Plasma processing device and plasma processing method for insulating coating of surface of wire

Abstract

The invention discloses a plasma processing device and method for insulation coating of the surface of a wire, and the device comprises a device body, a supporting wheel which is disposed in the device body and is supported on the wire, a low-temperature plasma generator disposed in the device body, and induction mechanisms which are symmetrically disposed at the two sides of the device body. A cleaning mechanism for cleaning the wire surface is arranged at the front end of the device body; the supporting wheel is supported on the wire and drives the device body to walk on the wire, the cleaning mechanism cleans dust on the surface of the wire, and the induction mechanism at the front end collects characteristic signals of the surface of the wire and transmits the signals to the upper computer, so that a plasma parameter configuration scheme of the low-temperature plasma generator is controlled, and the surface of the wire is pretreated. The induction mechanism at the rear end of the device body detects the processing effect, plasma parameters can be adjusted in real time according to wire material differences and size changes, the consistency and stability of wire surface processing are effectively improved, and the device is suitable for accurate surface processing of different types of wires.

Description

Technical Field

[0001] The invention relates to the field of wire insulation coating, in particular to a plasma processing device and a processing method for wire surface insulation coating. Background Art

[0002] Wire insulation coating technology is crucial in the power, communications, and electronic equipment sectors, directly impacting the safety, reliability, and service life of these devices. High-quality insulation coatings effectively prevent short circuits, leakage, and aging in wires, ensuring stable system operation. However, existing wire insulation coating methods have significant limitations in practical applications.

[0003] Traditional surface treatment techniques, such as chemical cleaning or mechanical polishing, often struggle to completely remove the oxide layer and microscopic contaminants on the conductor surface. This results in insufficient adhesion between the coating and the conductor, leading to flaking or cracking. Furthermore, these methods struggle to ensure uniform surface treatment when treating complex conductor shapes, increasing instability in the production process.

[0004] In the field of wire insulation coating, the core challenge focuses on how to effectively improve the interfacial bonding strength between the wire surface and the insulating coating. The oxide layer and contaminants on the wire surface are the primary factors affecting the bonding strength. These impurities hinder the close contact between the coating material and the wire substrate, resulting in insufficient adhesion. Furthermore, during the surface treatment process, if the treatment conditions, such as treatment intensity and time, cannot be precisely controlled, it may cause damage to the wire substrate, affecting its mechanical properties or conductive properties. This contradiction between the surface modification effect and substrate damage makes achieving uniform and controllable surface treatment a technical difficulty. Therefore, how to optimize the surface treatment conditions to enhance coating adhesion and avoid substrate damage while removing the oxide layer and contaminants on the wire surface has become a key issue in the research of wire insulation coating technology. Summary of the Invention

[0005] The purpose of the present invention is to solve the above-mentioned problems and provide a plasma treatment device and treatment method for wire surface insulation coating, which can adjust the plasma parameters in real time according to the differences in wire materials and size changes, effectively improving the consistency and stability of wire surface treatment, and is suitable for precise surface treatment of different types of wires.

[0006] The technical solution adopted by the present invention to solve the technical problem is: A plasma treatment device for insulating the surface of a conductor comprises a device body, a support wheel arranged in the device body and supported on the conductor, a low-temperature plasma generator arranged in the device body, and induction mechanisms symmetrically arranged on both sides of the device body. A cleaning mechanism for cleaning the surface of the conductor is provided at the front end of the device body. The cleaning mechanism includes a mounting plate arranged at the front end of the device body, a rotating frame symmetrically arranged at the lower end of the mounting plate and rotatably connected between the mounting plates, the rotating frame includes a vertical portion and a horizontal portion, a brush rotating on the horizontal portion is provided on the horizontal portion of the rotating frame, cross bars are staggered at one end of the inner side of the horizontal portion of the rotating frame, and 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 arranged 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 arranged at the end of the device body, and a plurality of industrial cameras are evenly arranged in the annular fixing plate.

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

[0011] Furthermore, a plasma treatment method for insulating the surface of a wire using the device comprises the following steps: S101 collects wire surface signals through a sensor array to obtain initial characteristic distribution information; S102 determines the mapping relationship between wire surface characteristics and plasma parameters based on the initial characteristic distribution information and a pre-established discharge parameter model, and generates 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 to generate calibration parameter execution instructions; S105 drives the plasma equipment according to the calibration parameter execution instructions, obtains operating data, and determines the stability of the wire surface treatment parameters; S106 obtains wire surface state change information through secondary detection to determine whether the pretreatment consistency standard is met; S107 If the pretreatment consistency standard is not met, the adaptive control algorithm is optimized to generate a new parameter adjustment strategy, drive the equipment to update the operating state, and determine the consistency of the wire surface characteristics.

[0012] Furthermore, step S103 includes the following steps: An initial set of plasma parameters is obtained, and the parameter change trend is calculated to obtain a preliminary set of influence weights. Based on the preliminary set of influence weights, combined with changes in wire size 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 for iterative adjustment to obtain an optimized parameter set, calculate the final influence weight, and determine the optimal parameter adjustment range.

[0013] Furthermore, step S104 includes the following steps: If the parameter adjustment range exceeds the preset threshold range, the parameter adjustment value is calculated by the support vector machine algorithm to obtain an 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 by the gradient descent algorithm, an execution instruction sequence is generated, and transmitted to the device control module to obtain the calibration effect evaluation result.

[0014] Furthermore, step S107 includes the following steps: The surface state change information is obtained through the state detection module to determine whether the change information reaches a preset threshold.

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

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

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

[0018] The beneficial effects of the present invention are: 1. The present invention includes a device body, a support wheel arranged inside the device body and supported on the wire, a low-temperature plasma generator arranged inside the device body, and a sensing mechanism symmetrically arranged on both sides of the device body. A cleaning mechanism for cleaning the surface of the wire is provided at the front end of the device body. When pre-treating the surface of the wire, the device body is hoisted onto the wire by an unmanned aerial vehicle, and the support wheel is supported on the wire, driving the device body to move on the wire. At the same time, the cleaning mechanism cleans the dust on the surface of the wire. The sensing mechanism at the front end collects characteristic signals of the wire surface and transmits the signals to the host computer, thereby controlling the plasma parameter configuration scheme of the low-temperature plasma generator to pre-treat the surface of the wire. The sensing mechanism at the rear end of the device body detects the treatment effect and can adjust the plasma parameters in real time according to the differences in wire material and size changes, effectively improving the consistency and stability of the wire surface treatment and being suitable for precise surface treatment of different types of wires.

[0019] 2. The cleaning mechanism of the present invention includes a mounting plate provided at the front end of the device body, a rotating frame symmetrically provided at the lower end of the mounting plate and rotatably connected between the mounting plates, the rotating frame including a vertical portion and a horizontal portion, the horizontal portion of the rotating frame being provided with a brush that rotates on the horizontal portion, one end of the inner side of the horizontal portion of the rotating frame being provided with a staggered cross bar, and a tension spring being 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 the outermost side. At this time, the cross bars on both sides are cross-arranged, and the lower ends of the brushes tilt outward. After the device body is supported on the wire, the wire contacts the lower end of the cross bar at the intersection. Under the action of the device body's own weight, the cross bar swings upward, and the brushes on both sides rotate to a vertical position. The rotation of the brushes cleans the dust on the surface of the wire, facilitating subsequent plasma treatment.

[0020] 3. The present invention uses a sensor array to collect wire surface state data in real time, utilizes multi-channel data fusion technology to obtain initial characteristic distribution information, and analyzes the mapping relationship between wire surface characteristics and plasma parameters in combination with 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 operating state of the plasma equipment. The treated wire surface is also subjected to a secondary inspection. If it does not meet the standards, the control algorithm is iteratively optimized and the parameter configuration is updated. This method 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 and being suitable for precise surface treatment of different types of wires. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Schematic diagram of the structure of the present invention Figure 1 ; Figure 2 This is the main view of the present invention; Figure 3 Schematic diagram of the structure of the present invention Figure 2 ; Figure 4 Flowchart of the present invention; Figure 5 This is a flow chart of the primary parameter configuration adjustment of the present invention; Figure 6 This is a flow chart of plasma calibration of the present invention; Figure 7 This is a flow chart of the secondary parameter configuration adjustment of the present invention.

[0022] In the figure: device body 1, support wheel 2, low-temperature plasma generator 3, mounting plate 4, rotating frame 5, brush 6, cross bar 7, tension spring 8, counterweight 9, annular fixing plate 10, industrial camera 11, opening 12, inclined plate 13. DETAILED DESCRIPTION

[0023] like Figure 1 and Figure 3 As shown, a plasma treatment device for wire surface insulation coating includes a device body 1, a support wheel 2 arranged in the device body 1 and supported on the wire, a low-temperature plasma generator 3 arranged in the device body 1, and sensing mechanisms symmetrically arranged on both sides of the device body 1, wherein the outer cylindrical surface of the support wheel 2 is provided with a groove for guiding cooperation, the device body 1 is provided with a motor for driving the support wheel 2 to rotate, and the front end of the device body 1 is provided with a cleaning mechanism for cleaning the surface of the wire; when pre-treating the surface of the wire, the device body 1 is hoisted onto the wire by an unmanned aerial vehicle, and the support wheel 2 is supported on the wire, driving the device body 1 to move on the wire. At the same time, the cleaning mechanism cleans the dust on the surface of the wire, and the sensing mechanism at the front end collects the characteristic signal of the wire surface and transmits the signal to the host computer, thereby controlling the plasma parameter configuration scheme of the low-temperature plasma generator 3 to pre-treat the surface of the wire. The sensing mechanism at the rear end of the device body 1 detects the treatment effect and can adjust the plasma parameters in real time according to the material difference and size change of the wire, effectively improving the consistency and stability of the wire surface treatment, and is suitable for precise surface treatment of different types of wires.

[0024] like Figure 3 As shown, the cleaning mechanism comprises a mounting plate 4 positioned at the front end of the device body 1, and a rotatable frame 5 symmetrically positioned below the mounting plate 4 and pivotally connected thereto. The rotatable frame 5 comprises a vertical portion and a horizontal portion, the upper end of the vertical portion pivotally connected to the mounting plate 4. The horizontal portion of the rotatable frame 5 is provided with a brush 6 that rotates within the horizontal portion, and a motor that drives the brush 6. Crossbars 7 are arranged staggered on one end of the inner side of the horizontal portion of the rotatable frame 5, and a tension spring 8 is positioned between the outer side of the rotatable frame 5 and the mounting plate 4. Under normal circumstances, under the action of the tension spring 8, the rotatable frame 5 rotates outward to its outermost position. At this point, the crossbars 7 on either side intersect, and the lower ends of the brushes 6 tilt outward. After the device body 1 is supported on the conductor, the conductor contacts the lower ends of the crossbars 7 at the intersection. Under the weight of the device body 1, the crossbars 7 swing upward, causing the brushes 6 on either side to rotate to their vertical position. The rotation of the brushes 6 cleans dust from the surface of the conductor, facilitating subsequent plasma treatment.

[0025] A low-temperature plasma generator is a device that generates plasma in a low-temperature environment. It primarily uses the following methods to generate plasma: Electric field excitation: Utilizing electric field energy to excite gas molecules, ionizing them to form plasma. Radio frequency or microwave excitation: Radiating energy from a radio frequency or microwave power source ionizes atoms or molecules in the gas. Chemical vapor deposition (CVD) technology: In a low-temperature environment, plasma is generated through chemical reactions for material deposition. Technical features include: Low-temperature operation: Operating at or near room temperature, it avoids high-temperature damage to materials. Highly reactive species generation: Generates large quantities of high-energy electrons, ions, free radicals, and other reactive species for purification, sterilization, and material modification. Non-thermal equilibrium method: Plasma generation utilizes a non-thermal equilibrium method, resulting in high efficiency and low energy consumption. Environmental adaptability: Stable discharge is possible in dry air, high-humidity air, or water. Easy operation: The device is simple to operate, generating plasma at the touch of a button. Applications for surface treatment include cleaning, activation, etching, and coating materials, improving their hydrophilicity, hydrophobicity, and adhesion.

[0026] like Figure 2 As shown, the device body 1 includes an arc-shaped portion in the middle and inclined portions arranged at both ends of the arc-shaped portion.

[0027] A counterweight 9 is provided at the lower end of the inclined portion of the device body 1 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 arranged at the end of the device body 1, and a plurality of industrial cameras 11 are evenly arranged in the annular fixing plate 10.

[0029] The lower end of the annular fixing plate 10 is provided with an opening 12 , and both ends of the opening 12 are provided with an outwardly inclined inclined plate 13 . The inclined plate 13 facilitates the wire to pass through the opening and be supported on the supporting wheel 2 .

[0030] like Figure 4 As shown, a plasma treatment method for insulating the surface of a wire using the device includes the following steps: S101 collects wire surface signals through a sensor array to obtain initial characteristic distribution information; S102 determines the mapping relationship between wire surface characteristics and plasma parameters based on the initial characteristic distribution information and a pre-established discharge parameter model, and generates 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 to generate calibration parameter execution instructions; S105 drives the plasma equipment according to the calibration parameter execution instructions, obtains operating data, and determines the stability of the wire surface treatment parameters; S106 obtains wire surface state change information through secondary detection to determine whether the pretreatment consistency standard is met; S107 If the pretreatment consistency standard is not met, the adaptive control algorithm is optimized to generate a new parameter adjustment strategy, drive the equipment to update the operating state, and determine the consistency of the wire surface characteristics.

[0031] Step S101 mainly includes: collecting multi-channel signals on the surface of the wire through a sensor array to obtain an original data stream; and preprocessing the original data stream using a 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, principal component analysis is performed to extract the main features to obtain a principal component feature set; Calculate the characteristic values ​​of the conductor surface state points according to the principal component feature set to obtain a surface characteristic vector; By performing cluster analysis on the surface feature vectors, the wire material difference classification is determined to obtain a classification feature map, and the surface characteristic distribution of the conductor is generated according to the classification feature map to obtain a final distribution chart.

[0032] Step S102 mainly includes obtaining initial characteristic data and distribution data of the conductor surface from the storage library to construct a basic data set for characteristic analysis; Based on the characteristic analysis basic data set, a pre-built discharge parameter model is used to derive mapping relationship data between the surface characteristics of the wire and the plasma parameters; For the mapping relationship data, if the analysis result shows that the correlation between the surface characteristics of the wire and the plasma parameters is lower than a preset threshold, the model parameters are adjusted through a regression analysis algorithm to obtain optimized mapping relationship data; Extract key influencing factors of plasma parameters from the optimized mapping relationship data to determine a preliminary parameter configuration direction. Based on the preliminary parameter configuration direction and combined with the output of the discharge parameter model, generate a draft plasma parameter configuration plan for the current conductor.

[0033] When constructing a discharge parameter model and deriving the mapping relationship data between wire surface characteristics and plasma parameters, it can be understood in principle that the roughness of the wire surface or the thickness of the oxide layer affects the discharge stability of the plasma. Suppose, in an analysis, high wire surface roughness leads to an uneven distribution of the plasma discharge current density, resulting in a correlation of only 0.6 in the mapping relationship data, which is lower than the preset threshold of 0.8. In this case, the model parameters need to be adjusted through a regression analysis algorithm, such as increasing the weighting factor for surface roughness. After optimization, the correlation is increased to 0.85, making the mapping relationship data more realistic.

[0034] For cases where the correlation in the mapping data falls below the threshold, the implementation of the regression analysis algorithm can be specifically implemented as follows: By comparing historical data, it is determined that the thickness of the surface oxide layer influences the plasma discharge voltage by approximately 30%, while the roughness influences the plasma discharge voltage by 50%. Based on this, the weight distribution of relevant parameters in the model is adjusted and the mapping relationship is recalculated to ensure that the model output is more consistent with actual operating conditions.

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

[0036] When acquiring an initial set of plasma parameters, we can start with the basic properties of the wire, collecting data on wire size and material variations. Assume that the wire diameter ranges from 2.5 to 5.0 mm, and the materials include copper and aluminum. Differences in size and material directly affect plasma parameter performance, so these differences need to be categorized, stored, and initially organized for subsequent algorithm analysis.

[0037] When using an adaptive control algorithm to analyze an initial set of parameters, the influence weights can be calculated by monitoring parameter trends in real time. For example, suppose an analysis reveals that for every 1.0 mm increase in wire diameter, the plasma parameter response changes by 10%, while switching from copper to aluminum results in a 15% change.

[0038] When dynamically adjusting plasma parameters based on a preliminary set of influence weights, adjustment strategies can be tailored to suit variations in wire size and material. For example, if a larger diameter wire requires a higher parameter value to maintain stability, while aluminum wire is more sensitive to the parameter, the parameter value can be gradually adjusted to determine a reasonable range of variation. This approach ensures targeted and effective parameter adjustments.

[0039] If the parameter variation range exceeds the preset threshold, a particle swarm optimization algorithm can be used for iterative adjustment. For example, if the preset threshold is ±5%, and 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 of ±4.5%. This method can quickly converge under complex conditions and improve the stability of parameter configuration.

[0040] When calculating the final impact weights of wire size changes and material differences, a weighted analysis can yield specific distribution results. Assuming the final calculation shows that size changes have a 40% impact on parameters, and material differences have a 60% impact, this provides a clear direction for subsequent strategy adjustments. This quantitative analysis allows for a more precise understanding of the proportion of each factor's influence.

[0041] When dynamically adjusting the adaptive control algorithm's control strategy based on the weight distribution results, parameter optimization can prioritize material differences with higher weights. 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 approach significantly improves the adaptability and efficiency of parameter configuration, helping to maintain system stability under varying conductor conditions.

[0042] like Figure 6 As shown, step S104 includes the following steps: If the parameter adjustment range exceeds a preset threshold, calculating parameter adjustment values ​​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, the calibration parameter set is optimized using a gradient descent algorithm to obtain an optimized parameter set. 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. Based on the optimized parameter set, an execution instruction sequence is generated and transmitted to the device control module using instruction distribution technology to obtain an instruction execution status. Based on the instruction execution status, real-time device response data is obtained, and the calibration effect is determined 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 the feedback mechanism to obtain updated model parameters.

[0043] In the case of plasma parameter adjustment, a support vector machine algorithm can be used to calculate a sequence of adjustment values ​​when the parameter adjustment range exceeds a preset threshold. The core of the support vector machine algorithm lies in constructing an optimal classification boundary to distinguish the influence range of different parameters and derive reasonable adjustment values. For example, in analyzing wire size and material differences, the system detects that a parameter deviates from the threshold by 20%. The support vector machine algorithm can generate a sequence of adjustment values ​​to gradually control the deviation to within 5%.

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

[0045] If the deviation between the calibration parameter set and the device state exceeds a preset threshold, a gradient descent algorithm can be used for optimization. The principle of the gradient descent algorithm is to iteratively adjust parameter values ​​to gradually approach the minimum value of the loss function, thereby optimizing the calibration parameters. For example, if the initial deviation of a calibration parameter is 10%, through multiple iterative adjustments, the deviation can be reduced to below 1%. This method can gradually approach the optimal solution when dealing with complex parameter optimization, improving calibration accuracy.

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

[0047] Comparative data analysis is crucial for obtaining real-time device response data and assessing calibration effectiveness. By comparing real-time data with expected values, we can assess whether the calibration has met expectations. For example, if the fluctuation range of a calibrated device parameter is within 2% compared to the preset standard of 3%, this indicates a good calibration.

[0048] If calibration fails to meet expectations, updating the dynamic calculation model becomes necessary. A feedback mechanism adjusts model parameters based on the calibration evaluation results to better reflect the actual operating environment. For example, suppose a model's initial prediction error for material differences is 8%. After updating through the feedback mechanism, this error can be reduced to 2%.

[0049] Step S105 includes the following steps: obtaining pre-calibrated parameter data, converting the calibration parameters into operating instructions through a preset interface, transmitting them to the plasma equipment control module, and driving the plasma equipment to start operation. When the plasma equipment is running, a real-time monitoring module is used to collect operating data from the equipment sensor to obtain an initial data set. The initial data set is removed from noise interference by a data cleaning tool to obtain a processed operating data group. If the parameter fluctuation value in the processed operating data group exceeds a preset threshold, a parameter adjustment mechanism is triggered to generate an adjustment instruction. The plasma equipment is driven to perform parameter correction through the adjustment instruction, and the corrected operating data is collected to obtain an updated data set. If the updated data set shows that the parameter stability does not meet the preset standard, the updated data set is feature extracted by a support vector machine algorithm to determine the key factors affecting stability. Based on the key factors, an optimized operating instruction is generated, transmitted to the equipment control module, the plasma equipment is driven to adjust the parameters, and the final operating data is collected to determine the stability of the wire surface treatment parameters.

[0050] Assume that before the device is started, the pre-calibrated parameter data includes a voltage value of 5000 volts and a gas flow rate of 10 liters per minute. These data are converted into specific control signals through a preset interface and transmitted to the device control module to ensure that the device is started according to the established parameters.

[0051] In a scenario where the adjustment mechanism is triggered when the parameter fluctuation value exceeds the preset threshold, assuming that the operating data group shows that the gas pressure fluctuation exceeds 5% of the allowable range, the system will automatically generate an adjustment instruction to reduce the gas input rate.

[0052] In the process of generating optimized operating instructions and transmitting them to the equipment control module, it is assumed that based on key factor analysis, the system generates instructions to increase the cooling power by 10%, and collects the final operating data in real time to determine whether the wire surface treatment parameters are stable. A closed-loop adjustment method is adopted.

[0053] Step S106 includes the following steps: obtaining equipment operation monitoring data, preprocessing the monitoring data through a data processing module, and obtaining a standardized data set. According to the standardized data set, a secondary detection process is executed to extract the characteristic parameters of the conductor surface and obtain surface characteristic data. Using the surface characteristic data, a support vector machine algorithm is used for classification processing to determine the surface state change characteristics and obtain state change information. If the state change information exceeds a preset threshold, the principal component analysis algorithm is used to extract the key change features and obtain a simplified change data set. For the simplified change data set, the deviation value from the preprocessing consistency standard is calculated to determine whether it meets the consistency standard and obtain a consistency assessment 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 via a state detection module. If the change information does not reach the preset threshold, the state detection module generates an initial state dataset and determines 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 and a priority order for parameter adjustment is determined. If the priority order meets preset conditions, the adjustment strategy is applied to subsequent processing via an automated system to obtain a new surface treatment parameter solution. The state detection module re-collects surface state change information and determines whether the re-collected change information reaches a preset threshold. If the re-collected change information still does not reach the preset threshold, the re-collected dataset is compared with the initial state dataset, and the differences are analyzed using a K-means clustering algorithm to obtain an optimized direction parameter set. Based on the optimized direction parameter set, the weights of the adaptive control algorithm are updated to generate a final surface treatment parameter solution, and the execution plan for subsequent processing is determined.

[0055] The core of the status detection module is to collect real-time data on microscopic changes in the conductor surface, such as surface roughness or oxide layer thickness, and compare it with preset thresholds, such as roughness not exceeding 2.5 microns, to determine whether further optimization is needed.

[0056] The gradient descent algorithm gradually adjusts control parameters, such as the current intensity or treatment time of the surface treatment equipment, to find the optimal parameter combination. For example, if the initial current intensity is 5 amps and the treatment time is 10 minutes, after multiple iterations, it might be adjusted to 4.5 amps and 12 minutes to better suit the actual surface requirements of the wire. This approach gradually approaches the optimal solution, ensuring the accuracy of parameter adjustments.

[0057] Prioritization can be determined based on the weight of the parameters' impact on surface treatment. For example, if current intensity contributes 60% to surface smoothness, while treatment time contributes 40%, current intensity adjustment would be prioritized. If the priority order meets pre-set criteria, such as current adjustment taking precedence over time adjustment, the automated system will adjust current parameters before time adjustment to ensure treatment stability. This approach targets the topic of recollecting surface condition change information and determining whether a threshold has been reached.

[0058] The state detection module can re-measure key indicators on the wire surface, such as whether the oxide layer thickness has dropped below 0.3 microns. If the threshold is still not reached, the data is compared with the initial state dataset to analyze the difference. For example, if the initial oxide layer thickness is 0.5 microns and the current thickness is 0.4 microns, it indicates that the optimization direction is correct but the magnitude is insufficient.

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

[0060] Step S107, according to the adjusted set of driving parameters, execute the configuration operation of the device driver module and update the operating status data of the device. Real-time information is extracted from the operating status data, and the real-time information is recorded by the data acquisition module to generate a structured status data set. With respect to the structured status data set, feature information related to the surface of the conductor is extracted to obtain a preliminary feature description of the surface of the conductor. If there are abnormal values ​​in the preliminary feature description, filtering is performed through a preset threshold to obtain a corrected feature description; if there are no abnormal values, the preliminary feature description is directly used as the corrected feature description. The support vector machine algorithm is used to classify the corrected feature description to determine the consistency measurement result of the conductor surface characteristics. Based on the consistency measurement result, the final evaluation data of the conductor surface characteristics is generated to complete the judgment of the degree of consistency of the characteristics.

[0061] For example, in a wire surface inspection scenario, the device driver module needs to adjust its operating frequency and detection accuracy based on new parameters. One possible implementation is to set the frequency in the driver parameters to 50Hz to accommodate the inspection requirements of specific wire materials, while also adjusting the detection accuracy to a 0.1mm error range to ensure that subtle surface variations are captured.

[0062] When extracting relevant wire surface feature information and generating a preliminary characterization, focus on two key indicators: surface roughness and texture distribution. Suppose, during an inspection, the roughness value is 2.5 microns, indicating uneven texture distribution. One possible approach is to quantify the texture distribution using image analysis techniques and generate a preliminary characterization report.

[0063] In the outlier filtering process, if the roughness value in the preliminary feature description suddenly jumps to 10 microns, which obviously exceeds the threshold of the normal range of 2.0-3.0 microns, the abnormal data can be filtered out by the preset threshold, and the corrected feature description will use 2.5 microns as the reference value.

[0064] When the modified feature descriptions are classified using a support vector machine algorithm, the conductor surface characteristics can be divided into two categories: uniform and non-uniform. Assuming that in a classification, 80% of the feature data is classified as uniform and the remaining 20% ​​as non-uniform, the system will generate a consistency metric result indicating a high degree of consistency. When generating the final evaluation data for the conductor surface characteristics, the consistency measurement results can be combined to produce a report containing the surface quality grade. Assuming a high degree of consistency, the evaluation data will rank the conductor surface quality as Grade 1, indicating that its characteristics meet production requirements. This evaluation method provides a clear reference for subsequent process adjustments and helps optimize the production process. The above examples and analysis demonstrate that every step, from equipment configuration to final evaluation, is closely aligned with the business needs of conductor surface inspection, ensuring data continuity and analysis reliability while providing a multi-dimensional reference for process improvement.

Claims

1. A plasma treatment device for wire surface insulation coating, characterized in that: The device comprises a device body (1), a support wheel (2) arranged in the device body (1) and supported on a wire, a low-temperature plasma generator (3) arranged in the device body (1), and induction mechanisms symmetrically arranged on both sides of the device body (1); a cleaning mechanism for cleaning the surface of the wire is provided at the front end of the device body (1); The cleaning mechanism comprises a mounting plate (4) arranged at the front end of the device body (1), 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) comprising a vertical portion and a horizontal portion, a brush (6) rotating on the horizontal portion being provided on the horizontal portion of the rotating frame (5), a staggered cross bar (7) being provided at one end of the inner side of the horizontal portion of the rotating frame (5), and a tension spring (8) being provided between the outer side of the rotating frame (5) and the mounting plate (4).

2. A plasma treatment device for wire surface insulation coating according to claim 1, characterized in that: The device body (1) comprises a central arc-shaped portion and inclined portions arranged at both ends of the arc-shaped portion.

3. A plasma treatment device for wire surface insulation coating according to claim 2, characterized in that: A counterweight (9) is provided at the lower end of the inclined portion of the device body (1).

4. The plasma treatment device for wire surface insulation coating according to claim 1, characterized in that: The sensing mechanism comprises an annular fixing plate (10) arranged at the end of the device body (1), and a plurality of industrial cameras (11) are evenly arranged in the annular fixing plate (10).

5. A plasma treatment device for wire surface insulation coating according to claim 4, characterized in that: The lower end of the annular fixing plate (10) is provided with an opening (12), and both ends of the opening (12) are provided with an outwardly inclined inclined plate (13).

6. A plasma treatment method for insulating the surface of a wire, using the device according to any one of claims 1 to 5, characterized in that: The following steps are involved: S101 collects wire surface signals through a sensor array to obtain initial characteristic distribution information; S102 determines the mapping relationship between wire surface characteristics and plasma parameters based on the initial characteristic distribution information and a pre-established discharge parameter model, and generates 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 to generate calibration parameter execution instructions; S105 drives the plasma equipment according to the calibration parameter execution instructions, obtains operating data, and determines the stability of the wire surface treatment parameters; S106 obtains wire surface state change information through secondary detection to determine whether the pretreatment consistency standard is met; S107 If the pretreatment consistency standard is not met, the adaptive control algorithm is optimized to generate a new parameter adjustment strategy, drive the equipment to update the operating state, and determine the consistency of the wire surface characteristics.

7. A plasma treatment method for wire surface insulation coating according to claim 6, characterized in that: Step S103 includes the following steps: An initial set of plasma parameters is obtained, and the parameter change trend is calculated to obtain a preliminary set of influence weights. Based on the preliminary set of influence weights, combined with changes in wire size 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 for iterative adjustment to obtain an optimized parameter set, calculate the final influence weight, and determine the optimal parameter adjustment range.

8. A plasma treatment method for wire surface insulation coating according to claim 6, 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 by the support vector machine algorithm to obtain an 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 by the gradient descent algorithm, an execution instruction sequence is generated, and transmitted to the device control module to obtain the calibration effect evaluation result.

9. A plasma treatment method for wire surface insulation coating according to claim 6, characterized in that: Step S107 includes the following steps: The surface state change information is obtained through the state detection module to determine whether the change information reaches a preset threshold. If the change information does not reach a preset threshold, the adaptive control algorithm is iteratively optimized using a gradient descent algorithm to obtain an updated control parameter set. A parameter adjustment strategy is generated based on the updated control parameter set, and a priority order of the parameter adjustment is determined. If the priority order meets the preset conditions, the adjustment strategy is applied through the automation system to obtain a new surface treatment parameter solution, and the surface state change information is re-collected for judgment.

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