Method for optimizing bare copper wire cold drawing process

Abstract

The application is suitable for the technical field of copper wire cold drawing process, and particularly relates to a bare copper wire cold drawing process optimization method, which comprises the following steps: obtaining dislocation density, drawing line speed and process vibration parameters of pass N; wherein the dislocation density is an index for measuring the internal plastic deformation capacity and strengthening degree of the bare copper wire, and the process vibration parameters comprise process vibration amplitude and process vibration frequency; determining a process state index of the pass N according to the dislocation density, the drawing line speed and the process vibration parameters of the pass N; determining a process flexibility coefficient of the pass N according to the process state index of the pass N; and optimizing the drawing parameters of the pass N based on the process flexibility coefficient of the pass N, and judging whether the pass N triggers annealing and optimizing annealing parameters based on the process flexibility coefficient of the pass N. The method can improve the precision and flexibility of the cold drawing process and adapt to the performance fluctuation of different materials.

Description

Technical Field

[0001] This application belongs to the field of copper wire cold drawing technology, and particularly relates to an optimization method for the cold drawing process of bare copper wire. Background Technology

[0002] Cold drawing of bare copper wire is a processing technique used to improve the mechanical properties and refine the dimensions of copper wire. This process involves stretching the copper wire through a series of dies at room temperature. Its main purpose is to increase the strength and hardness of the copper wire while improving its surface finish. Furthermore, cold drawing effectively controls the dimensional accuracy of the copper wire, meeting the stringent requirements of various applications.

[0003] In the existing technology, during the cold drawing process of bare copper wire, the material needs to go through multiple drawing passes. Since the process parameters set between different passes may not be completely matched with the changes in material state, it is easy to cause uneven mechanical properties during the processing. This not only affects the consistency of the finished product in a single pass, but may also accumulate deviations in subsequent processing passes, ultimately making it difficult to guarantee the overall performance of the product.

[0004] Traditional cold drawing process parameters are mostly set based on the operator's experience or historical process specifications. Although this can maintain basic process feasibility in a relatively stable production environment, this experience-based setting method is difficult to adapt to the differences in different drawing passes, which may lead to processing overload or underload, thereby reducing production efficiency or aggravating material fatigue damage.

[0005] In summary, during the cold drawing process of bare copper wire, there are problems such as the inability to accurately control the cold drawing process due to fluctuations in material properties and rigid setting of process parameters. Summary of the Invention

[0006] This application provides an optimization method for the cold drawing process of bare copper wire, which can solve the problem in related technologies where the cold drawing process of bare copper wire is difficult to control precisely due to fluctuations in material properties and rigid setting of process parameters.

[0007] In a first aspect, embodiments of this application provide an optimization method for the cold drawing process of bare copper wire, including:

[0008] Obtain the dislocation density, drawing speed, and process vibration parameters for pass N; wherein, the dislocation density is an indicator used to measure the plastic deformation capacity and strengthening degree inside the bare copper wire, and the process vibration parameters include the process vibration amplitude and the process vibration frequency.

[0009] Based on the dislocation density, drawing speed, and process vibration parameters of the Nth pass, determine the process status indicators of the Nth pass.

[0010] Based on the process status index of the Nth pass, determine the process compliance coefficient of the Nth pass.

[0011] Based on the process compliance coefficient of the Nth pass, the drawing parameters of the Nth pass are optimized, and based on the process compliance coefficient of the Nth pass, it is determined whether the Nth pass triggers annealing and the annealing parameters are optimized.

[0012] The technical solutions described in this application embodiment have at least the following technical effects:

[0013] The provided method for optimizing the cold drawing process of bare copper wire first obtains the dislocation density (an indicator of the internal plastic deformation capacity and strengthening degree of bare copper wire), drawing speed, and process vibration parameters (vibration amplitude and frequency) of pass N. Then, based on these parameters, the process state indicators for pass N are determined. Next, the process compliance coefficient for pass N is determined. Finally, based on the compliance coefficient, the drawing parameters for pass N are optimized, and the annealing parameters are optimized accordingly. This method allows for real-time adjustment of parameters during the drawing process, ensuring that the material deformation capacity and strengthening effect during cold drawing meet expectations. It helps reduce production problems caused by improper process parameter settings and improves product quality. Furthermore, this method can determine whether an annealing process is necessary and optimize annealing parameters based on the actual process state, thereby reducing quality fluctuations caused by insufficient or excessive annealing. This method effectively addresses material performance fluctuations, avoids defects caused by mechanical or material issues, and improves production reliability and consistency. Through flexible process adjustments, it also increases production efficiency and reduces rework rates and material waste. Furthermore, this method enhances the precision and flexibility of cold drawing processes, adapts to the performance fluctuations of different materials, and promotes process stability and controllability. It avoids the problem of inaccurate process control caused by material performance fluctuations or rigid process parameter settings.

[0014] Secondly, embodiments of this application provide an optimization device for the cold drawing process of bare copper wire, comprising:

[0015] The acquisition unit is used to acquire the dislocation density, drawing speed and process vibration parameters of pass N; wherein, the dislocation density is an indicator used to measure the plastic deformation capacity and strengthening degree inside the bare copper wire, and the process vibration parameters include the process vibration amplitude and the process vibration frequency.

[0016] The process condition index determination unit is used to determine the process condition index of the Nth pass based on the dislocation density, drawing speed and process vibration parameters of the Nth pass.

[0017] The process compliance coefficient determination unit is used to determine the process compliance coefficient of the Nth pass based on the process state index of the Nth pass.

[0018] The drawing parameter and annealing parameter optimization unit is used to optimize the drawing parameters of the Nth pass based on the process compliance coefficient of the Nth pass, and to determine whether the Nth pass triggers annealing and optimize the annealing parameters based on the process compliance coefficient of the Nth pass.

[0019] Thirdly, embodiments of this application provide a bare copper wire cold drawing process optimization device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method described in any of the embodiments of the first aspect.

[0020] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic flowchart of an embodiment of the optimized method for cold drawing of bare copper wire provided in this application;

[0023] Figure 2 This is a schematic diagram illustrating the implementation process of the optimized cold drawing process N in the bare copper wire cold drawing process optimization method provided in the embodiments of this application;

[0024] Figure 3 This is a schematic diagram of the structure of the bare copper wire cold drawing process optimization device provided in the embodiments of this application;

[0025] Figure 4 This is a schematic diagram of the structure of the bare copper wire cold drawing process optimization equipment provided in the embodiments of this application. Detailed Implementation

[0026] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0027] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0028] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0029] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0030] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0032] In related technologies, during the cold drawing process of bare copper wire, the material needs to undergo multiple drawing passes, each of which affects the microstructure and mechanical properties of the copper wire. Because the process parameters between different passes may not perfectly match the changes in material state, uneven mechanical properties during processing can easily occur. For example, tensile strength and elongation may fluctuate significantly between passes. This fluctuation not only affects the consistency of the finished product in a single pass but may also accumulate in subsequent passes, ultimately making it difficult to guarantee the overall performance of the product. In severe cases, it can even lead to quality accidents such as cracking and wire breakage. Furthermore, unstable product performance also creates adaptation difficulties for downstream processes such as stranding, coating, and electroplating, increasing quality control costs and reducing the overall competitiveness of the product.

[0033] Traditional cold drawing process parameters largely rely on operator experience or historical process specifications for setting. While this can maintain basic process feasibility in a relatively stable production environment, this experience-based approach lacks theoretical support and struggles to cope with changes in raw material conditions, equipment status, or environmental factors. Particularly in multi-pass drawing of bare copper wire, the degree of strain accumulation and material work hardening varies between passes, making it difficult for a single or uniform parameter setting to meet the actual needs of each pass. If process parameters fail to match the current material condition, it can lead to overload or underload, affecting processing efficiency and inducing fatigue damage, crack initiation, and decreased plasticity. More seriously, this process control model lacks portability and flexibility, often requiring re-experimentation when switching product types, changing drawing paths, or introducing new equipment. This increases development cycles and costs and limits the intelligent upgrading capabilities of the production line.

[0034] To address the aforementioned issues, this application provides a method for optimizing the cold drawing process of bare copper wire. This method first obtains the dislocation density (an indicator of the internal plastic deformation capacity and strengthening degree of the bare copper wire), drawing speed, and process vibration parameters (process vibration amplitude and frequency) of pass N. Then, based on the dislocation density, drawing speed, and process vibration parameters of pass N, the process state index of pass N is determined. Next, based on the process state index of pass N, the process compliance coefficient of pass N is determined. Finally, based on the process compliance coefficient of pass N, the drawing parameters of pass N are optimized, and based on the process compliance coefficient of pass N, it is determined whether annealing should be triggered for pass N and the annealing parameters are optimized. This method can adjust the parameters during the drawing process in real time, ensuring that the material deformation capacity and strengthening effect during cold drawing meet expectations. It helps reduce production problems caused by improper process parameter settings and improves product quality. This method can determine whether an annealing process needs to be triggered and optimize annealing parameters based on the actual process state, thereby reducing quality fluctuations caused by insufficient or excessive annealing. This method effectively addresses material performance fluctuations, avoids defects caused by mechanical or material issues, and improves production reliability and consistency. Through flexible process adjustments, it also increases production efficiency and reduces rework rates and material waste. Furthermore, this method enhances the precision and flexibility of cold drawing processes, adapts to the performance fluctuations of different materials, and promotes process stability and controllability. It avoids the problem of inaccurate process control caused by material performance fluctuations or rigid process parameter settings.

[0035] The bare copper wire cold drawing process optimization method provided in this application embodiment can be applied to bare copper wire cold drawing process optimization equipment. In this case, the bare copper wire cold drawing process optimization equipment is the execution subject of the bare copper wire cold drawing process optimization method provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of bare copper wire cold drawing process optimization equipment.

[0036] For example, the equipment for optimizing the cold drawing process of bare copper wire may include a drawing device, an annealing device, and a control device communicatively connected to the drawing device and the annealing device. The drawing device is a device capable of drawing bare copper wire to achieve a target diameter, and may include a single-die drawing machine, a multi-die drawing machine, a chain drawing machine, etc.; the annealing device is a device capable of heating the cold-drawn bare copper wire to restore its ductility, and may include a laser annealing device, a resistance annealing furnace, an atmosphere annealing furnace, etc.; the control device is a device capable of controlling the drawing device and the annealing device and performing data processing, such as a tablet computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, desktop computer, computing device or other processing device connected to a wireless modem, computer, laptop computer, customer premises equipment (CPE) and / or other devices for communication over wireless systems, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Networks (PLMNs), etc.

[0037] To better understand the bare copper wire cold drawing process optimization method provided in the embodiments of this application, the specific implementation process of the bare copper wire cold drawing process optimization method provided in the embodiments of this application will be described by way of example below.

[0038] Figure 1 This illustration shows a schematic flowchart of the bare copper wire cold drawing process optimization method provided in an embodiment of this application. The bare copper wire cold drawing process optimization method includes:

[0039] S100 obtains the dislocation density, drawing speed, and process vibration parameters for pass N. Dislocation density is an indicator used to measure the plastic deformation capacity and strengthening degree within the bare copper wire. Process vibration parameters include process vibration amplitude and process vibration frequency.

[0040] As is understandable, dislocation density is an important indicator for measuring the plastic deformation capacity and strengthening degree of a material. For bare copper wire, dislocation density reflects the number and distribution of dislocations during plastic deformation in the material during cold drawing. Dislocations are a type of crystal defect inside a metal. As the copper wire deforms during cold drawing, the number of dislocations gradually increases, thereby improving the strength and hardness of the material. However, excessively high dislocation density may lead to increased brittleness of the material.

[0041] For example, during the cold drawing process, the microstructure of the copper wire can be observed using microscopy techniques (such as scanning electron microscopy (SEM)) to calculate the dislocation density in the material; X-ray diffraction techniques can be used to estimate the dislocation density by the broadening of the diffraction peaks.

[0042] It is understandable that the drawing speed is the linear velocity of the bare copper wire along the drawing direction during the cold drawing process. It affects the material deformation rate and energy transfer efficiency during the cold drawing process and is directly related to the drawing force, drawing temperature and product quality.

[0043] For example, the drawing speed can be directly obtained through the control system of the drawing device. Modern drawing machines are equipped with sensors and feedback systems that can monitor and adjust the drawing speed in real time. The drawing speed of the bare copper wire can be monitored in real time by installing speed sensors (such as laser tachometers or encoders). The speed sensors can be installed on the drawing rollers of the drawing device to accurately capture the actual speed of the bare copper wire during the drawing process.

[0044] It can be understood that process vibration parameters refer to the vibration phenomena caused by the interaction between the drawing machine and the bare copper wire during the cold drawing process. Process vibration can include process vibration amplitude and process vibration frequency. Process vibration parameters directly affect the morphology, surface quality, and mechanical properties of the copper wire during the drawing process.

[0045] For example, vibration sensors (such as accelerometers and displacement sensors) can be installed at key locations in the drawing device (such as the drawing head and traction machine). These vibration sensors can accurately measure the amplitude and frequency of vibration. The vibration signals collected by the sensors can be analyzed using signal processing techniques (such as Fourier transform) to determine the amplitude and frequency of the vibration. The amplitude of the process vibration is its intensity, reflecting the fluctuation range of force during the drawing process; the vibration frequency reflects the periodic change of the vibration and may be related to factors such as the mechanical structure of the equipment and the physical properties of the copper wire.

[0046] This step allows for real-time monitoring of speed, mechanical properties, and vibration during the drawing process, ensuring optimal control over the plastic deformation capacity and strengthening effect of the bare copper wire, thereby effectively improving product quality.

[0047] S200, based on the dislocation density, drawing speed and process vibration parameters of pass N, determines the process status index of pass N.

[0048] As can be understood, process status indicators are a comprehensive quantitative reflection of various key parameters in the cold drawing process. These indicators can comprehensively describe the stability of the cold drawing process, the material's plastic deformation capacity, and the impact of vibration, helping production personnel assess whether the current process pass is in optimal condition and thus make necessary adjustments.

[0049] For example, data of different dimensions (dislocation density, drawing speed and process vibration parameters) can be normalized or standardized so that they have the same dimensional range in the calculation, avoiding calculation deviations caused by different units.

[0050] By analyzing the relationship between dislocation density and material strain using a model, we can determine the changes in dislocation density and calculate the plastic deformation (material strengthening coefficient) that occurs during the drawing process of bare copper wire. A higher dislocation density indicates a higher degree of strengthening of the material after deformation. The material strengthening coefficient reflects the change in material strength; that is, as dislocation density increases, the material's hardness and resistance to deformation also improve.

[0051] The stress changes during cold drawing can be calculated using a model that establishes the relationship between drawing speed and the stress-strain of the material. Drawing speed directly affects the stress distribution and deformation degree of the material; high-speed drawing may cause stress concentration on the material surface, leading to brittleness or fracture. The stress-strain model can help estimate stress changes at different drawing speeds, providing a basis for process optimization.

[0052] The amplitude and frequency of process vibrations can affect the deformation and quality of materials during cold drawing. The stability of the process (process stability coefficient) is assessed by analyzing the amplitude and frequency of process vibrations. Excessively high vibration amplitudes or unstable vibration frequencies may cause defects on the copper wire surface or affect the uniformity of the drawing process. The process stability coefficient reflects the impact of vibration on the process.

[0053] The material strengthening coefficient, stress variation, and process stability coefficient can be weighted and integrated to obtain a comprehensive process condition index. This index integrates the effects of dislocation density, drawing speed, and process vibration, and can comprehensively reflect the process condition of pass N, providing a basis for subsequent process optimization and adjustment.

[0054] In one possible implementation, S200, based on the dislocation density, drawing speed, and process vibration parameters of pass N, determines the process status indicators for pass N, including:

[0055] S210, determine the deformation resistance of pass N based on the dislocation density of pass N.

[0056] It is understandable that deformation resistance is the ability of a material to resist external forces during plastic deformation. It is closely related to dislocation density. An increase in dislocation density leads to an increase in the hardness and strength of the material, thereby improving deformation resistance.

[0057] For example, the deformation resistance of passage N can be calculated based on the Taylor dislocation strengthening model in mechanics of materials, according to the dislocation density of passage N. The Taylor dislocation strengthening model is as follows: ,in, Indicates resistance to deformation. Intrinsic yield strength (without dislocations) This represents the Taylor factor (determined by the crystal structure; approximately 3.06 for copper). This represents the dislocation interaction constant (an empirical value, ranging from 0.2 to 0.5). This indicates the shear modulus (approximately 42 GPa for copper). This represents the Burgers vector (copper is approximately 0.255 nm). This represents the dislocation density.

[0058] The relationship between deformation resistance and dislocation density can also be... ,in, This represents the initial resistance term of the material (which is related to factors such as the material's grain structure and solid solution strengthening). This represents the material constants related to dislocation multiplication and motion. It is an index related to factors such as material type and temperature, ranging from 1 to 2. , , It can be obtained through experimental data or literature based on factors such as the type of material (e.g., copper), the temperature of the production process, and the strain rate. If it is a specific cold-drawn copper wire, , , Fitting can be achieved using historical data or experiments.

[0059] This step allows for precise determination of the deformation resistance of bare copper wire based on dislocation density, thereby optimizing the cold drawing process and improving the stability and quality of the material during the cold drawing process.

[0060] S220, determine the vibration energy of pass N based on the process vibration parameters of pass N.

[0061] For example, the product of the process vibration amplitude and the process vibration frequency of pass N can be calculated as the vibration energy of pass N, i.e. ,in, Represents vibrational energy. Indicates the amplitude of process vibration. This indicates the frequency of vibration during the process. Higher vibration energy may indicate larger stress fluctuations during the cold drawing process, which may lead to defects, fatigue, and breakage on the surface of the copper wire; lower vibration energy may indicate less vibration during the cold drawing process, a more stable process, and better product quality.

[0062] S230, based on the deformation resistance, vibration energy and drawing speed of pass N, determines the process status index of pass N.

[0063] For example, deformation resistance and drawing speed directly reflect the deformation capacity of bare copper wire and the process's control over the material, determining the degree of plastic deformation and stress distribution of the copper wire during cold drawing. Formulas for calculating process condition indicators can be constructed. ,in, Indicates process status indicators, Indicates the drawing speed. It represents the deformation capacity and stress transmission rate of a bare copper wire during the drawing process per unit time. A higher value indicates better process stability, stronger material deformation capacity, and less impact from vibration. A lower value indicates that there is significant vibration or stress fluctuation during the cold drawing process, which may lead to surface defects in the copper wire.

[0064] Process status indicators can comprehensively reflect the deformation capacity, vibration impact, and drawing control effect of bare copper wires during cold drawing, providing an important basis for process optimization and helping to achieve an efficient and stable production process.

[0065] S300, based on the process status index of pass N, determine the process compliance coefficient of pass N.

[0066] As can be understood, the process compliance coefficient refers to the material and process system's ability to adapt to changes in process parameters (such as drawing speed and vibration) during the drawing process. A larger process compliance coefficient indicates stronger deformation capacity and adaptability of the material during drawing, making the process easier to adjust and control. Conversely, a lower process compliance coefficient indicates a more rigid process, poor material adaptability to changes in process parameters, and a higher likelihood of quality fluctuations.

[0067] For example, the process compliance coefficient can be obtained by modeling the elasticity and adaptability of the process system based on process state indicators. For instance, when the process state indicators of pass N indicate that the process is in a relatively rigid state (i.e., the process adaptability is poor), the process compliance coefficient will be low. Conversely, if the process state indicators show good adaptability (e.g., small stress changes, good process stability), then the process compliance coefficient will be high. The calculation model for the process compliance coefficient can be: ,in, Indicates the process compliance coefficient. Indicates the material strengthening coefficient. Indicates stress change, Indicates the process stability coefficient. , , These represent the weights corresponding to the material strengthening coefficient, stress variation, and process stability coefficient, respectively, and can be adjusted based on experimental data from actual processes. Indicates process status indicators, The system stiffness factor is a constant or an adjustment coefficient derived from experimental data, used to characterize the responsiveness of a process system to changes in process parameters. The process compliance coefficient for pass N can be calculated by substituting the process state indices of pass N into the calculation model.

[0068] In addition, since the process compliance coefficient emphasizes the flexibility of the process, it may have a nonlinear relationship with the process intensification coefficient, stress variation, and process stability coefficient. Therefore, nonlinear functions or regression models can be used to extract the process compliance coefficient. For example, .

[0069] This step determines the process compliance coefficient based on process status indicators and system response characteristics to optimize process parameters, thereby improving production stability and product quality. This step can also incorporate specific weighting models and nonlinear functions to derive the process compliance coefficient, providing a basis for decision-making regarding the optimization and adjustment of the Nth pass process.

[0070] In one possible implementation, S300 determines the process compliance coefficient of pass N based on the process status index of pass N, including:

[0071] S310, based on the basic flexibility coefficient, the process condition index of pass N, and the vibration energy, determine the process flexibility coefficient of pass N.

[0072] For example, the process compliance coefficient is a key parameter for measuring the adaptability and flexibility of cold drawing processes. It can be used to comprehensively evaluate the stability of the process by combining the material's deformation resistance, process conditions, and vibration energy. The calculation model for the process compliance coefficient can be... ,in, Indicates the process compliance coefficient. Represents the basic compliance coefficient, and represents the initial compliance coefficient of cold drawing. This represents the deformation sensitivity coefficient, reflecting the degree to which cold drawing is sensitive to deformation. This represents the vibration suppression coefficient, indicating the effect of vibration on process flexibility.

[0073] Basic compliance coefficient This is the initial value of the process compliance coefficient, representing the basic adaptability of the cold drawing process. It can be set initially by the production process or determined through historical data and empirical values. In practical applications, it can be a fixed constant or dynamically updated according to changes in the production process. For example, at the beginning of cold drawing, the basic compliance coefficient... It can be set as an initial value, the basic compliance coefficient during the cold drawing process. The value may be adjusted based on the actual drawing conditions, such as by automatically optimizing the value through real-time monitoring of process changes.

[0074] Deformation sensitivity coefficient The deformation sensitivity coefficient indicates the degree to which the process is sensitive to deformation and can be set as a constant (e.g., 0.3). Depending on the material properties, production conditions, and process equipment, it indicates how the material deformation affects the compliance coefficient during the process. It is the deformation compensation coefficient, which can compensate for deformation. When S is 1 (ideal state), the compensation coefficient is 1. It is used to indicate the degree of deviation from the ideal state.

[0075] Vibrational energy can be transmitted through The suppression of the exponential term indicates the negative impact of vibration energy on process compliance. The stronger the vibration, the lower the process compliance coefficient, thus affecting the stability of the production process.

[0076] The process compliance coefficient of pass N can be calculated by substituting the process condition index and vibration energy of pass N into the above calculation formula.

[0077] This step allows for precise quantification of the adaptability and flexibility of the cold drawing process. It not only considers the deformation characteristics of the material and the stability of the process, but also effectively suppresses the negative impact of vibration on the process. By calculating and adjusting the process compliance coefficient in real time, the cold drawing process can be optimized, which is beneficial to the efficiency and stability of the production process.

[0078] S400 optimizes the drawing parameters of pass N based on the process compliance coefficient of pass N, and determines whether pass N triggers annealing and optimizes the annealing parameters based on the process compliance coefficient of pass N.

[0079] For example, the goal of the optimization process is to improve production efficiency, reduce defect rate, and ensure process stability. When setting optimization goals, the optimization range can be determined based on the process compliance coefficient. With a high process compliance coefficient, higher drawing speeds or higher drawing forces can be allowed, while ensuring that the vibration amplitude is controlled within the allowable range to improve production efficiency. With a low process compliance coefficient, the optimization goal can be to maintain stability and avoid excessive process vibration or stress. This can be achieved by reducing the drawing speed or drawing force and adjusting vibration control to ensure process stability and quality.

[0080] Constraints can be determined based on process requirements and equipment limitations. For example, the maximum limit of drawing speed, the control range of vibration amplitude, and the tolerance for stress changes.

[0081] Suitable optimization algorithms can be selected: Genetic algorithms can simulate the natural selection process, randomly generate multiple candidate solutions (different combinations of drawing parameters), evaluate the performance of each solution through a fitness function, and iteratively generate better solutions; Particle Swarm Optimization (PSO) simulates the movement of multiple particles in the solution space to find the global optimum. In drawing parameter optimization, each particle represents a set of drawing parameters. The particles continuously adjust their positions to find the best combination of drawing linear velocity, vibration frequency, etc.; Simulated Annealing can simulate the physical annealing process. By randomly jumping to different solution space regions and gradually reducing the temperature, it finds the global optimum. In the process of drawing parameter optimization, it gradually reduces the probability of accepting poor solutions, thereby finally finding the best parameter combination.

[0082] Suppose we use Particle Swarm Optimization (PSO) to optimize drawing parameters. Each particle in the swarm represents a set of drawing parameters (such as drawing speed, drawing force, vibration frequency, etc.). If the process compliance coefficient of pass N is high, the PSO can search a wider range, and the optimization algorithm may suggest increasing the drawing speed or drawing force to improve efficiency without exceeding constraints. If the process compliance coefficient is low, the PSO will limit the range of parameter search to ensure adjustments are made within a reasonable process stability range, avoiding quality problems caused by drastic parameter adjustments.

[0083] After optimization, a set of optimized drawing parameters (such as drawing line speed, drawing force, vibration frequency, etc.) can be generated. The optimized drawing parameters will be input into the control system in real time for actual production, and the data during the drawing process will be monitored in real time. If the actual parameters are detected to deviate from the optimized values ​​(such as the drawing line speed being too fast or the vibration amplitude being too large), a warning can be issued and the corresponding parameters can be automatically adjusted to ensure the stability of the process.

[0084] By monitoring and optimizing in real time, the drawing parameters during the drawing process can be adjusted appropriately, thereby improving the stability of the process and the quality of the product, and avoiding quality problems caused by improper setting of process parameters.

[0085] It is understandable that annealing plays a crucial role in the cold drawing process, primarily used to eliminate internal stress in bare copper wires, reduce hardness, increase plasticity, and improve the overall properties of the material. Annealing parameters (the parameters of the annealing process) can include annealing temperature, annealing time, heating rate, etc., and these parameters can affect the material's grain structure, hardness, ductility, and other properties.

[0086] For example, whether annealing is needed can be determined by setting trigger conditions. For instance, a threshold for process compliance coefficient can be set, and the annealing process can be automatically triggered when the process compliance coefficient is lower than the threshold.

[0087] When it is determined that annealing is required for pass N, the annealing parameters for pass N can be optimized. The relationship between annealing temperature and process compliance coefficient can be calculated through regression analysis or empirical models. For example, the temperature adjustment range can be set to 600℃ to 900℃. If the process compliance coefficient is low, the annealing temperature can be increased to a higher temperature (such as 800℃) to ensure the annealing effect.

[0088] Historical data analysis, using methods such as curve fitting or linear regression, can determine the optimal match between annealing time and process compliance coefficient. For example, when the process compliance coefficient is low, the annealing time can be extended (e.g., from 20 minutes to 30 minutes) to ensure that internal stress is fully eliminated.

[0089] The annealing heating rate can be optimized based on thermodynamic models or historical data. An optimal heating rate (such as 2℃ / min) can be set, and the heating rate can be dynamically adjusted according to the process compliance coefficient to ensure temperature uniformity and uniform stress distribution.

[0090] Once the annealing parameters are optimized, the optimized annealing temperature, annealing time, and heating rate can be transmitted to the control system of the annealing apparatus, and the annealing process can be started. During the annealing process, if a large deviation between the actual temperature and the optimized annealing temperature is detected, the heating rate can be automatically adjusted or heating can be stopped to ensure that the temperature is within the ideal range. If the temperature changes too quickly or too slowly during the annealing process, the annealing time can be adjusted in real time to ensure that the internal stress can be completely eliminated.

[0091] The above methods enable precise control of the annealing process. When the process compliance coefficient is low, the annealing process is triggered to eliminate internal stress in the material and improve plasticity. By dynamically optimizing the annealing temperature, annealing time, and heating rate, the quality and stability of the material are guaranteed. This effectively improves the stability of the production process, reduces defects, and enhances the plasticity and ductility of the product, thereby achieving a high-efficiency and high-quality production process.

[0092] In one possible implementation, please refer to Figure 2 In step S400, based on the process compliance coefficient of pass N, the drawing parameters of pass N are optimized, including:

[0093] S410, based on the process compliance coefficient of pass N, calculate the compression ratio fluctuation of the next pass of pass N.

[0094] It is understandable that in the cold drawing process of bare copper wire, the compression ratio (i.e., the proportion of cross-sectional area reduction) is one of the key process parameters, directly affecting the degree of material deformation, mechanical properties, and the stability of subsequent processes. To enhance the adaptability and flexible adjustment capability of the process, a compression ratio fluctuation can be introduced, allowing the compression ratio of each pass to dynamically change according to the actual situation within the allowable range, thereby more precisely matching material properties and process conditions.

[0095] For example, the compression ratio fluctuation is used to determine the compression ratio fine-tuning range for the next pass (N+1) after pass N, and the expression can be: ,in, This indicates the amount of compression ratio fluctuation. This indicates the maximum allowable fluctuation reference factor (e.g., ±3%) set by the process, meaning that even at maximum compliance, the current compression ratio is allowed to fluctuate only slightly. The actual floating ratio is scaled by the process compliance coefficient of the current pass.

[0096] The sign of the compression rate fluctuation determines whether the compression should be increased or moderately reduced in the next pass (N+1). The direction of the fluctuation can be automatically determined based on dislocation density trends and other key process parameters. If the dislocation density is low or decreasing (indicating insufficient material strengthening and deformation), the compression rate fluctuation is positive (+), allowing for an increase in compression rate to enhance material deformation and strengthening. If the dislocation density is high or continuously increasing (indicating sufficient material hardening), the compression rate fluctuation is negative (-), allowing for a decrease in compression rate to avoid over-strengthening, material embrittlement, or wire breakage. Other auxiliary factors include high vibration energy in the current pass (reducing compression rate), high deformation resistance (reducing compression rate), and high drawing speed (reducing compression rate) to avoid wire breakage. The sign of the compression rate fluctuation can be determined by a logic judgment module or a simple decision tree.

[0097] Assuming the number of passes N =0.85, then according to the above formula, the compression ratio fluctuation of pass N+1 is: If the floating rate is determined to be positive, the compression rate fluctuation of pass N+1 is the base value plus 2.55%; if the floating rate is determined to be negative, the compression rate fluctuation of pass N+1 is the base value minus 2.55%. The base value is preset, that is, the drawing hole diameter of each pass in the drawing process is preset.

[0098] The compression ratio fluctuation can be used as feedback input to the drawing control system to control parameters such as the die design and linear speed setting for the next pass. At the same time, the actual effect of the adjustment can be evaluated in subsequent passes. If the effect is not ideal, the compression ratio fluctuation strategy can be further optimized (such as adjusting the upper limit of the fluctuation ratio or retraining the judgment model).

[0099] This step allows the compression ratio adjustment to become less rigid and more data-driven and intelligently floating, adapting to material conditions and actual working conditions, effectively improving the precision and robustness of the cold drawing process.

[0100] S420, based on the process compliance coefficient and reference vibration amplitude of pass N, calculate the auxiliary vibration amplitude of pass N. The auxiliary vibration amplitude is applied at the inlet of the drawing device, with the vibration direction at a 15° angle to the drawing direction. The drawing parameters include the compression ratio fluctuation of the next pass N and the auxiliary vibration amplitude of pass N.

[0101] It is understandable that the microscopic plastic deformation mechanism of the material directly affects its mechanical properties and drawing stability during the cold drawing process of bare copper wire. In order to further reduce deformation resistance, improve plasticity, and inhibit crack propagation, high-frequency micro-amplitude auxiliary vibration can be actively applied at the inlet of the drawing device to intervene in the deformation behavior of copper at the microscopic level, thereby achieving the ultrasonic vibration drawing effect. The auxiliary vibration can be actively applied by a vibrator, installed at the inlet of the drawing machine, with the vibration direction at a 15° angle to the drawing direction, so as to take into account both the transmission along the wire direction and the internal disturbance of the material.

[0102] Unlike passive process vibration parameters, auxiliary vibration is an active control variable that can apply amplitude and frequency, helping to reduce drawing force and improve drawing efficiency. In contrast, process vibration parameters are generated naturally by equipment operation and material response, are difficult to control, and reflect vibration interference in system operation. If they are too large, they will affect process stability. They can be suppressed, and process vibration parameters can be used to evaluate stability and trigger protection.

[0103] For example, the core logic for calculating the auxiliary vibration amplitude is to proportionally adjust the base vibration amplitude based on the process compliance coefficient of pass N, so that the vibration adapts to different process conditions and achieves personalized control. The formula for calculating the auxiliary vibration amplitude is as follows: ,in, Indicates the amplitude of the auxiliary vibration. Indicates the reference vibration amplitude (e.g., 3) ), representing the standard vibration amplitude applied under reference conditions. When A small value can increase the vibration amplitude to enhance the ultrasonic effect; when If the value is large, the vibration amplitude can be appropriately reduced to reduce energy consumption and equipment load.

[0104] Based on experience and experimental research, a standard reference vibration amplitude (baseline vibration amplitude) can be set. The reference vibration amplitude can be within the range of 3~5μm, and the reference vibration frequency can be controlled within the range of 20~40kHz. The range of reference vibration amplitude and reference vibration frequency can effectively activate the grain boundary slip mechanism of metallic materials, thereby reducing deformation resistance by about 15~20%, inhibiting microcrack propagation, increasing the material's reduction of area, and improving ductility.

[0105] This step can intelligently adjust the vibration intensity according to the real-time working conditions of the material (process compliance coefficient), actively stimulate grain boundary slip, reduce deformation resistance, and at the same time inhibit the propagation of microcracks and increase the reduction of area, thereby effectively improving the plastic deformation performance of copper wire and improving drawing stability and product quality.

[0106] In one possible implementation, please refer to Figure 2 In step S400, based on the process compliance coefficient of pass N, it is determined whether pass N triggers annealing and the annealing parameters are optimized, including:

[0107] S401, determine the trigger annealing threshold for pass N based on the reference annealing threshold, annealing coupling factor, and process compliance coefficient of pass N.

[0108] It is understandable that annealing is a crucial step in the cold drawing process of bare copper wire, as it regulates the material's microstructure, restores plasticity, and eliminates work hardening. To achieve precise control of the annealing process, a trigger annealing threshold can be set, which determines whether the material has reached the deformation limit requiring annealing. Traditional annealing thresholds are fixed values, applicable only to specific materials and ideal conditions, and cannot reflect the differences caused by fluctuations in process conditions during actual production. Introducing a process flexibility coefficient allows for dynamic adjustment of the trigger annealing threshold based on the actual deformation capacity and process flexibility of the current pass, enabling annealing strategies that adapt to changing working conditions.

[0109] For example, the dynamic adjustment expression for triggering the annealing threshold can be: ,in, This indicates the threshold for triggering annealing. This indicates the baseline annealing threshold (e.g., 0.15, corresponding to the initial safe deformation limit set for copper materials). This indicates the annealing coupling factor (adjusting the annealing trigger strength, taking into account factors such as material type, environment, and equipment, e.g., 1.0). This represents the compliance influence coefficient (the degree to which the compliance of the control process affects the annealing threshold, such as 0.2).

[0110] In the expression The term is a decreasing function, which physically means that the larger the process compliance coefficient, the weaker the annealing trigger threshold. High compliance indicates strong adaptability of the material and process, allowing it to withstand higher plastic deformation without compromising quality, thus enabling a delay in annealing. As a coefficient for adjusting the strength of the compliance influence, the compliance influence coefficient can be set to fine-tune the degree of influence of the process compliance coefficient on the trigger annealing threshold according to the material type or process requirements.

[0111] In actual production, different batches of materials, different annealing equipment, or different drawing conditions (such as wet and dry) have different requirements for annealing timing. In order to make the above expression more adaptable, an annealing coupling factor can be introduced.

[0112] The dynamic adjustment expression can be embedded in the industrial control system for online real-time judgment. It is suitable for automated annealing management strategies. It can dynamically determine the annealing trigger threshold for the current pass simply by updating the process compliance coefficient in real time.

[0113] The trigger annealing threshold obtained through this step can accurately reflect the current work hardening state and load-bearing capacity of the material, enabling personalized annealing strategies that vary depending on the process state. This effectively controls material performance fluctuations, improves plasticity recovery efficiency, and facilitates the continuity of the drawing process and the quality of the finished product.

[0114] S402, obtain the instantaneous residual strain of pass N, and determine whether the instantaneous residual strain of pass N is greater than or equal to the trigger annealing threshold of pass N, and obtain the judgment result of pass N.

[0115] It is understandable that in the production process of cold-drawn copper wire, instantaneous residual strain is a key indicator for measuring the degree of cumulative plastic deformation of the material at a certain moment, reflecting whether the material has a tendency to work harden. In order to achieve precise annealing control, the instantaneous residual strain of the current pass N can be compared with the trigger annealing threshold to determine whether the annealing conditions have been met, thereby dynamically controlling the annealing behavior.

[0116] For example, the instantaneous residual strain can be calculated by combining the actual compression ratio of pass N and the material stress-strain relationship, such as... ,in, Indicates instantaneous residual strain. This indicates the actual compression ratio.

[0117] A predictive model for residual strain can be established (such as a regression or neural network model based on pull-out force, linear velocity, temperature rise, and dislocation density). The instantaneous residual strain can be output by inputting real-time acquired data.

[0118] The instantaneous residual strain of pass N can be compared with the triggered annealing threshold of pass N to determine whether the annealing condition has been met. ≥ If the result indicates triggered annealing, it means the material has undergone significant work hardening and can immediately proceed to the annealing process; if < The judgment result indicates that annealing is not required, meaning the material still has sufficient plasticity and can continue cold drawing to the next pass. This judgment logic can be automatically executed by the conditional branch in the program, outputting a Boolean result (True / False), which can then be called by the drawing control system.

[0119] This step ensures a precise response to work hardening during the cold-drawn copper wire production process, effectively controls the annealing timing, avoids material performance degradation, and improves production pace and process flexibility.

[0120] S403, when the judgment result of pass N indicates that the instantaneous residual strain of pass N is less than the trigger annealing threshold of pass N, the drawing device is controlled to perform the next pass of drawing on the bare copper wire.

[0121] For example, when the judgment result is < Without annealing, this result can be fed back to the main control program as input for control command generation. After receiving the judgment result that annealing is not required, the drawing control system skips the annealing command process and calls the drawing parameter configuration for the next pass (N+1). This can include die (drawing device) size, drawing line speed, compression ratio adjustment range, auxiliary vibration settings, and the preset parameter file or optimized dynamic parameter group for this pass. The system can activate the drawing program for pass N+1, control the traction motor to start according to the set line speed, and the drawing device to perform metal deformation according to the set compression ratio. If there is an auxiliary vibration setting, the vibration excitation device can be turned on simultaneously, applying a preset amplitude and frequency (such as at a 15° angle to the drawing direction), and collecting key data such as dislocation density, drawing line speed, and process vibration parameters for the next pass in real time.

[0122] The closed-loop logic of this step ensures that the cold drawing system has adaptive capabilities and high response efficiency. That is, it can flexibly decide whether to skip annealing based on the actual state of the material, thereby optimizing the production line operation rhythm and energy consumption, and realizing intelligent and flexible production of cold-drawn copper wire.

[0123] S404: When the judgment result of pass N indicates that the instantaneous residual strain of pass N is greater than or equal to the trigger annealing threshold of pass N, the annealing laser energy of pass N is calculated based on the process compliance coefficient of pass N, and the annealing device is controlled to perform annealing on the bare copper wire based on the annealing laser energy of pass N. The annealing parameters include the trigger annealing threshold and the annealing laser energy.

[0124] For example, when the judgment result is ≥ When annealing is triggered, the system enters annealing mode, preparing to adjust the laser power and execute heating. The annealing laser energy can be calculated using the annealing laser energy calculation formula. ,in, Indicates the annealing laser energy. The reference laser energy (unit: J / cm² or W) can be set according to the material type and process. It is a monotonically increasing function, when The larger the value, the larger the overall denominator, and the lower the annealing laser energy, which conforms to the logic of "softness leads to gentler burning". The coefficient of 0.5 can be adjusted experimentally to control the sensitivity of the softness to energy adjustment.

[0125] Can The target laser energy is sent to the control unit of the laser annealing device. The laser adjusts the output power or pulse energy according to the target laser energy and applies heat treatment to the copper wire. The scanning speed and laser action time are controlled and adjusted synchronously to ensure that the copper wire per unit length receives uniform energy input. The temperature sensor feedback can be monitored at the same time to ensure that the annealing temperature (e.g., 400~600°C) is stable and to prevent overheating or insufficient annealing.

[0126] This step dynamically adjusts the annealing laser energy by combining the process compliance coefficient of pass N, achieving precise control and energy adaptation of the annealing process during copper wire processing. When the instantaneous residual strain reaches or exceeds the trigger annealing threshold, the required annealing laser energy is calculated based on the process compliance coefficient, and the laser device is controlled to perform on-demand annealing. This not only effectively eliminates work hardening and restores material plasticity, but also avoids grain coarsening or material overheating caused by excess energy, thereby improving annealing uniformity, reducing energy consumption fluctuations, and contributing to stable copper wire performance and consistent quality, significantly enhancing the intelligence and flexibility of the cold drawing process.

[0127] In one possible implementation, the optimization method for the cold drawing process of bare copper wire also includes:

[0128] S4001, obtain the final strain of track N.

[0129] For example, if annealing is not triggered in pass N, the final strain is the cumulative plastic strain of the copper wire after the drawing process of pass N ends, and the final strain of pass N can be calculated using the method in step S402.

[0130] If annealing has been triggered in pass N, the final strain can be regarded as the residual effective strain of the material after annealing (which can be zero or very small), or set as a fixed reference value (such as 0.02) according to the system definition.

[0131] S4002, based on the final strain of pass N, update the annealing coupling factor of the next pass N to obtain the updated annealing coupling factor.

[0132] For example, during the cold drawing process of bare copper wire, to achieve personalized, closed-loop adaptive annealing control, the annealing coupling factor in the annealing strategy can be dynamically updated. The annealing coupling factor affects the calculation of the annealing trigger threshold, thus determining the timing and frequency of annealing. The update process can be based on the final strain after N passes and follows an exponential decay formula: ,in, This represents the updated annealing coupling factor (the annealing coupling factor for pass N+1). This represents the annealing coupling factor for pass N. The final strain is represented by a constant of 0.10, which is the center value of the target strain range set empirically. If the final strain is close to 0.10, the annealing coupling factor remains basically unchanged. If the strain deviates more, the annealing coupling factor decreases exponentially, reducing the annealing threshold of the next pass and promoting early annealing.

[0133] The actual strain of copper wire reflects whether the material is within the ideal deformation range, and can be adjusted... The size of the value can be flexibly adjusted to change the level of the subsequent annealing trigger threshold, thereby forming a closed-loop control logic of process strain-annealing parameter-strain adjustment. The structure has mathematical properties such as monotonically decreasing, smooth continuity, and symmetrical convergence, which allows the annealing strategy to be slightly adjusted when the strain deviates slightly; when the deviation is serious, the annealing strategy is significantly tightened, which is in line with the control principle of actual process that the further away from the target, the more correction is needed.

[0134] This step enables the subsequent annealing strategy to be automatically adjusted according to the actual deformation, thereby precisely controlling the annealing rhythm, suppressing overheating or hardening accumulation, and significantly improving the adaptability of the cold drawing process and product consistency.

[0135] In addition to updating the annealing coupling factor, the basic compliance coefficient can also be updated. and vibration suppression coefficient (N+1) and Basic compliance coefficient The update formula can be ,in, This represents the updated basic compliance coefficient (for stage N+1). ), This represents the basic compliance coefficient for the number of passes, N. This indicates the product qualification rate or performance compliance rate after N passes. This indicates the expected target achievement rate (e.g., 95% or 98%). The basic compliance coefficient reflects the initial expectation of the ideal drawing environment and can be fine-tuned based on actual results to make it closer to the actual material performance and process stability.

[0136] The formula for updating the basic compliance coefficient introduces an adjustment factor (pass rate deviation) based on actual results, which reflects the closed-loop feedback concept. When the drawing quality is worse than expected, the deformation compensation weight in the calculation of the compliance coefficient of the next process can be indirectly increased by reducing the basic compliance coefficient, which prompts the system to control the degree of deformation and annealing behavior more conservatively, and effectively improves the stability and adaptability of quality control.

[0137] Vibration suppression coefficient The update formula can be ,in, This represents the updated vibration suppression coefficient (for N+1 passes). ), This represents the vibration suppression coefficient for track N. This represents the maximum vibration amplitude experienced by the copper wire in pass N. Vibration suppression is enhanced when the value exceeds 10 μm, and is upregulated for every 1 μm increase. Value 0.001 Increasing the value can amplify the weakening effect of vibration energy on compliance in the process compliance coefficient calculation model, thereby strengthening the vibration suppression weight.

[0138] During the cold drawing process of bare copper wire, high-amplitude vibrations can induce micro-cracks, die wear, and processing instability. If the value exceeds 10μm, it indicates the presence of adverse signs, and the adjustment should be increased. It can amplify the weight of vibration energy in the calculation of process compliance coefficient, thereby strengthening the suppression effect of vibration on process compliance. Essentially, it guides the system to avoid high vibration conditions and improves system robustness through feedback control of process compliance coefficient.

[0139] By adaptively updating the basic compliance coefficient and vibration suppression coefficient, the calculation model of the process compliance coefficient can be self-adjusted according to the actual drawing effect and process disturbance (vibration amplitude), realizing flexible parameter adjustment driven by quality feedback, enhancing the ability to quickly suppress unstable vibration behavior, and ensuring that the entire cold drawing process is more intelligent, personalized and stable.

[0140] In one possible implementation, the optimization method for the cold drawing process of bare copper wire also includes:

[0141] S10, based on the compression rate fluctuation of the next pass of pass N, determine the ideal drawing aperture of the next pass of pass N.

[0142] For example, the drawing compression ratio can be defined as ,in, Indicates the drawing compression ratio. This indicates the incoming diameter of track N+1 (i.e., the outgoing diameter of track N). This represents the lead diameter for pass N+1. The ideal lead diameter can be derived by using the drawing compression ratio standard. A compression ratio float can be introduced based on the standard definition of drawing compression ratio, so that the original design aperture (pre-set) can be adapted to the current actual process conditions. ,in, This indicates the ideal drawing orifice diameter (exit diameter) for pass N+1. This indicates the original drawing hole diameter for the N+1 pass (i.e., the outlet diameter of the drawing device before the floating adjustment). This represents the standard compression ratio for pass N+1 (e.g., 0.20 if the design target is 20%). Use Using it as a benchmark, without directly changing the original parameters, it is beneficial to keep each adjustment within a controlled range, which can give the system good continuity and stability and avoid sudden changes or fluctuations in the drawing quality.

[0143] The compression ratio fluctuation of N+1 passes can be substituted into the above. The calculation formula yields the ideal drawing orifice diameter for pass N+1, which will be used to control the exit diameter of the die for pass N+1 (or as a basis for die selection).

[0144] This step retains the controllability of the original design while introducing a flexible adaptive mechanism, making it an important step in realizing intelligent mold adjustment and improving the accuracy and stability of cold drawing.

[0145] S20, determine whether the die library contains the ideal drawing orifice diameter for the next pass N. The die library includes drawing devices with multiple drawing orifice diameters.

[0146] For example, the mold library interface can be called to query all mold (drawing device) specifications recorded in the mold library. The information stored in the mold library may include mold number (ID), wire outlet diameter (i.e., mold exit diameter), mold type, lifespan, wear condition, etc. The mold library can be a local database (such as SQLite), a list built into the PLC device, or a module in an industrial MES system.

[0147] You can compare the wire exit diameter in the mold library with the ideal drawing diameter to determine if there is a mold that meets the requirements.

[0148] S30, if it exists, call the drawing device corresponding to the ideal drawing hole diameter as the drawing device for the next pass N.

[0149] For example, if the judgment result in the previous step indicates that there is a drawing device in the mold library with the same drawing hole diameter as the ideal drawing hole diameter of pass N+1, the existence of the mold can be returned and the available mold number can be listed. If it is an automatic mold changing system, the control command can be sent to the robotic arm to control the robotic arm to complete the mold (drawing device) replacement of pass N+1 before the end of pass N; if it is a manual operation, the operator can be prompted to pick up the specified mold.

[0150] S40, if not found, select the drawing orifice closest to the ideal drawing orifice from the die library, and predict the process state index of the closest drawing orifice to obtain two predicted indices; compare the two predicted indices with the ideal process state index respectively, and take the drawing orifice corresponding to the predicted index that is closer to the ideal process state index as the actual drawing orifice of the next pass N; compensate for the error between the actual drawing orifice of the next pass N and the ideal drawing orifice. The closest drawing orifice includes both drawing orifices larger than the ideal drawing orifice and drawing orifices smaller than the ideal drawing orifice.

[0151] For example, the error between all the wire exit diameters (drawing diameters) in the mold library and the ideal drawing diameter can be calculated, and the two closest wire exit diameters can be selected, one slightly larger than the ideal drawing diameter and the other slightly smaller than the ideal drawing diameter.

[0152] Formula Calculate the compression ratio of each of the two outlet orifices. This refers to the exit hole diameter after N passes of drawing. The average deformation resistance of the two exit holes during the drawing process can be estimated using a material stress-strain model (such as the Hollomon or Voce model, or empirical formulas). ,in Indicates the material strengthening coefficient. The deformation resistance hardening index can be obtained from material databases or experimental fitting. The average deformation resistance of the two exit orifices can be substituted into the process condition index calculation formula to calculate the process condition index (predicted index) for the two exit orifices. The drawing speed and vibration energy in the formula can be the drawing speed and vibration energy of the Nth pass.

[0153] Ideal process state indicators (such as S=1.0) can be preset, and the difference between the two predicted indicators and the ideal process state indicators can be calculated. The output hole diameter corresponding to the predicted indicator with the smaller difference is taken as the actual drawing hole diameter of the N+1 pass.

[0154] The error value between the actual drawing hole diameter and the ideal drawing hole diameter can be calculated. Based on the error value, the reference compression ratio of the next pass of pass N+1 can be adjusted to adapt to the current error, or the adjustable process parameters such as the auxiliary vibration amplitude, annealing energy, and drawing speed of pass N+1 can be adjusted appropriately, or the error value can be recorded and accumulated into the subsequent mold design for adjustment.

[0155] This step enables the selection of an alternative mold through predictive modeling, multi-scheme comparison, and dynamic compensation when the ideal mold is missing. This achieves minimal deviation of process indicators, stability and consistency of the processing process, flexible system control, and controllable error compensation.

[0156] Optionally, S40, compensation is made for the error between the actual drawing aperture and the ideal drawing aperture in the next pass of pass N, including:

[0157] S41, calculate the aperture error ratio and aperture difference based on the actual drawing aperture and ideal drawing aperture of the next pass N.

[0158] For example, the ratio of the actual drawing aperture to the ideal drawing aperture for pass N+1 can be calculated, i.e. ,in, Indicates the aperture error ratio. Indicates the actual drawing hole diameter. This represents the ideal drawing orifice diameter. The difference between the actual drawing orifice diameter and the ideal drawing orifice diameter for pass N+1 can be calculated, i.e. , This represents the difference in aperture.

[0159] S42, based on the aperture error ratio, compensate for the reference vibration amplitude to obtain the compensated reference vibration amplitude.

[0160] For example, the reference vibration amplitude of track N can be compensated according to the compensation formula for the reference vibration amplitude to obtain the reference vibration amplitude of track N+1 (after compensation), which can be used as the auxiliary vibration amplitude of track N+1. Setting, i.e. ,in, This represents the compensated reference vibration amplitude (of track number N+1). ), This represents the reference vibration amplitude for track number N. This represents the sensitivity adjustment coefficient of the vibration amplitude to error, and its value can be between 0.5 and 1.5, adjusted according to process experience.

[0161] By adjusting the aperture error ratio through exponential mapping, the system can flexibly respond to strain changes caused by mold deviations, achieving the goal of flexible control. It can ensure that only fine-tuning is needed when the error is small, and a strong response is needed when the error is large, which makes it easy for the system to make progressive corrections based on process requirements.

[0162] This step, by introducing a power function compensation relationship between the aperture error ratio and the vibration amplitude, enables the system to have intelligent adaptive capability to mold selection errors, significantly improving the accuracy and flexibility of auxiliary vibration control during cold drawing.

[0163] S43, based on the aperture error ratio, the reference annealing threshold is compensated to obtain the compensated reference annealing threshold.

[0164] For example, the baseline annealing threshold of pass N can be compensated according to the compensation formula of the baseline annealing threshold to obtain the baseline annealing threshold of pass N+1 (after compensation), which can be used to calculate the trigger annealing threshold of pass N+1. ,Right now ,in, This represents the base annealing threshold after compensation (for pass N+1). ), This represents the baseline annealing threshold for pass N. The adjustment coefficient indicating the sensitivity of the annealing threshold to aperture error can be set empirically, such as 0.05.

[0165] Die aperture deviation can lead to strain deviation in each pass. The above compensation formula dynamically adjusts the reference annealing threshold through a linear compensation relationship, achieving flexible self-adaptation of the annealing threshold. This indicates the degree of deviation from the actual error, multiplied by a sensitivity coefficient. The subsequent increment is both directional and controllable. Even minute deviations in aperture during cold drawing can cause significant changes in residual strain; therefore, this compensation method helps ensure the rationality of annealing timing and the consistency of material properties.

[0166] S44, calculate the total compression ratio compensation for the subsequent M passes based on the aperture difference and the ideal drawing aperture.

[0167] For example, the compression ratio is essentially closely related to the inlet and outlet diameters. Die aperture errors directly cause strain shifts during drawing. A proportional correction method (the ratio between the aperture difference and the ideal drawing aperture) can be used to adjust and absorb these errors through subtle parameter adjustments during subsequent drawing processes, avoiding material damage caused by sudden changes. ,in, This represents the total compression ratio compensation. The coefficient 0.15 indicates that every 1% of the aperture error will cause an adjustment weight of approximately 15% in the compression ratio (which can be fitted based on process experience or historical regression). This means that the deformation (compression ratio) deviation caused by the drawing hole diameter error can be equally distributed in subsequent M passes, or weighted according to pass compliance and strain sensitivity, to achieve multi-pass dynamic compensation.

[0168] This step quantifies the drawing aperture error, transforms it into the compression ratio compensation requirement for the subsequent drawing process, and achieves closed-loop error control through linear correction.

[0169] In one possible implementation, the optimization method for the cold drawing process of bare copper wire also includes:

[0170] S101, Obtain the dislocation density, drawing speed, and process vibration parameters of the next pass of pass N, and determine the process status index; Based on the process status index of the next pass of pass N, determine the process compliance coefficient of the next pass of pass N; S102, Based on the process compliance coefficient of the next pass of pass N and the compensated reference vibration amplitude, calculate the auxiliary vibration amplitude of the next pass of pass N; S103, Based on the process compliance coefficient of the next pass of pass N, the compensated reference annealing threshold, and the updated annealing coupling factor, determine the trigger annealing threshold of the next pass of pass N.

[0171] For example, the dislocation density, drawing speed, and process vibration parameters of pass N+1 can be obtained using the method in step S100. The process condition index of pass N+1 can be calculated according to the process condition index calculation formula in step S230. The process compliance coefficient of pass N+1 can be calculated according to the process compliance coefficient calculation model in step S310. .

[0172] The auxiliary vibration amplitude of pass N+1 can be calculated based on the process compliance coefficient of pass N+1 and the compensated reference vibration amplitude. ,in, This represents the auxiliary vibration amplitude of pass N+1. The trigger annealing threshold for pass N+1 can be calculated based on the process compliance coefficient of pass N+1, the compensated reference annealing threshold, and the updated annealing coupling factor. ,in, This represents the trigger annealing threshold for stage N+1.

[0173] Through these steps, dynamic adaptive control of the next cold drawing process can be achieved, which can effectively address the control challenges caused by material property fluctuations and rigid process parameter settings, significantly improve drawing stability, plasticity control accuracy and energy efficiency, and promote the cold drawing process to a new stage of intelligent manufacturing with high precision, high toughness and flexibility.

[0174] In one possible implementation, the optimization method for the cold drawing process of bare copper wire also includes:

[0175] S1001, the total compression ratio compensation amount of the subsequent M passes is distributed to each of the subsequent M passes according to the exponential decay, so as to obtain the compression ratio compensation amount of each of the subsequent M passes.

[0176] For example, the total compression ratio compensation can be distributed exponentially to the subsequent M passes (e.g., M=3, representing N+2, N+3, N+4). This exponential decay ensures maximum compensation in the first pass, gradually decreasing thereafter, preventing risks such as uneven plasticity and microcrack formation caused by abrupt strain changes. Since stress and deformation transfer are delayed during the drawing process, earlier error correction is more effective; therefore, exponential distribution is a physically and technologically sound compensation path. For instance, the allocation method could be... ,in, The track number indicates the track number to be compensated, starting from 1 (i.e., N+2 is the first track to be compensated). Indicates the number of tracks The compression ratio compensation amount, with an exponential decay coefficient of 0.7, can be adjusted according to actual process requirements. The above allocation method can be used for each pass. The compression ratio compensation is calculated and added to the planned compression ratio of the corresponding track to achieve progressive error compensation.

[0177] For each of the subsequent M chutes:

[0178] S1002, calculate the compression ratio fluctuation of the current pass based on the process compliance coefficient of the previous pass.

[0179] For example, assuming M is 3, the subsequent M passes are passes N+2, N+3, and N+4. The compression ratio fluctuation of pass N+2 can be calculated based on the process compliance coefficient of pass N+1 and the compression ratio fluctuation calculation formula in step S410, and the compression ratio fluctuation of subsequent passes can be calculated in the same way.

[0180] S1003, based on the process status indicators of the current pass, determine the weights corresponding to the compression ratio fluctuation and compression ratio compensation of the current pass.

[0181] For example, weights can be calculated using an exponential function of the process status index to avoid abrupt weight changes, facilitate a smooth transition during process parameter adjustments, and improve stability. A significant deviation of the process status index from 1 in the exponential function indicates a substantial difference between the current state and the ideal state, allowing for priority error correction; conversely, a process status index close to 1 indicates a stable state, allowing for more flexible application of process strategies. The weight calculation method for the compression ratio compensation amount can be... ,in, This represents the weight of the compression ratio compensation amount. Since the sum of the weights corresponding to the compression ratio fluctuation and the compression ratio compensation amount is 1, the weight of the compression ratio fluctuation amount is... .

[0182] Based on the process status indicators of the current pass (pass N+2, pass N+3, pass N+4), the weights of the compression ratio fluctuation and compression ratio compensation for the current pass can be calculated using the above method.

[0183] S1004. Based on the compression rate fluctuation, compression rate compensation, and the corresponding weights of the compression rate fluctuation and compression rate compensation for the current track, determine the total compression rate for the current track.

[0184] For example, the total compression ratio of the current trace can be obtained by weighted summation of the compression ratio fluctuation and its weight, as well as the compression ratio compensation and its weight.

[0185] S1005, based on the total compression ratio of the current pass, determine the ideal drawing aperture for the current pass.

[0186] For example, the ideal drawing aperture for the current pass can be calculated using the ideal drawing aperture calculation method in step S10, based on the total compression ratio of the current pass.

[0187] Traditional cumulative compensation methods are prone to problems such as the continuous accumulation of compensation values, leading to control variable inflation; drastic fluctuations in compression ratio in subsequent passes, hindering stable control; and poor system controllability and robustness, easily resulting in complete loss of control due to a single error. The core idea of ​​the method described above is to create a separate compensation task for each error. These tasks exist independently, have a fixed lifespan, and only affect subsequent M passes, with no interference between tasks. This method achieves intelligent control effects such as local error isolation and dynamic adjustment of compression ratio, effectively solving problems such as cumulative error amplification, compensation loss of control, and process adjustment lag in traditional processes. It not only improves the accuracy and stability of the drawing path but also enhances the maintainability and robustness of the system.

[0188] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0189] Corresponding to the bare copper wire cold drawing process optimization method described in the above embodiments, this application also provides a bare copper wire cold drawing process optimization device, the various units of which can realize the various steps of the bare copper wire cold drawing process optimization method. Figure 3A structural block diagram of the bare copper wire cold drawing process optimization device provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0190] Reference Figure 3 The device includes:

[0191] The acquisition unit is used to acquire the dislocation density, drawing speed, and process vibration parameters for pass N. Dislocation density is an indicator used to measure the plastic deformation capacity and strengthening degree within the bare copper wire, while the process vibration parameters include the vibration amplitude and frequency.

[0192] The process condition index determination unit is used to determine the process condition index of pass N based on the dislocation density, drawing speed and process vibration parameters of pass N.

[0193] The process compliance coefficient determination unit is used to determine the process compliance coefficient of pass N based on the process status index of pass N.

[0194] The drawing parameter and annealing parameter optimization unit is used to optimize the drawing parameters of pass N based on the process compliance coefficient of pass N, and to determine whether pass N triggers annealing and optimize the annealing parameters based on the process compliance coefficient of pass N.

[0195] It should be noted that the information interaction and execution process between the above-mentioned units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0196] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0197] This application also provides an optimized equipment for the cold drawing process of bare copper wire. Figure 4This is a schematic diagram of the structure of a bare copper wire cold drawing process optimization device provided in one embodiment of this application. The bare copper wire cold drawing process optimization device includes a drawing device, an annealing device, and a control device communicatively connected to the drawing device and the annealing device. Figure 4 As shown, the control device 6 of the bare copper wire cold drawing process optimization equipment in this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown in the image), at least one memory 61 ( Figure 4 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the bare copper wire cold drawing process optimization equipment to implement the steps in any of the above embodiments of the bare copper wire cold drawing process optimization method, or causes the bare copper wire cold drawing process optimization equipment to implement the functions of each unit in the above embodiments of the apparatus.

[0198] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the control device 6 of the bare copper wire cold drawing process optimization equipment.

[0199] The control device 6 of the bare copper wire cold drawing process optimization equipment can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. This bare copper wire cold drawing process optimization equipment may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 4 This is merely an example of equipment for optimizing the cold drawing process of bare copper wire, and does not constitute a limitation on such equipment. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0200] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0201] In some embodiments, the memory 61 may be an internal storage unit of the control device 6 of the bare copper wire cold drawing process optimization equipment, such as a hard disk or memory of the bare copper wire cold drawing process optimization equipment. In other embodiments, the memory 61 may be an external storage device of the bare copper wire cold drawing process optimization equipment, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the bare copper wire cold drawing process optimization equipment. Further, the memory 61 may include both internal storage units and external storage devices of the bare copper wire cold drawing process optimization equipment. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0202] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0203] This application provides a computer program product that, when run on a bare copper wire cold drawing process optimization device, enables the bare copper wire cold drawing process optimization device to implement the steps in any of the above method embodiments.

[0204] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to bare copper wire cold drawing process optimization equipment, recording media, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0205] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0206] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0207] In the embodiments provided in this application, it should be understood that the disclosed bare copper wire cold drawing process optimization apparatus, equipment, and method can be implemented in other ways. For example, the embodiments of bare copper wire cold drawing process optimization apparatus and equipment described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, and may be electrical, mechanical, or other forms.

[0208] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0209] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An optimized method for cold drawing process of bare copper wire, characterized in that, include: Obtain the dislocation density, drawing speed, and process vibration parameters for pass N; wherein, the dislocation density is an indicator used to measure the plastic deformation capacity and strengthening degree inside the bare copper wire, and the process vibration parameters include the process vibration amplitude and the process vibration frequency. Based on the dislocation density, drawing speed, and process vibration parameters of the Nth pass, determine the process status indicators of the Nth pass. Based on the process status index of the Nth pass, determine the process compliance coefficient of the Nth pass. Based on the process compliance coefficient of the Nth pass, the drawing parameters of the Nth pass are optimized, and based on the process compliance coefficient of the Nth pass, it is determined whether the Nth pass triggers annealing and the annealing parameters are optimized. The step of determining the process state indicators of pass N based on the dislocation density, drawing speed, and process vibration parameters of pass N includes: Based on the dislocation density of the aforementioned pass N, the deformation resistance of the aforementioned pass N is calculated using the Taylor dislocation strengthening model; wherein, the Taylor dislocation strengthening model is... , For deformation resistance, The intrinsic yield strength without dislocations. Taylor factor, determined by crystal structure. For dislocation interaction constant, Shear modulus For Burgers vector, Dislocation density; Calculate the product between the process vibration amplitude and the process vibration frequency of the Nth pass, and determine the vibration energy of the Nth pass as the product between the process vibration amplitude and the process vibration frequency of the Nth pass. Based on the deformation resistance, vibration energy, and drawing speed of pass N, the process condition indicators of pass N are determined; wherein, the calculation formula for the process condition indicators is as follows: , For process status indicators, For the drawing speed, Vibrational energy; The step of determining the process compliance coefficient of pass N based on the process status index of pass N includes: The process compliance coefficient of pass N is determined based on the basic compliance coefficient, the process state index of pass N, and the vibration energy; wherein, the calculation model for the process compliance coefficient is as follows: , This is the process compliance coefficient. The basic compliance coefficient, The deformation sensitivity coefficient, This is the vibration suppression coefficient; The optimization of the drawing parameters for pass N based on the process compliance coefficient of pass N includes: Calculate the product between the process compliance coefficient of the pass N and the maximum allowable floating reference coefficient set by the process, and determine the compression ratio floating amount of the next pass N as the product between the process compliance coefficient of the pass N and the maximum allowable floating reference coefficient set by the process; wherein, the next pass N is pass N+1. Calculate the ratio between the reference vibration amplitude and the process compliance coefficient of the pass N, and determine the auxiliary vibration amplitude of the pass N as the ratio between the reference vibration amplitude and the process compliance coefficient of the pass N; wherein, the auxiliary vibration amplitude is applied at the inlet of the drawing device, the vibration direction is at a 15° angle with the drawing direction, and the drawing parameters include the compression ratio fluctuation of the pass N+1 and the auxiliary vibration amplitude of the pass N; The determination of whether annealing is triggered in pass N based on the process compliance coefficient of pass N and the optimization of annealing parameters include: Based on the baseline annealing threshold, the annealing coupling factor, and the process compliance coefficient of the pass N, the trigger annealing threshold for pass N is determined; wherein, the dynamic adjustment expression for the trigger annealing threshold is: , To trigger the annealing threshold, As the baseline annealing threshold, The annealing coupling factor. This is the coefficient for influence of flexibility. The instantaneous residual strain of the Nth pass is obtained, and it is determined whether the instantaneous residual strain of the Nth pass is greater than or equal to the trigger annealing threshold of the Nth pass, so as to obtain the determination result of the Nth pass. When the determination result of the Nth pass indicates that the instantaneous residual strain of the Nth pass is less than the trigger annealing threshold of the Nth pass, the drawing device is controlled to perform the N+1th pass of drawing on the bare copper wire. When the determination result of pass N indicates that the instantaneous residual strain of pass N is greater than or equal to the trigger annealing threshold of pass N, the annealing laser energy of pass N is calculated based on the process compliance coefficient of pass N, and the annealing device is controlled to perform annealing on the bare copper wire based on the annealing laser energy of pass N; wherein, the annealing parameters include the trigger annealing threshold and the annealing laser energy, and the formula for calculating the annealing laser energy is as follows: , For annealing laser energy, The reference laser energy is used.

2. The optimized method for cold drawing process of bare copper wire as described in claim 1, characterized in that, The method further includes: Obtain the final strain of the Nth pass; Based on the final strain of pass N, the annealing coupling factor of pass N+1 is updated using exponential decay to obtain the updated annealing coupling factor; wherein, the exponential decay formula is: , For the updated annealing coupling factor, The annealing coupling factor for the Nth pass is... The final strain of the Nth pass is given.

3. The optimized method for cold drawing process of bare copper wire as described in claim 2, characterized in that, The method further includes: Based on the compression ratio fluctuation of pass N+1, the ideal drawing orifice diameter of pass N+1 is determined; wherein, the formula for calculating the ideal drawing orifice diameter is as follows: , The ideal drawing aperture for the N+1 pass is... The drawing hole diameter is set for the N+1 draw pass. This is the compression ratio fluctuation for the N+1th pass. The standard compression ratio for the N+1th pass; Determine whether the ideal drawing orifice diameter for the next pass of the Nth pass exists in the die library; wherein, the die library includes drawing devices with multiple drawing orifice diameters; If it exists, the drawing device corresponding to the ideal drawing hole diameter is called as the drawing device for the next pass N. If not found, the drawing orifice closest to the ideal drawing orifice is selected from the mold library, and the process state index of the closest drawing orifice is predicted to obtain two predicted indices. The two predicted indices are compared with the ideal process state index, and the drawing orifice corresponding to the predicted index that is closer to the ideal process state index is taken as the actual drawing orifice of the next pass N. The error between the actual drawing orifice and the ideal drawing orifice of the next pass N is compensated. The closest drawing orifice includes drawing orifices larger than the ideal drawing orifice and drawing orifices smaller than the ideal drawing orifice.

4. The optimized method for cold drawing process of bare copper wire as described in claim 3, characterized in that, The compensation for the error between the actual drawing aperture and the ideal drawing aperture in the next pass of the Nth pass includes: Calculate the aperture error ratio and aperture difference based on the actual and ideal drawing aperture of the N+1 pass. The reference vibration amplitude is compensated based on the aperture error ratio to obtain the compensated reference vibration amplitude. Based on the aperture error ratio, the reference annealing threshold is compensated to obtain the compensated reference annealing threshold; Calculate the ratio between the aperture difference and the ideal drawing aperture, and calculate the ratio between the ratio and the compression ratio adjustment weight to obtain the total compression ratio compensation for the subsequent M passes of the N+1 pass.

5. The optimized method for cold drawing process of bare copper wire as described in claim 4, characterized in that, The method further includes: Obtain the dislocation density, drawing speed, and process vibration parameters of pass N+1. Based on the dislocation density of pass N+1, calculate the deformation resistance of pass N+1 using the Taylor dislocation strengthening model. Calculate the product of the process vibration amplitude and the process vibration frequency of pass N+1, and determine the vibration energy of pass N+1 as the process vibration energy of pass N+1. Based on the deformation resistance, vibration energy, and drawing speed of pass N+1, calculate the process state index of pass N+1 using the calculation formula of the process state index. The process vibration parameters of pass N+1 include the process vibration amplitude and the process vibration frequency. Based on the process status index of the N+1 pass, the basic compliance coefficient, and the vibration energy of the N+1 pass, the process compliance coefficient of the N+1 pass is calculated using the calculation model of the process compliance coefficient. Calculate the ratio between the compensated reference vibration amplitude and the process compliance coefficient of the N+1 pass, and determine the ratio between the compensated reference vibration amplitude and the process compliance coefficient of the N+1 pass as the auxiliary vibration amplitude of the N+1 pass. Based on the process compliance coefficient of the N+1 pass, the compensated baseline annealing threshold, and the updated annealing coupling factor, the trigger annealing threshold of the N+1 pass is calculated using the dynamic adjustment expression of the trigger annealing threshold.

6. The optimized method for cold drawing process of bare copper wire as described in claim 4, characterized in that, The method further includes: The total compression ratio compensation for the subsequent M passes is distributed to each of the subsequent M passes in an exponentially decaying manner to obtain the compression ratio compensation for each of the subsequent M passes. For each of the subsequent M passes: Calculate the product between the process compliance coefficient of the previous pass and the maximum allowable floating reference coefficient set by the process, and determine the compression ratio fluctuation of the current pass as the product between the process compliance coefficient of the previous pass and the maximum allowable floating reference coefficient set by the process. Based on the process status index of the current pass, the weight corresponding to the compression ratio compensation amount of the current pass is calculated using the exponential function of the process status index. The difference between the constant 1 and the weight corresponding to the compression ratio compensation amount of the current pass is then calculated to obtain the weight corresponding to the compression ratio fluctuation of the current pass. Wherein, the exponential function of the process status index is... , The weight of the compression ratio compensation amount; The compression ratio fluctuation, compression ratio compensation, and the corresponding weights of the compression ratio fluctuation and compression ratio compensation for the current stage are weighted and summed to obtain the total compression ratio for the current stage. Based on the total compression ratio of the current pass, the ideal drawing aperture of the current pass is calculated using the formula for calculating the ideal drawing aperture.

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