robot uses a wire diameter measurement module to perform multi-point adaptive measurements on bare wires to obtain the actual wire diameter data. Based on the wire diameter data, a preset wire diameter-material specification mapping table is called to match the corresponding width of solid insulation material; The coating process parameters are adaptively adjusted according to the wire diameter, ambient temperature, and operating environment. The robot is controlled to move along the guide wire and perform hot melt coating operations, and the coating status is monitored in real time; process parameters are dynamically adjusted to adapt to changes in the working environment. After the wrapping is completed, the insulation layer quality is verified, and a qualified insulation wrapping result is output.

2. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The wire diameter measurement step adopts a dual-sensor symmetrical arrangement measurement method, selecting at least 3 measurement points along the circumference of the conductor, sampling each measurement point 5 times consecutively, and taking the average value after removing outliers as the actual wire diameter data.

3. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The material matching step establishes a mapping table of wire diameter and material specifications. When the wire diameter is 9mm~14mm, it is matched with an insulating material with a width of 30mm~40mm. When the wire diameter is 14mm~18mm, it is matched with an insulating material with a width of 40mm~50mm. When the wire diameter is 18mm~22mm, it is matched with an insulating material with a width of 50mm~60mm.

4. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The coating process parameters include initial forming temperature, working forming temperature, cutting blade temperature and robot travel speed. The initial forming temperature and working forming temperature are increased by 5℃~8℃ respectively, and the cutting blade temperature is always 20℃~30℃ higher than the working forming temperature.

5. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The dynamic adjustment step uses the gyroscope and visual monitoring module on the robot to detect the climbing angle and traveling posture of the guide wire in real time.

6. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The quality verification step involves dual verification through visual inspection and thickness inspection. Visual inspection shows that the insulation layer surface is smooth and free of bubbles and wrinkles. Thickness inspection uses an ultrasonic sensor to randomly select 6 inspection points along the covered section. The insulation layer thickness of the 10kV voltage level conductor needs to reach 1.0±0.05mm, and the thickness of the 35kV voltage level conductor needs to reach 2.5±0.05mm.

7. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The real-time monitoring steps also include foreign object detection and anomaly warning. When foreign objects that have not been cleaned are detected on the wire, or when material breakage or abnormal temperature occurs during the wrapping process, the robot is immediately stopped and an early warning signal is issued. After the fault is cleared, the wrapping operation continues from the fault point.

8. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, After the material is adapted, a material preheating step is also included. The preheating time is adjusted according to the ambient temperature: 10-15 minutes when the ambient temperature is 5℃~15℃, 5-8 minutes when the ambient temperature is 15℃~30℃, and 3-5 minutes when the ambient temperature is 30℃~40℃.

9. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The robot's movement steps adopt a combination of path pre-planning and real-time correction. The initial movement path is planned based on the traverse data, and obstacles are identified through the vision module during the operation to automatically adjust the movement trajectory.

10. The adaptive wire diameter planning method for a high-voltage bare conductor solid insulation coating robot according to claim 1, characterized in that, The method also includes a data storage and traceability step, which records wire diameter measurement data, material specifications, process parameters, operation time, and quality inspection results to form a complete operation data archive, supporting subsequent queries and quality traceability, while updating the valid data to the wire diameter and parameter mapping table.

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