Plasma cleaning method and system for surface defects of high-voltage cable

Abstract

The invention discloses a high-voltage cable surface defect plasma cleaning method and system, and relates to the technical field of plasma cleaning, and the method comprises the steps: recognizing the surface defect type of a to-be-cleaned high-voltage cable; after the high-voltage cable to be cleaned is fixed in the cleaning work space, a first simulation cleaning control combination and a second simulation cleaning control combination are configured; regulating and controlling by using the regional temperature field of the cleaning working space, and dynamically regulating the contact angle resolution; and meanwhile, the cleaning effect is fed back in real time in combination with a plasma density sensor, and when it is detected that local cleaning is not thorough, a dynamic complementary scanning protocol is triggered. The technical problem that in the prior art, the cleaning effect is poor due to the fact that the cleaning precision of the surface defects of the high-voltage cable is insufficient and local cleaning is not thorough is solved, and the technical effects that precise cleaning of the surface defects of the high-voltage cable and dynamic repair sweeping of the local incomplete area are achieved, and the cleaning quality is improved are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of plasma cleaning, and particularly to a plasma cleaning method and system for surface defects of high-voltage cables. Background Art

[0002] During the production and manufacturing process of high-voltage cables, their surfaces often have defects due to various factors, such as oxide layers, oil stains, cracks, etc. These defects will affect the performance and service life of the cables, so they need to be cleaned. Existing plasma cleaning methods have problems of insufficient cleaning accuracy when dealing with surface defects of high-voltage cables. It is difficult to perform precise cleaning according to the specific characteristics of the defects (such as type, location, size), and there is a lack of real-time feedback and dynamic adjustment mechanisms for the cleaning effect, which easily leads to incomplete local cleaning, resulting in unstable cleaning effects and unable to meet the high-quality cleaning requirements of high-voltage cables.

[0003] The existing technology has technical problems of insufficient cleaning accuracy for surface defects of high-voltage cables and poor cleaning effects caused by incomplete local cleaning. Summary of the Invention

[0004] This application provides a plasma cleaning method and system for surface defects of high-voltage cables, which are used to solve the technical problems of insufficient cleaning accuracy for surface defects of high-voltage cables and poor cleaning effects caused by incomplete local cleaning in the existing technology.

[0005] In view of the above problems, this application provides a plasma cleaning method and system for surface defects of high-voltage cables.

[0006] In the first aspect of this application, a plasma cleaning method for surface defects of high-voltage cables is provided. The method includes: Identifying the types of surface defects of the high-voltage cable to be cleaned, and associating and storing defect feature information including surface defect types, surface defect positions, and surface defect sizes; after the high-voltage cable to be cleaned is fixed in the cleaning working space, configuring a first simulated cleaning control combination and a second simulated cleaning control combination according to the surface defect types, surface defect positions, and surface defect sizes in the defect feature information; after orthogonal verification of the first simulated cleaning control combination and the second simulated cleaning control combination, regulating the temperature field of the sub-regions of the cleaning working space, and dynamically adjusting the contact angle resolution using an integrated cable surface energy tester in the cleaning working space; at the same time, combining a plasma density sensor to real-time feedback the cleaning effect, and triggering a dynamic supplementary scanning protocol when it is detected that the local cleaning is incomplete.

[0007] In a possible implementation manner, the movement path of the plasma nozzle is simulated based on the surface defect position and surface defect size in the defect feature information to obtain a first simulated cleaning control combination; the cleaning parameters of the plasma generator are simulated based on the surface defect type and surface defect size in the defect feature information to obtain a second simulated cleaning control combination, where the cleaning parameters include the type of plasma gas source, working air pressure, and discharge power.

[0008] In a possible implementation manner, the contour is divided into multiple micro regions through the surface defect position and surface defect size in the defect feature information; the multiple micro regions are traversed, the movement trajectories of the nozzle in each micro region are fitted by spline curves, and the safety margin of the nozzle movement path is set; based on the safety margin of the nozzle movement path, with the goal of minimizing the nozzle idle travel time, the movement path of the plasma nozzle is globally optimized to determine the first simulated cleaning control combination.

[0009] In a possible implementation manner, a mapping matching table between the surface defect type and the type of plasma gas source is established; with the goal of minimizing cleaning energy consumption as the objective function, the cleaning parameters are optimized according to the mapping matching table and the surface defect size to determine the second simulated cleaning control combination.

[0010] In a possible implementation manner, temperature data is collected in real time within the cleaning work space; the regional energy requirements of the cleaning work space are introduced, and partition heating is used for dynamic temperature field regulation, and a temperature - plasma activity coupling factor is set; based on the temperature - plasma activity coupling factor, the discharge power in the cleaning parameters is feedback - adjusted.

[0011] In a possible implementation manner, according to the cleaning accuracy requirement, the contact angle resolution of the cable surface energy tester is dynamically adjusted, and the cable surface cleanliness is assisted in evaluation based on the contact angle measurement data; when the contact angle change rate is less than the set change rate threshold, a surface cleanliness judgment request is issued; based on the surface cleanliness judgment request, a cleaning stage switching decision is made.

[0012] In a possible implementation manner, the plasma density is measured; an empirical index of the plasma density and the cleaning effect is set, and when the deviation degree of the plasma density from the set value exceeds the deviation degree threshold, the cleaning parameters of the plasma generator are automatically adjusted.

[0013] In a possible implementation manner, the surface of the high - voltage cable after cleaning is detected in real time to identify the areas that are not thoroughly cleaned; according to the areas that are not thoroughly cleaned, a supplementary scanning path and supplementary scanning cleaning parameters are generated; the supplementary scanning path and supplementary scanning cleaning parameters are uploaded to the control center, and the dynamic supplementary scanning protocol built in the control center is used for coordinated configuration of the supplementary scanning operation.

[0014] In a possible implementation manner, through the spatio-temporal distribution analysis of the plasma density, a predicted cleaning blind area during the cleaning process is obtained; and the plasma nozzle is co-controlled with the predicted cleaning blind area.

[0015] In a second aspect of the present application, a plasma cleaning system for surface defects of a high-voltage cable is provided. The system includes: A surface defect identification module, configured to identify the type of surface defects of the high-voltage cable to be cleaned, and associate and store defect feature information including the type of surface defects, the position of surface defects, and the size of surface defects; a cleaning control combination configuration module, configured to, after the high-voltage cable to be cleaned is fixed in the cleaning work space, configure a first simulated cleaning control combination and a second simulated cleaning control combination according to the type of surface defects, the position of surface defects, and the size of surface defects in the defect feature information; a contact angle resolution adjustment module, configured to, after orthogonal verification of the first simulated cleaning control combination and the second simulated cleaning control combination, perform sub-region temperature field regulation of the cleaning work space and dynamically adjust the contact angle resolution by using an integrated cable surface energy tester in the cleaning work space; a dynamic supplementary scanning protocol trigger module, configured to simultaneously, in combination with the real-time feedback of the cleaning effect by a plasma density sensor, trigger a dynamic supplementary scanning protocol when it is detected that local cleaning is not thorough.

[0016] One or more technical solutions provided in the present application have at least the following technical effects or advantages: Identify the type of surface defects of the high-voltage cable to be cleaned; after the high-voltage cable to be cleaned is fixed in the cleaning work space, configure a first simulated cleaning control combination and a second simulated cleaning control combination according to the defect feature information; after orthogonal verification of the first simulated cleaning control combination and the second simulated cleaning control combination, perform sub-region temperature field regulation of the cleaning work space and dynamically adjust the contact angle resolution; simultaneously, in combination with the real-time feedback of the cleaning effect by a plasma density sensor, trigger a dynamic supplementary scanning protocol when it is detected that local cleaning is not thorough. The technical effect of achieving precise cleaning of the surface defects of the high-voltage cable and dynamic supplementary scanning of local non-thorough areas is achieved, and the cleaning quality is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings without creative efforts based on these drawings.

[0018] Figure 1 It is a schematic flowchart of a plasma cleaning method for surface defects of a high-voltage cable provided by an embodiment of the present application; Figure 2 This is a schematic structural diagram of a plasma cleaning system for surface defects of high-voltage cables provided by an embodiment of the present application.

[0019] Explanation of reference numerals: Surface defect identification module 10, cleaning control combination configuration module 20, contact angle resolution adjustment module 30, dynamic supplementary scan protocol trigger module 40. Specific embodiments

[0020] The present application provides a plasma cleaning method and system for surface defects of high-voltage cables, aiming to solve the technical problems of insufficient cleaning accuracy of surface defects of high-voltage cables and poor cleaning effect caused by incomplete local cleaning in the prior art.

[0021] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0022] Embodiment 1, as Figure 1 shown, the present application provides a plasma cleaning method for surface defects of high-voltage cables, and the method includes: Step S100: Identify the type of surface defects of the high-voltage cable to be cleaned, and associatively store defect feature information including the type of surface defects, the position of surface defects, and the size of surface defects.

[0023] Specifically, through the collaborative work of an industrial vision detection device and a three-dimensional laser scanning device, the surface of the high-voltage cable fixed in the cleaning work space is scanned, and convolutional neural network algorithms are used to identify surface defect types such as cracks, oxide layers, and oil stains. The spatial coordinates and size parameters such as length, width, and depth of the defects are synchronously obtained, and the defect type, position (accuracy up to 0.1 mm), and size data (error ±5%) are associatively stored as structured defect feature information, providing accurate data support for subsequent configuration of the movement path of the plasma nozzle, cleaning parameters, etc. for simulation control combinations.

[0024] Step S200: After the high-voltage cable to be cleaned is fixed in the cleaning work space, configure a first simulated cleaning control combination and a second simulated cleaning control combination according to the type of surface defects, the position of surface defects, and the size of surface defects in the defect feature information.

[0025] Specifically, when the high-voltage cable to be cleaned is fixed in the cleaning working space (positioning accuracy ±0.5 mm) through the tooling fixture, a two-dimensional simulation configuration is implemented based on the stored defect feature information: on the one hand, according to the defect position (such as 1.2 m from the end point) and size (such as a 5 mm × 3 mm pit), the defect contour is divided into micro-element regions, the moving trajectory of the plasma spray head is fitted by a spline curve, a safety margin of 2 - 3 mm is set, and the path is optimized with the goal of minimizing the idle travel time, forming a first simulated cleaning control combination including trajectory coordinates and moving speed; on the other hand, according to the defect type (such as the oxide layer), the type of plasma gas source is matched (such as argon-hydrogen mixed gas), and combined with the defect size (such as a depth of 0.2 mm), a parameter optimization model with the goal of minimizing the cleaning energy consumption is established, the optimal parameters such as the discharge power and working pressure are obtained by algorithm solving, and a second simulated cleaning control combination is constructed to provide precise control parameters for subsequent orthogonal verification and cleaning operations.

[0026] Step S300: After orthogonal verification of the first simulated cleaning control combination and the second simulated cleaning control combination, the temperature field of the cleaning working space is regulated by sub-region, and the contact angle resolution is dynamically adjusted using the integrated cable surface energy tester in the cleaning working space.

[0027] Specifically, first, temperature data is collected in real time in the cleaning working space, the energy requirements of each sub-region are introduced, and the temperature field is dynamically regulated by means of zone heating. At the same time, a coupling factor between the temperature and the plasma activity is set, and the discharge power in the cleaning parameters is feedback-adjusted based on this coupling factor; in addition, the integrated cable surface energy tester in the cleaning working space is used to dynamically adjust the contact angle resolution according to the cleaning accuracy requirements, and the contact angle measurement data is used to assist in evaluating the cleanliness of the cable surface. When the contact angle change rate is less than the set change rate threshold, a surface cleanliness judgment request is issued, and then a cleaning stage switching decision is made based on this request.

[0028] Step S400: At the same time, the cleaning effect is real-time feedback combined with the plasma density sensor. When it is detected that the local cleaning is incomplete, a dynamic supplementary scanning protocol is triggered.

[0029] Specifically, the plasma density sensor is used to monitor the plasma density in the cleaning area in real time. According to the correlation between the plasma density and the cleaning effect, when the plasma density deviates from the set value, the cleaning parameters of the plasma generator are automatically adjusted. At the same time, the surface of the high-voltage cable after cleaning is detected in real time. Once an uncleaned area is identified, a supplementary scanning path and supplementary scanning cleaning parameters are generated accordingly and uploaded to the control center. The control center's built-in dynamic supplementary scanning protocol is used to coordinate and configure the supplementary scanning operation. In addition, by analyzing the spatio-temporal distribution of the plasma density, the predicted cleaning blind spots during the cleaning process are obtained, and then the plasma spray head is co-controlled.

[0030] In a possible implementation manner, step S100 further includes: Step S110: Simulate the movement path of the plasma nozzle based on the surface defect position and surface defect size in the defect feature information, and obtain a first simulated cleaning control combination.

[0031] Step S120: Simulate the cleaning parameters of the plasma generator based on the surface defect type and surface defect size in the defect feature information, and obtain a second simulated cleaning control combination, where the cleaning parameters include the type of plasma gas source, working pressure, and discharge power.

[0032] Specifically, based on the surface defect position and size in the defect feature information, first divide the defect contour into multiple micro-element regions, then traverse these micro-element regions, use spline curves to fit the movement trajectories of the nozzle in each region, and set the safety margin of the nozzle movement path. Then, with the goal of minimizing the nozzle idle travel time, globally optimize the movement path of the plasma nozzle, and finally determine the first simulated cleaning control combination including parameters such as the nozzle movement trajectory and movement speed, so as to achieve the precise coverage of the defect area by the nozzle movement path and improve the cleaning efficiency.

[0033] Based on the surface defect type and size in the defect feature information, first establish a mapping matching table between the surface defect type and the type of plasma gas source, and then, with the goal function of minimizing the cleaning energy consumption, combine this mapping matching table and the surface defect size to optimize the cleaning parameters of the plasma generator (including the type of plasma gas source, working pressure, discharge power, etc.). Through algorithm solving, obtain the optimal cleaning parameter combination, so as to obtain the second simulated cleaning control combination, making the parameter configuration of the plasma generator adaptable to the defect type and size, and achieving energy consumption reduction while ensuring the cleaning effect.

[0034] In a possible implementation manner, step S110 further includes: Step S111: Divide the contour into multiple micro-element regions through the surface defect position and surface defect size in the defect feature information.

[0035] Step S112: Traverse the multiple micro-element regions, use spline curves to fit the movement trajectories of the nozzle in each micro-element region, and set the safety margin of the nozzle movement path.

[0036] Step S113: Based on the safety margin of the nozzle movement path, with the goal of minimizing the nozzle idle travel time, globally optimize the movement path of the plasma nozzle, and determine the first simulated cleaning control combination.

[0037] Specifically, when realizing contour division through the surface defect position and size in the defect feature information, a three-dimensional grid meshing algorithm is specifically adopted: first, based on the defect position coordinates (such as X meters away from the cable end point), the positioning of the defect in space is determined, and then according to the length, width, and depth size parameters of the defect, the defect contour is discretized with a grid accuracy of 0.1 - 1 mm, and it is divided into several regular or irregular micro-element regions in the three-dimensional space. During the division process, it is necessary to ensure that the size of each micro-element region does not exceed the effective action range of the plasma nozzle, and it can completely cover the defect edge and the uneven parts, so as to provide a refined spatial unit basis for the subsequent nozzle trajectory fitting.

[0038] When traversing multiple micro-element regions and fitting the nozzle movement trajectory, the surface point cloud data of each micro-element region is obtained by three-dimensional visual scanning, and the cubic spline curve algorithm is used to interpolate and fit the three-dimensional coordinates of the defect contour, so that the curve accurately fits the defect edge while ensuring continuity (fitting error ≤ 0.1 mm). During the fitting process, according to the physical size of the plasma nozzle (such as nozzle diameter) and the safe discharge distance (usually 2 - 5 mm), a safety margin region is generated by expanding in the normal direction of the fitting trajectory, and spatial vector operations are used to ensure that the nozzle movement path maintains a safe distance from the cable surface, avoiding collisions or abnormal discharges. At the same time, the fitting trajectories of adjacent micro-element regions are smoothed, and Bezier curves are used to connect the trajectory endpoints of different regions to ensure the continuity of the nozzle movement speed.

[0039] Based on the safety margin of the nozzle movement path, when performing global optimization with the goal of minimizing the nozzle idle travel time, first, the movement trajectories with safety margins of each micro-element region are constructed into a spatial node network, and each node contains parameters such as the start and end coordinates of the trajectory and the safety distance; then, with the goal of reducing the movement time of the nozzle in the non-cleaning area, the genetic algorithm is used to iteratively optimize the access order of the nodes and the trajectory connection method, and by calculating the distance between nodes and the nozzle movement speed, a path with the shortest idle travel is generated; at the same time, the ant colony algorithm is used to strengthen the search for the optimal path, and finally, the first simulated cleaning control combination including parameters such as the trajectory coordinate sequence, movement speed, and safety distance is determined, significantly shortening the idle travel time on the premise of ensuring the safe distance between the nozzle and the cable surface.

[0040] In a possible implementation manner, step S120 further includes: Step S121: Establish a mapping matching table between the surface defect type and the ion gas source type.

[0041] Step S122: Taking the minimization of cleaning energy consumption as the objective function, optimize the cleaning parameters according to the mapping matching table and the surface defect size, and determine the second simulated cleaning control combination.

[0042] Specifically, when establishing a mapping and matching table between surface defect types and plasma gas source types, first analyze the physical and chemical properties of common surface defects of high-voltage cables (such as oxide layers, oil residue, cracks, pits, etc.), and combine historical cleaning experiment data to statistically analyze the cleaning efficiency and surface damage degree of different gas sources (such as argon-oxygen mixed gas, hydrogen-nitrogen mixed gas, helium, etc.) for various defects, and then construct a standardized corresponding relationship database. For example, match the oxide layer defect with the argon-oxygen mixed gas with strong oxidizing property, the oil residue defect with the hydrogen-nitrogen mixed gas with high decomposition ability, and the crack defect with helium that is easy to penetrate into the gap to form a mapping and matching table that can directly guide the selection of gas sources.

[0043] When optimizing the cleaning parameters with the minimum cleaning energy consumption as the objective function, first determine the type of plasma gas source suitable for the surface defect type according to the established mapping and matching table, and then construct a multi-variable optimization model including parameters such as working pressure and discharge power in combination with the surface defect size (such as length, width, depth). Iteratively solve the model through the particle swarm optimization algorithm, and find the parameter combination corresponding to the minimum energy consumption on the premise of meeting the cleaning effect. For example, for small-size oxide layer defects, based on matching the argon-oxygen mixed gas, optimize to obtain low-energy consumption parameters of a working pressure of 50 Pa and a discharge power of 100 W; for large-size oil stains, optimize to obtain a parameter combination of a working pressure of 150 Pa and a discharge power of 300 W, and finally form a second simulated cleaning control combination including gas source type, working pressure, and discharge power to reduce the cleaning energy consumption while ensuring the cleaning efficiency.

[0044] In a possible implementation manner, step S300 further includes: Step S310: Real-time collect temperature data in the cleaning work space.

[0045] Step S320: Introduce the regional energy requirements of the cleaning work space, perform dynamic temperature field regulation by zone heating, and set the temperature-plasma activity coupling factor.

[0046] Step S330: Based on the temperature-plasma activity coupling factor, feedback and adjust the discharge power in the cleaning parameters.

[0047] Specifically, when real-time collecting temperature data in the cleaning work space, evenly arrange multiple high-precision temperature sensors (such as thermocouples or infrared temperature sensors) in the cleaning work space to monitor the temperature of different regions in the space in real time. The sensor sampling frequency is set according to the cleaning process requirements to ensure that temperature changes can be captured in time, and the collected temperature data is transmitted to the control system in real time to provide accurate data support for subsequent temperature field regulation.

[0048] After introducing the sub-region energy requirements of the cleaning workspace, according to the defect distribution and cleaning process requirements, the cleaning workspace is divided into several temperature control regions. Each region is equipped with an independent heating unit (such as a resistance heating plate or an infrared heating tube). The PLC control system dynamically adjusts the heating power of each region according to the temperature data collected in real time, realizing the dynamic adjustment of the temperature field in zones. For the setting of the temperature-plasma activity coupling factor, first, an experimental platform is built. In the temperature range of 25°C to 150°C, plasma cleaning experiments are carried out on typical defect samples. Under different temperature conditions, plasma diagnostic equipment (such as Langmuir probes, spectrometers, etc.) is used to measure active parameters such as plasma density, electron temperature, and ion concentration, and the corresponding cleaning efficiency data are recorded at the same time. Then, the multiple regression analysis method is used to fit the relationship between temperature, plasma active parameters, and cleaning efficiency, and a mathematical model is established. Finally, the expression of the temperature-plasma activity coupling factor is obtained as K(T)= , where: K(T) represents the coupling factor at temperature T, which is used to quantify the influence degree of temperature on plasma activity; T represents temperature, with the unit of degree Celsius (°C); and are coefficients obtained by fitting experimental data, reflects the activity benchmark at the initial temperature, reflects the influence rate of temperature change on activity. This factor is determined through the above specific experiments and mathematical fitting processes, providing an accurate quantitative basis for adjusting the discharge power based on temperature feedback later.

[0049] When adjusting the discharge power based on the feedback of the temperature-plasma activity coupling factor, first, the temperature data of the cleaning workspace are collected in real time through a temperature sensor, and the temperature-plasma activity coupling factor K(T)= already set is used to calculate the plasma activity level at the current temperature. When the temperature change causes the plasma activity to deviate from the set range, the influence degree of temperature on activity is quantified according to the coupling factor, and then a discharge power adjustment instruction is generated. For example, if the temperature rises and the plasma activity increases, the coupling factor value increases, and the discharge power is automatically reduced to avoid over-cleaning; conversely, when the temperature drops, the discharge power is increased to ensure that the plasma activity is maintained in the optimal cleaning range, thereby realizing the precise feedback adjustment of the discharge power and ensuring the stability and efficiency of the cleaning effect.

[0050] In a possible implementation manner, step S300 further includes: Step S340: Dynamically adjust the contact angle resolution of the cable surface energy tester according to the cleaning accuracy requirement, and use the contact angle measurement data to assist in evaluating the cable surface cleanliness.

[0051] Step S350: When the contact angle change rate is less than the set change rate threshold, a surface cleanliness judgment request is issued.

[0052] Step S360: Make a decision on switching the cleaning stage based on the surface cleanliness judgment request.

[0053] Specifically, according to the preset cleaning accuracy requirements (for example, the resolution needs to reach 0.1° during high-precision cleaning and 1° during conventional cleaning), the contact angle resolution of the cable surface energy tester is automatically adjusted dynamically. Specifically, the resolution is switched by sending instructions to the tester to change the magnification of its optical system and the image acquisition frequency. At the same time, the contact angle of the cable surface is measured in real time by this tester. Since the improvement of cleanliness will increase the surface energy and decrease the contact angle, the measured data is compared with the standard cleanliness database to assist in evaluating the current cleanliness of the cable surface.

[0054] Calculate in real time the change rate of the contact angle on the cable surface per unit time (for example, calculate the angular change of the contact angle in seconds), and compare this change rate with a preset threshold (such as 0.5° / s). When the contact angle change rates in multiple consecutive sampling periods (such as 3 - 5 periods) are all less than the set threshold, it indicates that the improvement rate of the cable surface cleanliness has tended to be slow and the cleaning effect is close to a stable state. At this time, a surface cleanliness judgment request is sent to the main control module to trigger a comprehensive evaluation process of the current cable surface cleanliness status.

[0055] When receiving the surface cleanliness judgment request, the multi-source information such as the contact angle measurement data, plasma density feedback, and temperature field distribution is integrated to evaluate the current cleanliness of the cable surface. If the evaluation result shows that the cleanliness requirement of the current cleaning stage has been met, a decision will be made to switch to the next cleaning stage. For example, switch from the rough cleaning stage to the fine cleaning stage. After determining the switch, a stage switch instruction is automatically generated, and the relevant cleaning parameters are adjusted synchronously, such as reducing the discharge power to avoid over-cleaning, and improving the movement accuracy of the plasma nozzle to achieve a more refined cleaning operation, so as to ensure that the entire cleaning process can be advanced efficiently and orderly.

[0056] In a possible implementation manner, step S400 further includes: Step S410: Measure the plasma density.

[0057] Step S420: Set the empirical index of the plasma density and the cleaning effect. When the deviation degree of the plasma density from the set value exceeds the deviation threshold, the cleaning parameters of the plasma generator are automatically adjusted.

[0058] Specifically, by installing a plasma density sensor (such as a Langmuir probe or a microwave interferometer) in the cleaning workspace, the density value of the plasma is measured in real time. The sensor converts the collected plasma particle concentration signal into an electrical signal and transmits it to the control system for processing to ensure the real-time and accuracy of the measurement data, providing a basis for subsequent adjustment of cleaning parameters.

[0059] When setting the empirical index of plasma density and cleaning effect and realizing automatic parameter adjustment, the following means are specifically adopted: First, based on historical experimental data, a mapping relationship database of plasma density and cleaning efficiency is constructed, and regression analysis is used to determine the empirical index model E = k· (where E is the cleaning efficiency, is the plasma density, and k and n are fitting coefficients), and corresponding density set values and deviation thresholds (such as ±10%) are set for different defect types. When the plasma density sensor (such as a Langmuir probe) measures the density value in real time, calculate the deviation degree of the current density from the set value = | | / ×100%. If exceeds the threshold, immediately automatically adjust the discharge power (adjustment step 5 - 10 W) or working pressure (adjustment step 10 - 20 Pa) of the plasma generator through a PID controller to make the density return to the optimal range. During the adjustment process, continuously optimize the parameter combination based on the empirical index model to ensure the stability of the cleaning effect.

[0060] In a possible implementation manner, step S400 further includes: Step S430: Perform real-time detection on the surface of the high-voltage cable after cleaning to identify areas that are not thoroughly cleaned.

[0061] Step S440: Generate a supplementary scanning path and supplementary scanning cleaning parameters according to the areas that are not thoroughly cleaned.

[0062] Step S450: Upload the supplementary scanning path and supplementary scanning cleaning parameters to the control center, and use the dynamic supplementary scanning protocol built in the control center to coordinate and configure the supplementary scanning operation.

[0063] Specifically, when performing real-time detection on the surface of the high-voltage cable after cleaning, a high-resolution linear array camera and a laser scanner installed at the exit of the cleaning workspace are used to scan the surface of the cable to obtain two-dimensional images and three-dimensional topography data of the surface. The data is processed and analyzed through a convolutional neural network algorithm and compared with the data of the standard clean surface, so as to identify the areas with pollutant residues or incomplete cleaning, and mark the position, size, shape and other information of these areas, providing an accurate basis for subsequent supplementary scanning operations.

[0064] According to the information such as the position, shape and size of the incompletely cleaned areas identified, a supplementary scanning path is generated using a path planning algorithm (such as the A algorithm or the RRT algorithm), ensuring that the path can cover all the uncleaned areas and has the shortest path length, while avoiding the areas that have been cleaned to improve efficiency. Then, according to the defect types (such as oxide layer, oil stain, etc.) and severity of the incompletely cleaned areas, the corresponding supplementary scanning and cleaning parameters are retrieved from the preset parameter library, including the types of plasma gas sources, working pressure, discharge power, etc., and finally an accurate supplementary scanning path and supplementary scanning and cleaning parameters are generated.

[0065] The generated supplementary scanning path and supplementary scanning and cleaning parameters (including the types of plasma gas sources, working pressure, discharge power, etc.) are uploaded to the control center through industrial Ethernet or fieldbus. After receiving the data, the control center, according to the built-in dynamic supplementary scanning protocol, first determines the priority of the supplementary scanning task. If there are multiple uncleaned areas, they are sorted according to the severity of the defects. Then, it coordinates the operation timings of devices such as plasma generators, nozzle moving mechanisms, and gas supply systems. First, it sends a gas source switching instruction to the gas mixing device to switch the gas source to the type required for supplementary scanning, then adjusts the discharge power and working pressure of the plasma generator to the set values for supplementary scanning, and at the same time controls the nozzle to move along the planned supplementary scanning path. During the movement, it monitors the plasma density and temperature field distribution in real time to ensure the accurate execution of the supplementary scanning operation, realizes the coordinated cooperation between the cleaning parameters and the mechanical movement, and completes the efficient supplementary scanning of the incompletely cleaned areas.

[0066] In a possible implementation manner, step S450 further includes: Step S451: Obtain the predicted cleaning blind spots during the cleaning process through the spatio-temporal distribution analysis of the plasma density.

[0067] Step S452: Coordinate the control of the plasma nozzle with the predicted cleaning blind spots.

[0068] Specifically, the plasma density data at different positions and time points in the cleaning working space are collected in real time through a plasma density sensor, a spatio-temporal distribution matrix is constructed, and the digital signal processing algorithm (such as fast Fourier transform) is used to analyze the spatial distribution law and time variation trend of the density data. Combining the geometric characteristics of the cable surface and the nozzle movement trajectory, the areas where the plasma density is lower than the effective cleaning threshold are identified, and then the possible cleaning blind spots during the cleaning process are predicted, that is, the areas where the plasma fails to fully cover or the cleaning intensity is insufficient, providing a basis for the subsequent nozzle control.

[0069] According to the obtained predicted cleaning blind area, multi-axis linkage control instructions are generated to coordinately control the plasma spray head. By adjusting the three-dimensional movement trajectory (X / Y / Z axes) of the spray head, the spray head automatically reduces the movement speed and increases the residence time when passing through the blind area. At the same time, the pitch angle and yaw angle of the spray head are linked and adjusted to ensure that the plasma spraying direction is perpendicular to the surface of the blind area to improve the cleaning efficiency. In addition, in combination with the predicted insufficient plasma density in the blind area, the discharge power of the plasma generator is increased in real time (the adjustment range is 5% - 15%) and the working air pressure is optimized to enhance the plasma density in the blind area. Through the coordinated adjustment of the mechanical movement of the spray head and the cleaning parameters, targeted coverage of the predicted cleaning blind area is achieved, ensuring the uniformity of the cable surface cleaning.

[0070] Embodiment 2, based on the same inventive concept as the plasma cleaning method for surface defects of high-voltage cables in the foregoing embodiment, as Figure 2 shown, the present application provides a plasma cleaning system for surface defects of high-voltage cables. The system in the embodiment of the present application and the method embodiment are based on the same inventive concept. Among them, the system includes: A surface defect recognition module 10, which is used to recognize the types of surface defects of the high-voltage cable to be cleaned, and associatively store defect feature information including the types of surface defects, the positions of surface defects, and the sizes of surface defects.

[0071] A cleaning control combination configuration module 20, which is used to configure a first simulated cleaning control combination and a second simulated cleaning control combination according to the types of surface defects, the positions of surface defects, and the sizes of surface defects in the defect feature information after the high-voltage cable to be cleaned is fixed in the cleaning work space.

[0072] A contact angle resolution adjustment module 30, which is used to perform orthogonal verification on the first simulated cleaning control combination and the second simulated cleaning control combination, regulate the temperature field of sub-regions in the cleaning work space, and dynamically adjust the contact angle resolution using an integrated cable surface energy tester in the cleaning work space.

[0073] A dynamic supplementary scanning protocol trigger module 40, which is used to simultaneously, in combination with the real-time feedback of the cleaning effect by the plasma density sensor, trigger a dynamic supplementary scanning protocol when it is detected that the local cleaning is incomplete.

[0074] Furthermore, the system is also used to implement the following functions: Simulate the movement path of the plasma spray head according to the positions and sizes of surface defects in the defect feature information to obtain a first simulated cleaning control combination; simulate the cleaning parameters of the plasma generator according to the types and sizes of surface defects in the defect feature information to obtain a second simulated cleaning control combination, where the cleaning parameters include the types of plasma gas sources, working air pressure, and discharge power.

[0075] Further, the system is also used to implement the following functions: Divide the profile into multiple micro-regions according to the surface defect position and surface defect size in the defect feature information; traverse the multiple micro-regions, fit the movement trajectory of the nozzle in each micro-region with a spline curve, and set the safety margin of the nozzle movement path; based on the safety margin of the nozzle movement path, with the goal of minimizing the nozzle idle travel time, globally optimize the movement path of the plasma nozzle to determine the first simulated cleaning control combination.

[0076] Further, the system is also used to implement the following functions: Establish a mapping and matching table between the surface defect type and the type of plasma gas source; with the minimum cleaning energy consumption as the objective function, optimize the cleaning parameters according to the mapping and matching table and the surface defect size to determine the second simulated cleaning control combination.

[0077] Further, the system is also used to implement the following functions: Real-time collect temperature data in the cleaning workspace; introduce the regional energy requirements of the cleaning workspace, perform dynamic temperature field regulation by zone heating, and set the temperature-plasma activity coupling factor; based on the temperature-plasma activity coupling factor, feedback and adjust the discharge power in the cleaning parameters.

[0078] Further, the system is also used to implement the following functions: Dynamically adjust the contact angle resolution of the cable surface energy tester according to the cleaning accuracy requirement, and use the contact angle measurement data to assist in evaluating the cable surface cleanliness; when the contact angle change rate is less than the set change rate threshold, issue a surface cleanliness judgment request; make a cleaning stage switching decision based on the surface cleanliness judgment request.

[0079] Further, the system is also used to implement the following functions: Measure the plasma density; set the empirical index of the plasma density and the cleaning effect, and automatically adjust the cleaning parameters of the plasma generator when the deviation degree of the plasma density from the set value exceeds the deviation threshold.

[0080] Further, the system is also used to implement the following functions: Perform real-time detection on the surface of the high-voltage cable after cleaning to identify the areas that are not thoroughly cleaned; generate a supplementary scanning path and supplementary scanning cleaning parameters according to the areas that are not thoroughly cleaned; upload the supplementary scanning path and supplementary scanning cleaning parameters to the control center, and use the dynamic supplementary scanning protocol built in the control center to coordinate and configure the supplementary scanning operation.

[0081] Further, the system is also used to implement the following functions: Through the spatio-temporal distribution analysis of the plasma density, a predicted cleaning blind area during the cleaning process is obtained; and the plasma nozzle is cooperatively controlled with the predicted cleaning blind area.

[0082] It should be noted that the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of the present specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0084] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A plasma cleaning method for surface defects of high-voltage cables, characterized in that, The method includes: Identifying the surface defect types of the high-voltage cable to be cleaned, and associatively storing defect feature information including surface defect types, surface defect positions, and surface defect sizes; After the high-voltage cable to be cleaned is fixed in the cleaning workspace, configuring a first simulated cleaning control combination and a second simulated cleaning control combination according to the surface defect type, surface defect position, and surface defect size in the defect feature information; After orthogonal verification of the first simulated cleaning control combination and the second simulated cleaning control combination, regulating the sub-region temperature field of the cleaning workspace, and dynamically adjusting the contact angle resolution using an integrated cable surface energy tester in the cleaning workspace; Meanwhile, combining a plasma density sensor to real-time feedback the cleaning effect, and triggering a dynamic supplementary scanning protocol when it is detected that the local cleaning is incomplete.

2. The plasma cleaning method for surface defects of high-voltage cables according to claim 1, characterized in that, Simulating the movement path of the plasma nozzle based on the surface defect position and surface defect size in the defect feature information to obtain the first simulated cleaning control combination; Simulating the cleaning parameters of the plasma generator based on the surface defect type and surface defect size in the defect feature information to obtain the second simulated cleaning control combination, where the cleaning parameters include plasma gas source type, working air pressure, and discharge power.

3. The plasma cleaning method for surface defects of high-voltage cables according to claim 2, characterized in that, Simulating the movement path of the plasma nozzle based on the surface defect position and surface defect size in the defect feature information to obtain the first simulated cleaning control combination, the method includes: Dividing the contour into multiple micro-element regions through the surface defect position and surface defect size in the defect feature information; Traversing the multiple micro-element regions, fitting the movement trajectory of the nozzle in each micro-element region using a spline curve, and setting the safety margin of the nozzle movement path; Based on the safety margin of the nozzle movement path, globally optimizing the movement path of the plasma nozzle with the goal of minimizing the nozzle idle travel time to determine the first simulated cleaning control combination.

4. The plasma cleaning method for surface defects of high-voltage cables according to claim 3, characterized in that, Simulating the cleaning parameters of the plasma generator based on the surface defect type and surface defect size in the defect feature information to obtain the second simulated cleaning control combination, the method includes: Establishing a mapping matching table between the surface defect type and the plasma gas source type; Taking minimizing the cleaning energy consumption as the objective function, optimizing the cleaning parameters according to the mapping matching table and the surface defect size to determine the second simulated cleaning control combination.

5. The plasma cleaning method for surface defects of high-voltage cables according to claim 2, characterized in that, After orthogonal verification of the first simulated cleaning control combination and the second simulated cleaning control combination, regulating the sub-region temperature field of the cleaning workspace, the method includes: Real-time collecting temperature data in the cleaning workspace; Introducing the sub-region energy requirements of the cleaning workspace, dynamically adjusting the temperature field by zone heating, and setting the temperature-plasma activity coupling factor; Based on the temperature-plasma activity coupling factor, feedback-adjusting the discharge power in the cleaning parameters.

6. The plasma cleaning method for surface defects of high-voltage cables according to claim 5, characterized in that, Dynamically adjusting the contact angle resolution using an integrated cable surface energy tester in the cleaning workspace, the method includes: Dynamically adjust the contact angle resolution of the cable surface energy tester according to the cleaning precision requirement, and use the contact angle measurement data to assist in evaluating the cable surface cleanliness; When the contact angle change rate is less than the set change rate threshold, send a surface cleanliness judgment request; Make a decision on the cleaning stage switch based on the surface cleanliness judgment request.

7. The plasma cleaning method for surface defects of high-voltage cables according to claim 2, characterized in that, Combined with the real-time feedback of the cleaning effect by the plasma density sensor, the method includes: Measure the plasma density; Set the empirical index of the plasma density and the cleaning effect. When the deviation degree of the plasma density from the set value exceeds the deviation degree threshold, automatically adjust the cleaning parameters of the plasma generator.

8. The plasma cleaning method for surface defects of high-voltage cables according to claim 7, characterized in that, When it is detected that the local cleaning is incomplete, trigger the dynamic supplementary scanning protocol. The method includes: Perform real-time detection on the surface of the high-voltage cable after cleaning to identify the areas where the cleaning is not thorough; Generate a supplementary scanning path and supplementary scanning cleaning parameters according to the areas where the cleaning is not thorough; Upload the supplementary scanning path and supplementary scanning cleaning parameters to the control center, and use the dynamic supplementary scanning protocol built in the control center to coordinate and configure the supplementary scanning operation.

9. The plasma cleaning method for surface defects of high-voltage cables according to claim 8, wherein, Obtain the predicted cleaning blind area during the cleaning process through the spatio-temporal distribution analysis of the plasma density; Cooperatively control the plasma nozzle with the predicted cleaning blind area.

10. A plasma cleaning system for surface defects of high-voltage cables, characterized in that, The system is used to implement the plasma cleaning method for the surface defects of the high-voltage cable according to any one of claims 1-9. The system includes: A surface defect identification module, which is used to identify the types of surface defects of the high-voltage cable to be cleaned, and associatively store the defect characteristic information including the surface defect type, surface defect position, and surface defect size; A cleaning control combination configuration module, which is used to configure the first simulated cleaning control combination and the second simulated cleaning control combination according to the surface defect type, surface defect position, and surface defect size in the defect characteristic information after the high-voltage cable to be cleaned is fixed in the cleaning work space; A contact angle resolution adjustment module, which is used to perform orthogonal verification on the first simulated cleaning control combination and the second simulated cleaning control combination, regulate the temperature field of the sub-regions of the cleaning work space, and dynamically adjust the contact angle resolution by using the cable surface energy tester integrated in the cleaning work space; A dynamic supplementary scanning protocol trigger module, which is used to simultaneously, combined with the real-time feedback of the cleaning effect by the plasma density sensor, trigger the dynamic supplementary scanning protocol when it is detected that the local cleaning is incomplete.

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