A plasma processing apparatus and method for wire surface insulation coating

Abstract

The application discloses a kind of wire surface insulation coating with plasma processing device and processing method, including device body, support wheel being supported on wire being arranged in the device body, low-temperature plasma generator being arranged in device body and inductive mechanism being symmetrically arranged on the both sides of the device body, cleaning mechanism for cleaning wire surface is equipped at the front end of device body;Support wheel is supported on wire, drives device body to walk on wire, cleaning mechanism is cleaned to dust on the surface of wire, and inductive mechanism at the front end acquires wire surface characteristic signal, and signal is transmitted to host computer, so as to control low-temperature plasma generator ion plasma parameter configuration scheme, wire surface is pretreated, and inductive mechanism at the rear end of device body detects processing effect, can be adjusted plasma parameter according to wire material difference and size change in real time, effectively improve the consistency and stability of wire surface processing, and be applicable to accurate surface treatment of different types of wire.

Description

Technical Field

[0001] This invention relates to the field of conductor insulation coating, and more specifically to a plasma treatment apparatus and method for conductor surface insulation coating. Background Technology

[0002] Conductor insulation coating technology is crucial in the fields of power, communication, and electronic equipment, directly affecting the safety, reliability, and lifespan of the equipment. High-quality insulation coatings can effectively prevent conductor short circuits, leakage current, and aging, ensuring stable system operation. However, existing conductor insulation coating methods have significant limitations in practical applications.

[0003] Traditional surface treatment techniques, such as chemical cleaning or mechanical polishing, often fail to completely remove the oxide layer and micro-contaminants from the surface of the conductors, resulting in insufficient adhesion between the coating and the conductors, making them prone to peeling or cracking. Furthermore, these methods struggle to ensure uniform surface treatment when processing conductors with complex shapes, increasing instability in the production process.

[0004] In the field of conductor insulation coating, the core challenge lies in effectively improving the interfacial adhesion between the conductor surface and the insulation coating. Oxide layers and contaminants on the conductor surface are the primary factors affecting adhesion; these impurities hinder the close contact between the coating material and the conductor substrate, leading to insufficient adhesion. Furthermore, during surface treatment, if processing conditions, such as treatment intensity and time, are not precisely controlled, damage to the conductor substrate may occur, affecting its mechanical or electrical properties. This contradiction between the surface modification effect and substrate damage makes achieving uniform and controllable surface treatment a technical challenge. Therefore, how to optimize surface treatment conditions to enhance coating adhesion and avoid substrate damage while removing oxide layers and contaminants from the conductor surface has become a key issue in conductor insulation coating technology research. Summary of the Invention

[0005] The purpose of this invention is to solve the above-mentioned problems and provide a plasma treatment device and method for insulating coating of conductor surfaces. This device and method can adjust plasma parameters in real time according to differences in conductor material and size changes, effectively improving the consistency and stability of conductor surface treatment. It is suitable for precise surface treatment of different types of conductors.

[0006] The technical solution adopted by this invention to solve its technical problem is: A plasma treatment device for insulating coating of wire surface includes a device body, a support wheel disposed in the device body and supported on the wire, a low temperature plasma generator disposed in the device body and a sensing mechanism symmetrically disposed on both sides of the device body, and a cleaning mechanism for cleaning the wire surface is provided at the front end of the device body. The cleaning mechanism includes a mounting plate disposed at the front end of the device body and a rotating frame symmetrically disposed at the lower end of the mounting plate and rotatably connected between the mounting plates. The rotating frame includes a vertical part and a horizontal part. A brush that rotates on the horizontal part is provided on the horizontal part. A crossbar is provided at one end of the inner side of the horizontal part of the rotating frame. A tension spring is provided between the outer side of the rotating frame and the mounting plate.

[0007] Furthermore, the device body includes a central arc-shaped portion and inclined portions disposed at both ends of the arc-shaped portion.

[0008] Furthermore, a counterweight is provided at the lower end of the inclined portion of the device body.

[0009] Furthermore, the sensing mechanism includes an annular fixing plate disposed at the end of the device body, and a plurality of industrial cameras are evenly arranged within the annular fixing plate.

[0010] Furthermore, the lower end of the annular fixing plate is provided with an opening, and each opening end is provided with an outwardly inclined plate.

[0011] Furthermore, a plasma treatment method for insulating coating of a conductor surface, utilizing the aforementioned apparatus, includes the following steps: S101 Acquires initial characteristic distribution information by collecting surface signals of the conductor through a sensor array; S102 Determines the mapping relationship between conductor surface characteristics and plasma parameters based on the initial characteristic distribution information and a pre-established discharge parameter model, generating a preliminary plasma parameter configuration scheme; S103 Dynamically adjusts the preliminary plasma parameter configuration scheme using an adaptive control algorithm to determine the optimal parameter adjustment range; S104 Calibrates the plasma equipment through a closed-loop feedback mechanism and generates calibration parameter execution instructions; S105 Drives the plasma equipment according to the calibration parameter execution instructions, acquires operating data, and judges the stability of conductor surface treatment parameters; S106 Acquires conductor surface state change information through secondary detection and determines whether the preprocessing consistency standard has been met; S107 If the preprocessing consistency standard has not been met, optimizes the adaptive control algorithm, generates a new parameter adjustment strategy, drives the equipment to update its operating state, and determines the consistency of conductor surface characteristics.

[0012] Further, step S103 includes the following steps: An initial set of plasma parameters is obtained, and the trend of parameter changes is calculated to obtain a preliminary set of influence weights. Based on the preliminary set of influence weights, and in combination with changes in wire size and material differences, the plasma parameters are dynamically adjusted to determine the range of parameter changes. If the range of parameter changes exceeds a preset threshold, a particle swarm optimization algorithm is used for iterative adjustment to obtain an optimized set of parameters. The final influence weights are then calculated to determine the optimal parameter adjustment range.

[0013] Further, step S104 includes the following steps: If the parameter adjustment range exceeds the preset threshold range, the parameter adjustment value is calculated using the support vector machine algorithm to obtain the adjustment value sequence; a calibration parameter set is generated based on the adjustment value sequence; if the deviation between the calibration parameter set and the device state exceeds the preset threshold, the calibration parameter set is optimized using the gradient descent algorithm to generate an execution instruction sequence, which is transmitted to the device control module to obtain the calibration effect evaluation result.

[0014] Further, step S107 includes the following steps: The surface state change information is obtained by the state detection module, and it is determined whether the change information reaches a preset threshold.

[0015] If the change information does not reach the preset threshold, the gradient descent algorithm is used to iteratively optimize the adaptive control algorithm to obtain the updated control parameter set.

[0016] Based on the updated set of control parameters, a parameter adjustment strategy is generated, and the priority order of the parameter adjustments is determined.

[0017] If the priority order meets the preset conditions, the adjustment strategy is applied through the automated system to obtain a new surface treatment parameter scheme, and the surface state change information is collected again for judgment.

[0018] The beneficial effects of this invention are: 1. This invention includes a device body, support wheels mounted on a wire within the device body, a low-temperature plasma generator within the device body, and sensing mechanisms symmetrically arranged on both sides of the device body. A cleaning mechanism for cleaning the wire surface is located at the front end of the device body. During pretreatment of the wire surface, the device body is hoisted onto the wire by a drone, with the support wheels supporting it and propelling the device body along the wire. Simultaneously, the cleaning mechanism cleans dust from the wire surface. The front-end sensing mechanism collects characteristic signals from the wire surface and transmits these signals to a host computer, thereby controlling the plasma parameter configuration scheme of the low-temperature plasma generator to pretreat the wire surface. The sensing mechanism at the rear end of the device body detects the treatment effect and can adjust plasma parameters in real time according to differences in wire material and size variations, effectively improving the consistency and stability of wire surface treatment. This invention is suitable for precise surface treatment of different types of wires.

[0019] 2. The cleaning mechanism in this invention includes a mounting plate disposed at the front end of the device body and a rotating frame symmetrically disposed at the lower end of the mounting plate and rotatably connected between the mounting plates. The rotating frame includes a vertical part and a horizontal part. A brush rotating on the horizontal part of the rotating frame is provided. Crossbars are provided at one end of the inner side of the horizontal part of the rotating frame, and a tension spring is provided between the outer side of the rotating frame and the mounting plate. Under normal circumstances, under the action of the tension spring, the rotating frame rotates outward to its outermost position. At this time, the crossbars on both sides are crossed, and the lower end of the brush is tilted outward. After the device body is supported on the wire, the lower end of the wire contacts the crossbar at the intersection position. Under the weight of the device body itself, the crossbar swings upward, and the brushes on both sides rotate to the vertical position. The rotation of the brushes cleans the dust on the surface of the wire, facilitating subsequent plasma treatment.

[0020] 3. This invention acquires real-time surface state data of the conductor using a sensor array, obtains initial characteristic distribution information using multi-channel data fusion technology, and analyzes the mapping relationship between conductor surface characteristics and plasma parameters using a preset discharge parameter model to determine a preliminary parameter configuration scheme. An adaptive control algorithm is used to dynamically calculate the optimal parameter adjustment range, and a closed-loop feedback mechanism is used to calibrate the working state of the plasma equipment. A secondary inspection is also performed on the processed conductor surface; if it does not meet the standards, the control algorithm is iteratively optimized and the parameter configuration is updated. This method can adjust plasma parameters in real time according to differences in conductor material and size variations, effectively improving the consistency and stability of conductor surface treatment, and is suitable for precise surface treatment of different types of conductors. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of the present invention. Figure 1 ; Figure 2 This is the front view of the present invention; Figure 3 This is a schematic diagram of the structure of the present invention. Figure 2 ; Figure 4 This is a flowchart of the present invention; Figure 5 This is a flowchart of the parameter configuration adjustment process for this invention; Figure 6 This is a flowchart of the plasma calibration process of the present invention; Figure 7 This is a flowchart of the secondary parameter configuration and adjustment process for this invention.

[0022] In the diagram: 1. Device body; 2. Support wheel; 3. Low-temperature plasma generator; 4. Mounting plate; 5. Rotating frame; 6. Brush; 7. Crossbar; 8. Tension spring; 9. Counterweight; 10. Annular fixing plate; 11. Industrial camera; 12. Opening; 13. Inclined plate. Detailed Implementation

[0023] like Figure 1 and Figure 3 As shown, a plasma treatment device for insulating coating of wire surfaces includes a device body 1, a support wheel 2 mounted inside the device body 1 and supported on the wire, a low-temperature plasma generator 3 mounted inside the device body 1, and sensing mechanisms symmetrically arranged on both sides of the device body 1. The support wheel 2 has a groove on its outer cylindrical surface for guiding. A motor is installed inside the device body 1 to drive the support wheel 2 to rotate. A cleaning mechanism for cleaning the wire surface is located at the front end of the device body 1. During pretreatment of the wire surface, the device body 1 is hoisted onto the wire by a drone, with the support wheel 2 supporting it and moving the device body 1 along the wire. Simultaneously, the cleaning mechanism cleans the dust from the wire surface. The front-end sensing mechanism collects characteristic signals from the wire surface and transmits these signals to a host computer, thereby controlling the plasma parameter configuration scheme of the low-temperature plasma generator 3 to pretreat the wire surface. The rear-end sensing mechanism of the device body 1 detects the treatment effect and can adjust the plasma parameters in real time according to differences in wire material and size changes, effectively improving the consistency and stability of wire surface treatment. This device is suitable for precise surface treatment of different types of wires.

[0024] like Figure 3 As shown, the cleaning mechanism includes a mounting plate 4 located at the front end of the device body 1 and a rotating frame 5 symmetrically arranged at the lower end of the mounting plate 4 and rotatably connected between the mounting plates 4. The rotating frame 5 includes a vertical part and a horizontal part. The upper end of the vertical part is rotatably connected to the mounting plate 4. A brush 6 rotating on the horizontal part is provided on the horizontal part, and a motor driving the brush 6 to rotate is provided on the horizontal part. Crossbars 7 are arranged alternately on one side of the horizontal part of the rotating frame 5, and a tension spring 8 is provided between the outer side of the rotating frame 5 and the mounting plate 4. Under normal circumstances, under the action of the tension spring 8, the rotating frame 5 rotates outward to the outermost position. At this time, the crossbars 7 on both sides are crossed, and the lower end of the brush 6 is tilted outward. After the device body 1 is supported on the wire, the lower end of the wire contacts the crossbar 7 at the intersection position. Under the action of the weight of the device body 1, the crossbar 7 swings upward, and the brushes 6 on both sides rotate to the vertical position. The brushes 6 rotate to clean the dust on the surface of the wire, which is convenient for subsequent plasma treatment.

[0025] A low-temperature plasma generator is a device that generates plasma in a low-temperature environment. It primarily generates plasma through the following methods: Electric field excitation: Utilizing electric field energy to excite gas molecules, causing them to ionize and form plasma. Radio frequency or microwave excitation: Providing energy through radio frequency or microwave power supplies to ionize atoms or molecules in the gas. Chemical vapor deposition (CVD): Generating plasma through chemical reactions in a low-temperature environment for material deposition. Key technical features include: Low-temperature operation: Operating at or near room temperature, avoiding damage to materials from high temperatures. Generation of highly reactive substances: Capable of generating large amounts of high-energy electrons, ions, free radicals, and other reactive substances for purification, sterilization, and material modification. Non-thermal equilibrium method: Generating plasma using a non-thermal equilibrium method, resulting in high efficiency and low energy consumption. Strong environmental adaptability: Stable discharge in dry air, high-humidity air, or water. Simple operation: The device is easy to operate; plasma is generated simply by pressing a button. When applied to surface treatment, it is used for cleaning, activation, etching, and coating of material surfaces, improving the hydrophilicity, hydrophobicity, and adhesion of materials.

[0026] like Figure 2 As shown, the device body 1 includes a central arc-shaped portion and inclined portions disposed at both ends of the arc-shaped portion.

[0027] The lower end of the inclined portion of the device body 1 is provided with a counterweight 9 to prevent the device body 1 from falling off the wire.

[0028] like Figure 2 As shown, the sensing mechanism includes an annular fixing plate 10 disposed at the end of the device body 1, and a plurality of industrial cameras 11 are evenly disposed within the annular fixing plate 10.

[0029] The lower end of the annular fixing plate 10 is provided with an opening 12, and each end of the opening 12 is provided with an outwardly inclined plate 13. By setting the inclined plate 13, it is convenient for the wire to pass through the opening and be supported on the support wheel 2.

[0030] like Figure 4 As shown, a plasma treatment method for insulating coating of a conductor surface, utilizing the aforementioned apparatus, includes the following steps: S101 Acquires initial characteristic distribution information by collecting surface signals of the conductor through a sensor array; S102 Determines the mapping relationship between conductor surface characteristics and plasma parameters based on the initial characteristic distribution information and a pre-established discharge parameter model, generating a preliminary plasma parameter configuration scheme; S103 Dynamically adjusts the preliminary plasma parameter configuration scheme using an adaptive control algorithm to determine the optimal parameter adjustment range; S104 Calibrates the plasma equipment through a closed-loop feedback mechanism and generates calibration parameter execution instructions; S105 Drives the plasma equipment according to the calibration parameter execution instructions, acquires operating data, and judges the stability of conductor surface treatment parameters; S106 Acquires conductor surface state change information through secondary detection and determines whether the preprocessing consistency standard has been met; S107 If the preprocessing consistency standard has not been met, optimizes the adaptive control algorithm, generates a new parameter adjustment strategy, drives the equipment to update its operating state, and determines the consistency of conductor surface characteristics.

[0031] Step S101 mainly includes: acquiring multi-channel signals from the surface of the conductor through a sensor array to obtain the raw data stream; The original data stream is preprocessed using multi-channel data fusion technology to obtain a fused signal vector; If the signal-to-noise ratio of the fused signal vector is greater than a preset threshold, then the main features are extracted through principal component analysis to obtain the principal component feature set; The feature values ​​of the surface state points of the conductor are calculated based on the principal component feature set to obtain the surface feature vector; By performing cluster analysis on the surface feature vectors, the differences in wire materials are classified to obtain a classification feature map. Based on the classification feature map, the surface characteristic distribution of the conductor is generated to obtain the final distribution chart.

[0032] Step S102 mainly includes obtaining initial characteristic data and distribution data of the conductor surface from the repository and constructing a basic data set for characteristic analysis; Based on the aforementioned characteristic analysis data set, a pre-constructed discharge parameter model is used to derive the mapping relationship between the surface characteristics of the conductor and the plasma parameters. If the analysis results show that the correlation between the surface characteristics of the conductor and the plasma parameters is lower than a preset threshold, the model parameters are adjusted by regression analysis algorithm to obtain optimized mapping data. Key influencing factors of plasma parameters are extracted from the optimized mapping data to determine a preliminary parameter configuration direction. Based on this preliminary parameter configuration direction and the output of the discharge parameter model, a draft plasma parameter configuration scheme for the current conductor is generated.

[0033] When constructing discharge parameter models and deriving the mapping relationship between conductor surface characteristics and plasma parameters, it can be understood in principle that the surface roughness or oxide layer thickness of the conductor affects the discharge stability of the plasma. Suppose that in an analysis, when the conductor surface roughness is high, the current density distribution of the plasma discharge is uneven, resulting in a correlation of only 0.6 in the mapping relationship data, lower than the preset threshold of 0.8. In this case, it is necessary to adjust the model parameters through regression analysis algorithms, such as increasing the weighting factor for surface roughness. The optimized correlation improves to 0.85, and the mapping relationship data is more consistent with reality.

[0034] For cases where the correlation in the mapping relationship data is below a threshold, the implementation of the regression analysis algorithm can be specified as follows: By comparing historical data, it is analyzed that the surface oxide layer thickness accounts for approximately 30% of the influence on plasma discharge voltage, while the roughness accounts for 50%. Based on this, the weight allocation of relevant parameters in the model is adjusted, and the mapping relationship is recalculated to ensure that the model output better matches the actual working conditions.

[0035] like Figure 5 As shown, step S103 includes the following steps: obtaining an initial plasma parameter set, which includes wire size and material difference data. An adaptive control algorithm is used to analyze the initial plasma parameter set, calculate the parameter change trend, and obtain a preliminary influence weight set. Based on the preliminary influence weight set, combined with wire size changes and material differences, the plasma parameters are dynamically adjusted to determine the parameter change range. If the parameter change range exceeds a preset threshold, a particle swarm optimization algorithm is used to iteratively adjust the plasma parameters to obtain an optimized parameter set. Based on the optimized parameter set, the final influence weights of wire size changes and material differences are calculated to obtain the weight distribution result. Based on the weight distribution result, the control strategy of the adaptive control algorithm is dynamically adjusted to determine the optimal parameter adjustment range.

[0036] When obtaining the initial set of plasma parameters, we can start by examining the basic properties of the wires, collecting data on differences in wire size and material. Assume the wire diameter ranges from 2.5 to 5.0 mm, and the material includes both copper and aluminum. Differences in size and material directly affect the performance of the plasma parameters; therefore, these differences need to be categorized, stored, and initially organized for subsequent algorithm analysis.

[0037] When using an adaptive control algorithm to analyze the initial parameter set, the influence weights can be estimated by monitoring the parameter change trends in real time. For example, in a certain analysis, it was found that for every 1.0 mm increase in the wire diameter, the plasma parameter response value changes by 10%, while when the material is switched from copper to aluminum, the response value changes by 15%.

[0038] When dynamically adjusting plasma parameters based on the initial set of influence weights, adjustment strategies can be set separately for changes in conductor size and material differences. For example, if larger diameter conductors require higher parameter values ​​to maintain stability, while aluminum conductors are more sensitive to parameter variations, a reasonable range of variation can be determined by gradually adjusting the parameter values. This approach ensures the targeted and effective nature of parameter adjustments.

[0039] If the parameter variation range exceeds a preset threshold, a particle swarm optimization algorithm can be introduced for iterative adjustment. Assuming the preset threshold is ±5%, while the actual variation range reaches ±8%, multiple parameter combinations can be simulated to gradually approach the optimal solution, ultimately obtaining an optimized parameter set with a variation range controlled within ±4.5%. This method can converge quickly under complex conditions, improving the stability of parameter configuration.

[0040] When calculating the final impact weights of conductor size variation and material difference, a weighted analysis can be used to obtain specific distribution results. Assuming the final calculation shows that the impact weight of size variation on the parameters is 40%, and material difference is 60%, this provides a clear direction for subsequent strategy adjustments. Through this quantitative analysis, the proportion of each factor's influence can be grasped more accurately.

[0041] When dynamically adjusting the control strategy of the adaptive control algorithm based on the weight distribution results, parameter optimization can be prioritized for material differences that have a higher impact weight. For example, for aluminum conductors, the parameter adjustment frequency can be increased by 20% to accommodate their higher sensitivity, ultimately determining the optimal parameter adjustment range. This dynamic adjustment method can significantly improve the adaptability and efficiency of parameter configuration, helping to maintain system stability under different conductor conditions.

[0042] like Figure 6 As shown, step S104 includes the following steps: If the parameter adjustment range exceeds a preset threshold range, the parameter adjustment value is calculated using a support vector machine algorithm to obtain an adjustment value sequence. Based on the adjustment value sequence, a closed-loop feedback mechanism is used to generate calibration parameters to obtain a calibration parameter set. If the deviation between the calibration parameter set and the device state exceeds a preset threshold range, the calibration parameter set is optimized using a gradient descent algorithm to obtain an optimized parameter set, where the gradient descent algorithm formula is: θ=θ-α∇J(θ), where θ represents the calibration parameter, α represents the learning rate, and ∇J(θ) represents the gradient of the loss function. An execution instruction sequence is generated based on the optimized parameter set and transmitted to the device control module using instruction distribution technology to obtain the instruction execution status. Based on the instruction execution status, real-time response data of the device is obtained, and the calibration effect is judged through data comparison and analysis to obtain a calibration effect evaluation result. If the calibration effect evaluation result does not meet the preset standard, the dynamic calculation model is updated through a feedback mechanism to obtain updated model parameters.

[0043] In plasma parameter adjustment scenarios, when parameter adjustment ranges exceed preset thresholds, a support vector machine (SVM) algorithm can be used to calculate an adjustment value sequence. The core of the SVM algorithm lies in constructing an optimal classification boundary to distinguish the influence ranges of different parameters, thereby deriving reasonable adjustment values. For example, in the analysis of differences in wire size and material, if the system detects that a certain parameter deviates from the threshold by 20%, the SVM algorithm can generate an adjustment value sequence to gradually control the deviation within 5%.

[0044] When generating the calibration parameter set, the closed-loop feedback mechanism collects real-time equipment operating data and compares it with the expected parameters, forming a dynamic calibration process. If plasma parameters fluctuate due to material differences during operation, the closed-loop feedback mechanism generates calibration parameters based on real-time data, reducing the fluctuation range from the initial 15% to approximately 3%. This method continuously monitors the equipment status, ensuring the stability of parameter adjustments.

[0045] If the deviation between the calibration parameter set and the device state exceeds a preset threshold, optimization can be achieved using the gradient descent algorithm. The principle of gradient descent is to iteratively adjust parameter values, gradually approaching the minimum value of the loss function, thereby optimizing the calibration parameters. Assuming the initial deviation of a calibration parameter is 10%, through multiple iterations, the deviation can be reduced to below 1%. This method can gradually approach the optimal solution and improve calibration accuracy when dealing with complex parameter optimization.

[0046] When generating and transmitting the sequence of execution instructions to the device control module, the instruction distribution technology ensures that the instructions are delivered to the device accurately according to priority and timing, avoiding instruction conflicts.

[0047] Data comparison and analysis are crucial when acquiring real-time device response data and assessing calibration effectiveness. By comparing real-time data with expected values, it's possible to evaluate whether the calibration has achieved its intended purpose. For example, if the device's parameter fluctuations are controlled within 2% after calibration, while the preset standard is 3%, then the calibration is considered successful.

[0048] If the calibration results are unsatisfactory, updating the dynamic calculation model becomes a necessary step. The feedback mechanism adjusts the model parameters based on the calibration effect evaluation results to better reflect the actual operating environment. For example, if a model initially has an 8% prediction deviation for material differences, the deviation can be reduced to 2% after updating through the feedback mechanism.

[0049] Step S105 includes the following steps: acquiring pre-calibrated parameter data, converting the calibration parameters into operation commands through a preset interface, transmitting them to the plasma equipment control module, and driving the plasma equipment to start operation. During plasma equipment operation, a real-time monitoring module collects operating data from equipment sensors to obtain an initial dataset. A data cleaning tool removes noise interference from the initial dataset to obtain a processed operating data set. If the parameter fluctuation value in the processed operating data set exceeds a preset threshold, a parameter adjustment mechanism is triggered, generating an adjustment command. The adjustment command drives the plasma equipment to perform parameter correction, and the corrected operating data is collected to obtain an updated dataset. If the updated dataset shows that parameter stability does not meet a preset standard, a support vector machine algorithm is used to extract features from the updated dataset to determine the key factors affecting stability. Based on the key factors, optimized operation commands are generated, transmitted to the equipment control module, drive the plasma equipment to perform parameter adjustment, collect final operating data, and determine the stability of the wire surface treatment parameters.

[0050] Assuming that the pre-calibrated parameters before the equipment is started include a voltage of 5000 volts and a gas flow rate of 10 liters per minute, these parameters are converted into specific control signals through a preset interface and transmitted to the equipment control module to ensure that the equipment starts up according to the predetermined parameters.

[0051] In scenarios where the adjustment mechanism is triggered when the parameter fluctuation value exceeds the preset threshold, assuming that the running data group shows that the gas pressure fluctuation exceeds the allowable range by more than 5%, the system will automatically generate an adjustment command to reduce the gas input rate.

[0052] The process of generating optimized operation instructions and transmitting them to the equipment control module assumes that, based on key factor analysis, the system generates instructions to increase cooling power by 10%, and collects final operating data in real time to determine whether the surface treatment parameters of the conductors are stable, and adopts a closed-loop adjustment method.

[0053] Step S106 includes the following steps: acquiring equipment operation monitoring data; preprocessing the monitoring data using a data processing module to obtain a standardized dataset; performing a secondary detection process based on the standardized dataset to extract feature parameters of the conductor surface to obtain surface characteristic data; using the surface characteristic data, performing classification processing using a support vector machine algorithm to determine surface state change characteristics and obtain state change information; if the state change information exceeds a preset threshold, extracting key change features using a principal component analysis algorithm to obtain a simplified change dataset; calculating the deviation value from the preprocessing consistency standard for the simplified change dataset, determining whether it meets the consistency standard, and obtaining a consistency evaluation result.

[0054] like Figure 7As shown, step S107 includes the following steps: acquiring surface state change information, and determining whether the change information reaches a preset threshold through a state detection module. If the change information does not reach the preset threshold, an initial state dataset is generated through the state detection module to determine the parameter range to be optimized. Based on the initial state dataset, the adaptive control algorithm is iteratively optimized using a gradient descent algorithm to obtain an updated control parameter set. Based on the updated control parameter set, a parameter adjustment strategy is generated to determine the priority order of parameter adjustments. If the priority order meets preset conditions, the adjustment strategy is applied to subsequent processing through an automated system to obtain a new surface treatment parameter scheme. The surface state change information is re-acquired through the state detection module, and it is determined whether the re-acquired change information reaches a preset threshold. If the re-acquired change information still does not reach the preset threshold, the re-acquired dataset is compared with the initial state dataset, and the difference is analyzed using a K-means clustering algorithm to obtain an optimization direction parameter set. Based on the optimization direction parameter set, the weights of the adaptive control algorithm are updated to generate a final surface treatment parameter scheme and determine the execution scheme for subsequent processing.

[0055] The core of the condition detection module is to collect microscopic change data on the surface of the conductor in real time, such as surface roughness or oxide layer thickness. By comparing it with a preset threshold, such as roughness not exceeding 2.5 micrometers, it can determine whether further optimization is needed.

[0056] Gradient descent algorithms can find the optimal combination of control parameters, such as the current intensity or processing time of the surface treatment equipment, by gradually adjusting these parameters. Assuming an initial current intensity of 5 amps and a processing time of 10 minutes, after multiple iterations, it might be adjusted to 4.5 amps and 12 minutes to better suit the actual needs of the wire surface. This approach progressively approximates the optimal solution, ensuring the accuracy of parameter adjustments.

[0057] Priority can be determined based on the weight of each parameter's impact on surface treatment. For example, if current intensity accounts for 60% of the surface smoothness effect, while processing time accounts for 40%, then current intensity should be adjusted first. If the priority order meets preset conditions, such as current adjustment having a higher priority than time adjustment, the automated system will adjust the current parameter first, then the time parameter, ensuring the stability of the processing. This applies to the topic of re-collecting surface state change information and determining whether a threshold has been reached.

[0058] The key indicators of the conductor surface can be measured again through the state detection module, such as whether the oxide layer thickness has dropped below 0.3 micrometers. If the threshold is still not reached, the difference is analyzed by comparing it with the initial state dataset. For example, if the initial oxide layer thickness was 0.5 micrometers and the current thickness is 0.4 micrometers, it indicates that the optimization direction is correct but the magnitude is insufficient.

[0059] K-means clustering can divide differential data into multiple categories, such as temperature-affected categories and humidity-affected categories, and assign different weight adjustment coefficients to each category. For example, the weight of temperature-affected data can be increased from 0.3 to 0.5, thereby generating the final surface treatment parameter scheme.

[0060] Step S107: Based on the adjusted set of driving parameters, execute the configuration operation of the device driving module to update the device's operating status data. Extract real-time information from the operating status data, record the real-time information using a data acquisition module, and generate a structured status dataset. For the structured status dataset, extract feature information related to the conductor surface to obtain a preliminary feature description of the conductor surface. If outliers exist in the preliminary feature description, filter them using a preset threshold to obtain a corrected feature description; if there are no outliers, directly use the preliminary feature description as the corrected feature description. Use a support vector machine algorithm to classify the corrected feature description to determine the consistency measurement result of the conductor surface characteristics. Based on the consistency measurement result, generate the final evaluation data of the conductor surface characteristics to complete the judgment of the characteristic consistency degree.

[0061] In a scenario involving surface inspection of conductors, the device drive module needs to adjust its operating frequency and detection accuracy based on new parameters. One possible approach is to set the frequency value in the drive parameters to 50Hz to accommodate the specific conductor material being inspected, while simultaneously adjusting the detection accuracy to an error range of 0.1mm to ensure the capture of minute surface variations.

[0062] When extracting relevant feature information from the conductor surface and obtaining a preliminary feature description, two core indicators can be considered: surface roughness and texture distribution. Suppose that in a single inspection, the roughness value is 2.5 micrometers, and the texture distribution is uneven. One possible approach is to quantify the texture distribution using image analysis techniques to generate a preliminary feature description report.

[0063] In the outlier filtering process, if the roughness value in the initial feature description suddenly jumps to 10 micrometers, which is significantly beyond the normal range of 2.0-3.0 micrometers, the outlier data can be filtered out by a preset threshold, and the corrected feature description will use 2.5 micrometers as the reference value.

[0064] When using the Support Vector Machine (SVM) algorithm to classify the corrected feature descriptions, the surface characteristics of the conductor can be divided into two categories: uniform and non-uniform. Assuming that in a single classification, 80% of the feature data is classified as uniform and the remaining 20% ​​as non-uniform, the system will generate a consistency measurement result showing a high degree of consistency. When generating the final evaluation data for conductor surface characteristics, a report including surface quality grades can be generated by combining the consistency measurement results. Assuming a high degree of consistency, the evaluation data will classify the conductor surface quality as Grade 1, indicating that its characteristics meet production requirements. This evaluation method provides a clear reference direction for subsequent process adjustments and helps optimize the production process. Through the above examples and analyses, it can be seen that every step from equipment configuration to final evaluation is closely centered on the business needs of conductor surface inspection, ensuring data continuity and analytical reliability, while providing multi-dimensional reference for process improvement.

Claims

1. A plasma treatment method for insulating coating of a conductor surface, characterized in that, A plasma treatment device for insulating coating of wire surface is used. The device includes a device body (1), a support wheel (2) set inside the device body (1) and supported on the wire, a low temperature plasma generator (3) set inside the device body (1) and a sensing mechanism symmetrically arranged on both sides of the device body (1). A cleaning mechanism for cleaning the wire surface is provided at the front end of the device body (1). The cleaning mechanism includes a mounting plate (4) disposed at the front end of the device body (1) and a rotating frame (5) symmetrically disposed at the lower end of the mounting plate (4) and rotatably connected to the mounting plate (4). The rotating frame (5) includes a vertical part and a horizontal part. A brush (6) rotating on the horizontal part is provided on the horizontal part of the rotating frame (5). A crossbar (7) is provided at one end of the inner side of the horizontal part of the rotating frame (5). A tension spring (8) is provided between the outer side of the rotating frame (5) and the mounting plate (4). The device body (1) includes a central arc-shaped portion and inclined portions at both ends of the arc-shaped portion; The device body (1) has a counterweight (9) at the lower end of its inclined portion. The sensing mechanism includes an annular fixing plate (10) disposed at the end of the device body (1), and a plurality of industrial cameras (11) are uniformly disposed within the annular fixing plate (10). The lower end of the annular fixing plate (10) is provided with an opening (12), and each end of the opening (12) is provided with an outwardly inclined plate (13). The method includes the following steps: S101 Acquires initial characteristic distribution information by collecting surface signals of the conductor through a sensor array; S102 Determines the mapping relationship between conductor surface characteristics and plasma parameters based on the initial characteristic distribution information and a pre-established discharge parameter model, generating a preliminary plasma parameter configuration scheme; S103 Dynamically adjusts the preliminary plasma parameter configuration scheme using an adaptive control algorithm to determine the optimal parameter adjustment range; S104 Calibrates the plasma equipment through a closed-loop feedback mechanism and generates calibration parameter execution instructions; S105 Drives the plasma equipment according to the calibration parameter execution instructions, acquires operating data, and judges the stability of conductor surface treatment parameters; S106 Acquires conductor surface state change information through secondary detection and determines whether the preprocessing consistency standard has been met; S107 If the preprocessing consistency standard has not been met, optimizes the adaptive control algorithm, generates a new parameter adjustment strategy, drives the equipment to update its operating state, and determines the consistency of conductor surface characteristics.

2. The plasma treatment method for insulating coating of a conductor surface as described in claim 1, characterized in that, Step S103 includes the following steps: obtaining an initial set of plasma parameters, calculating the parameter change trend, and obtaining a preliminary set of influence weights; dynamically adjusting the plasma parameters based on the preliminary set of influence weights, combined with changes in wire size and material differences, and determining the parameter change range; if the parameter change range exceeds a preset threshold, using a particle swarm optimization algorithm for iterative adjustment to obtain an optimized parameter set, calculating the final influence weights, and determining the optimal parameter adjustment range.

3. The plasma treatment method for insulating coating of a conductor surface as described in claim 1, characterized in that, Step S104 includes the following steps: If the parameter adjustment range exceeds the preset threshold range, the parameter adjustment value is calculated using the support vector machine algorithm to obtain the adjustment value sequence; a calibration parameter set is generated based on the adjustment value sequence; if the deviation between the calibration parameter set and the device state exceeds the preset threshold, the calibration parameter set is optimized using the gradient descent algorithm to generate an execution instruction sequence, which is transmitted to the device control module to obtain the calibration effect evaluation result.

4. The plasma treatment method for insulating coating of a conductor surface as described in claim 1, characterized in that, Step S107 includes the following steps: The surface state change information is obtained through the state detection module, and it is determined whether the change information reaches a preset threshold. If the change information does not reach the preset threshold, the gradient descent algorithm is used to iteratively optimize the adaptive control algorithm to obtain the updated control parameter set. Based on the updated control parameter set, a parameter adjustment strategy is generated, and the priority order of the parameter adjustments is determined; If the priority order meets the preset conditions, the adjustment strategy is applied through the automated system to obtain a new surface treatment parameter scheme, and the surface state change information is collected again for judgment.

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