Optimization method of die setting coefficient for bare copper wire multi-pass drawing

Abstract

The application is suitable for the technical field of copper wire, and particularly relates to a die matching coefficient optimization method for multi-pass drawing of bare copper wire, which comprises the following steps: a coefficient offset and a coefficient reference difference are respectively determined through a die matching reference parameter and real-time production parameters and the die matching reference parameter and a preset die matching target parameter, so as to obtain a coefficient actual difference of each pass of the bare copper wire; the intermediate quantity of the die matching reference parameter is introduced, instead of directly obtaining the coefficient actual difference through the real-time production parameters and the preset die matching target parameter, so as to improve the accuracy of the coefficient actual difference; and finally, a die matching coefficient optimization scheme of the bare copper wire is obtained through the coefficient actual difference and a preset extension threshold value. Through the above method, the problem that the die matching coefficient optimization scheme obtained by directly using the calculation logic of the target die matching coefficient minus the actual die matching coefficient has deviation and cannot accurately achieve the die matching target can be solved.

Description

Technical Field

[0001] This application belongs to the field of copper wire technology, and in particular relates to a method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire. Background Technology

[0002] Bare copper wire is a core material in fields such as power transmission and electronic component connections, and its production quality directly affects the performance of end products. Multi-pass drawing is a key process in bare copper wire forming, using multiple sets of dies to gradually reduce the copper wire diameter to obtain finished copper wire that meets specifications. Properly setting the die matching coefficient is a crucial prerequisite for ensuring stable drawing processes and qualified finished products; its accuracy directly affects the stability of the drawing force, the surface finish of the copper wire, its mechanical properties, and production efficiency.

[0003] Traditional techniques, when the mold matching baseline parameters cannot meet the preset mold matching target parameters, do not take into account the deviation between real-time production parameters and mold matching baseline parameters, or the deviation between mold matching baseline parameters and preset mold matching target parameters, to make corrections. Instead, they directly use the calculation logic of subtracting the actual mold matching coefficient from the target mold matching coefficient, which leads to deviations in the obtained mold matching coefficient optimization scheme and makes it impossible to accurately achieve the mold matching target. Summary of the Invention

[0004] This application provides a method for optimizing the die matching coefficient for multi-pass drawing of bare copper wires. This method can solve the problem that the calculation logic of directly subtracting the actual die matching coefficient from the target die matching coefficient leads to deviations in the optimized die matching coefficient scheme and fails to accurately achieve the die matching target.

[0005] In a first aspect, embodiments of this application provide a method for optimizing the die matching coefficient for multi-pass drawing of bare copper wires, including: Based on the die matching reference parameters and real-time production parameters for each pass of the bare copper wire, the coefficient offset for each pass of the bare copper wire is obtained; wherein, the die matching reference parameters refer to the reference elongation coefficient after the standard die production is determined for each pass; the real-time production parameters reflect the actual elongation coefficient of the bare copper wire for each pass; the coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions. Based on the die matching reference parameters and the preset die matching target parameters for each pass of the bare copper wire, the coefficient reference difference for each pass of the bare copper wire is obtained; wherein, the preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing; the coefficient reference difference reflects the inherent gap between the die matching reference parameters and the preset die matching target parameters under standard working conditions. Based on the coefficient offset and the coefficient reference difference, the actual coefficient difference for each pass of the bare copper wire is obtained; wherein, the actual coefficient difference represents the magnitude of the extension coefficient that needs to be adjusted to achieve the preset mold matching target parameters under the real-time production parameters; Based on the actual difference of the coefficients and the preset extension threshold, the optimization scheme of the mold coefficient of the bare copper wire is obtained.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The die matching coefficient optimization method for multi-pass drawing of bare copper wire provided in this application embodiment obtains the coefficient offset of each pass of the bare copper wire based on the die matching reference parameters and real-time production parameters. The die matching reference parameters refer to the reference elongation coefficient after the standard die production is established for each pass; the real-time production parameters reflect the actual elongation coefficient of the bare copper wire in each pass; the coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions; based on the die matching reference parameters and preset die matching target parameters for each pass of the bare copper wire, the following is obtained: The coefficient reference difference for each pass of the bare copper wire drawing; wherein, the preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing; the coefficient reference difference reflects the inherent difference between the die matching reference parameters and the preset die matching target parameters under standard working conditions; based on the coefficient offset and the coefficient reference difference, the actual coefficient difference for each pass of the bare copper wire drawing is obtained; wherein, the actual coefficient difference represents the elongation coefficient that needs to be adjusted to achieve the preset die matching target parameters under the real-time production parameters; based on the actual coefficient difference and the preset elongation threshold, the die matching coefficient optimization scheme for the bare copper wire drawing is obtained. This application determines the coefficient offset and the coefficient reference difference by using the die matching reference parameters and real-time production parameters, as well as the die matching reference parameters and the preset die matching target parameters, respectively, thereby obtaining the actual coefficient difference for each pass of the bare copper wire drawing. It introduces the intermediate quantity of the die matching reference parameters, instead of directly obtaining the actual coefficient difference through real-time production parameters and the preset die matching target parameters, thus improving the accuracy of the actual coefficient difference. Finally, based on the actual coefficient difference and the preset elongation threshold, the die matching coefficient optimization scheme for the bare copper wire drawing is obtained. The above method can solve the problem that the calculation logic of directly subtracting the actual mold matching coefficient from the target mold matching coefficient leads to deviations in the obtained mold matching coefficient optimization scheme, making it impossible to accurately achieve the mold matching target.

[0007] In a second aspect, embodiments of this application provide a die matching coefficient optimization system applied to electronic devices, used to implement the die matching coefficient optimization method for multi-pass drawing of bare copper wire as described in any of the first aspects above, the die matching coefficient optimization system comprising: The acquisition unit is used to obtain the coefficient offset of each pass of the bare copper wire based on the die matching reference parameters and real-time production parameters; wherein, the die matching reference parameters refer to the reference elongation coefficient after the standard die production is determined for each pass; the real-time production parameters reflect the actual elongation coefficient of the bare copper wire in each pass; and the coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions. A reference unit is used to obtain the coefficient reference difference for each pass of the bare copper wire based on the die matching reference parameters and the preset die matching target parameters for each pass; wherein, the preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing; the coefficient reference difference reflects the inherent gap between the die matching reference parameters and the preset die matching target parameters under standard working conditions. The actual unit is used to obtain the actual coefficient difference of each pass of the bare copper wire based on the coefficient offset and the coefficient reference difference; wherein, the actual coefficient difference represents the magnitude of the extension coefficient that needs to be adjusted to achieve the preset mold matching target parameters under the real-time production parameters; The optimization unit is used to obtain an optimization scheme for the matching coefficient of the bare copper wire based on the actual difference of the coefficient and the preset extension threshold.

[0008] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any of the foregoing aspects.

[0009] Fourthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to perform the method described in any one of the first aspects above.

[0010] It is understood that the beneficial effects of the second to fourth 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

[0011] 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.

[0012] Figure 1 This is a flowchart illustrating a method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire provided in an embodiment of this application. Figure 2This is a schematic diagram illustrating the operation of a method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of the model matching coefficient optimization system provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0013] 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.

[0014] 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.

[0015] 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.

[0016] 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]."

[0017] 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.

[0018] 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.

[0019] In related technologies, when the mold matching baseline parameters cannot meet the preset mold matching target parameters, corrections are not made based on the actual deviation from the mold and the deviation between the mold and the target. Instead, the calculation logic of directly subtracting the actual mold matching coefficient from the target mold matching coefficient is used. This results in a deviation in the optimized mold matching coefficient scheme, which cannot accurately achieve the mold matching target. Simply calculating the difference between the mold and the target also fails to accurately achieve the mold matching target.

[0020] To address the aforementioned issues, this application provides a method for optimizing die matching coefficients in multi-pass drawing of bare copper wire. This method includes obtaining the coefficient offset for each pass of the bare copper wire drawing process based on die matching reference parameters and real-time production parameters. The die matching reference parameters refer to the reference elongation coefficient after standard die production for each pass. The real-time production parameters reflect the actual elongation coefficient of the bare copper wire in each pass. The coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions. Based on the die matching reference parameters and preset die matching target parameters for each pass of the bare copper wire drawing process, the coefficients for each pass are obtained. The reference difference; wherein, the preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing; the reference difference of the coefficient reflects the inherent difference between the die matching reference parameters and the preset die matching target parameters under standard working conditions; based on the coefficient offset and the reference difference of the coefficient, the actual difference of the coefficient for each pass of the bare copper wire is obtained; wherein, the actual difference of the coefficient represents the elongation coefficient that needs to be adjusted to achieve the preset die matching target parameters under the real-time production parameters; based on the actual difference of the coefficient and the preset elongation threshold, the die matching coefficient optimization scheme for the bare copper wire is obtained. This application determines the coefficient offset and the reference difference of the coefficient by using the die matching reference parameters and real-time production parameters, as well as the die matching reference parameters and the preset die matching target parameters, respectively, thereby obtaining the actual difference of the coefficient for each pass of the bare copper wire. It introduces the intermediate quantity of the die matching reference parameters, instead of directly obtaining the actual difference of the coefficient through real-time production parameters and preset die matching target parameters, thereby improving the accuracy of the actual difference of the coefficient. Finally, the die matching coefficient optimization scheme for the bare copper wire is obtained through the actual difference of the coefficient and the preset elongation threshold. The above method can solve the problem that the calculation logic of directly subtracting the actual mold matching coefficient from the target mold matching coefficient leads to deviations in the obtained mold matching coefficient optimization scheme, making it impossible to accurately achieve the mold matching target.

[0021] The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire provided in this application embodiment can be applied to electronic devices. In this case, the electronic device is the executing entity of the method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0022] For example, electronic devices can be industrial control computers, edge computing gateways, production scheduling servers, cloud servers, industrial tablets, or intelligent scheduling terminals. Electronic devices include memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the methods described in any of the foregoing aspects.

[0023] To better understand the die matching coefficient optimization method for multi-pass drawing of bare copper wire provided in the embodiments of this application, the specific implementation process of the die matching coefficient optimization method for multi-pass drawing of bare copper wire provided in the embodiments of this application will be described by way of example below.

[0024] Figure 1 A flowchart illustrating the method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire provided in an embodiment of this application is shown. Figure 2 The diagram illustrates the operation of a die matching coefficient optimization method for multi-pass drawing of bare copper wire provided in this application embodiment. The die matching coefficient optimization method for multi-pass drawing of bare copper wire includes: S100, based on the die matching reference parameters and real-time production parameters for each pass of the bare copper wire, obtains the coefficient offset for each pass. The die matching reference parameters refer to the reference elongation coefficient after the standard die production is established for each pass. The real-time production parameters reflect the actual elongation coefficient of the bare copper wire in each pass. The coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions.

[0025] It can be understood that the die matching reference parameters are the reference elongation coefficients set for each pass of the standard die under standard operating conditions, serving as the theoretical reference for the drawing process. Real-time production parameters are the actual elongation coefficients monitored during the drawing process for each pass, reflecting the true state of the current operating conditions. The coefficient offset is the difference between the actual elongation coefficient and the reference elongation coefficient, quantifying the degree of deviation between the real-time operating conditions and the standard operating conditions. For example, assuming the die matching reference parameter (reference elongation coefficient) for the third pass of a certain specification of bare copper wire is 1.25, and the actual elongation coefficient (real-time production parameter) for the third pass is calculated to be 1.22 through real-time monitoring by a diameter sensor, then the coefficient offset is 1.22 - 1.25 = -0.03, clearly reflecting the deviation of the actual elongation coefficient from the reference value by 0.03, providing data support for subsequent process adjustments.

[0026] It should be noted that the elongation factor, also known as the die matching factor, is a core process parameter for single-pass drawing, defined as the ratio of the cross-sectional area of ​​the copper wire before and after a single-pass drawing. ,in, For the cross-sectional area of ​​the die, For the demolding cross-sectional area, (where is the elongation coefficient), the total elongation coefficient of multi-pass drawing is the product of the elongation coefficients of each pass.

[0027] As an optional embodiment of this application, in step S100, the coefficient offset of each pass of the bare copper wire is obtained based on the die matching reference parameters and real-time production parameters, including: S110, based on the mold production instructions for each pass of the bare copper wire, obtain the mold matching reference parameters.

[0028] It's understandable that the mold manufacturing manual is a technical document accompanying the mold upon delivery, containing key parameters such as mold-compatible materials, bore diameter, recommended operating conditions, and baseline elongation coefficient. The mold matching baseline parameter is a baseline value for the elongation coefficient set based on the mold's characteristics, serving as the basis for subsequent deviation calculations and process optimization. For example, the manufacturing manual for a certain specification of bare copper wire used in the third drawing process clearly states that the baseline elongation coefficient for the compatible bare copper wire is 1.25. The processor can directly extract the baseline elongation coefficient from the manual as the mold matching baseline parameter for the third drawing process, ensuring the standardization and accuracy of the parameter source.

[0029] S120: Based on the real-time cross-sectional area values ​​of each pass of the bare copper wire, determine the real-time production parameters. The real-time production parameters represent the ratio of the real-time cross-sectional area value of the previous pass to the real-time cross-sectional area value of the next pass.

[0030] It can be understood that the real-time cross-sectional area value is the actual cross-sectional area data collected during the drawing process of the bare copper wire entering and exiting the die in each pass. It is the core original basis for calculating the actual elongation coefficient. The real-time production parameter, namely the actual elongation coefficient (die matching coefficient) of each pass, is calculated by directly comparing the real-time cross-sectional area values ​​before and after drawing in a single pass. It can accurately reflect the actual deformation degree and execution status of the current pass drawing process. Among them, the real-time cross-sectional area before entering the die is the actual cross-sectional area of ​​the bare copper wire before entering the die in the current pass, and the real-time cross-sectional area after exiting the die is the actual cross-sectional area of ​​the bare copper wire after being drawn by the die in the current pass. The calculation of the real-time production parameter strictly follows the definition of "the ratio of the real-time cross-sectional area before entering the die to the real-time cross-sectional area after exiting the die", and the calculation formula is as follows: ,(in, For real-time production parameters, For the real-time cross-sectional area of ​​the die, The calculation formula (based on the real-time cross-sectional area at the die exit) closely matches the original definition of the elongation coefficient, resulting in higher data accuracy. For example, in the third drawing of a certain specification of bare copper wire, the monitoring equipment collected data showing that the real-time cross-sectional area at the die entry was 3.066 mm², and the real-time cross-sectional area at the die exit was 2.513 mm². Substituting these values ​​into the formula, the real-time production parameter μ is calculated as μ = 3.066 ÷ 2.513 ≈ 1.22.

[0031] S130, based on the mold matching reference parameters and real-time production parameters, obtains the coefficient offset of each pass of the bare copper wire.

[0032] It can be understood that the die-fitting baseline parameter is a theoretical reference value, while the real-time production parameter is the actual monitored value. The difference between the two is used to calculate the coefficient offset, thus quantifying the deviation between the baseline extension coefficient and the actual extension coefficient. For example, if the die-fitting baseline parameter for the third pass is known to be 1.25, and the real-time production parameter calculated through diameter monitoring is 1.22, then using the formula "coefficient offset = real-time production parameter - die-fitting baseline parameter", the coefficient offset for the third pass is calculated to be 1.22 - 1.25 = -0.03, accurately quantifying the degree of deviation between the current working condition and the standard working condition.

[0033] By employing steps S110 to S130, it is possible to achieve standardized extraction of mold matching baseline parameters, accurate calculation of real-time production parameters, and scientific quantification of coefficient offsets, providing real and reliable deviation data for subsequent process optimization. At the same time, the clear breakdown of steps ensures the traceability of parameter acquisition and calculation at each step, avoiding deviations caused by non-standard parameter sources or confused calculation logic, and improving the overall accuracy of process optimization.

[0034] S200, based on the die matching reference parameters and preset die matching target parameters for each pass of the bare copper wire, obtains the coefficient reference difference value for each pass of the bare copper wire. The preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing. The coefficient reference difference value reflects the inherent difference between the die matching reference parameters and the preset die matching target parameters under standard operating conditions.

[0035] It can be understood that the die matching baseline parameter is the theoretical elongation coefficient baseline of the standard die. The preset die matching target parameter is the target elongation coefficient value set for each pass based on the quality requirements of the finished copper wire (such as diameter accuracy and mechanical properties). The coefficient baseline difference is the inherent difference between the two under standard operating conditions, and does not involve real-time operating condition fluctuations; it only reflects the difference between the theoretical baseline and the target requirement. For example, if the die matching baseline parameter for the 3rd pass is 1.25, and considering the finished copper wire diameter accuracy requirements, the preset die matching target parameter (the elongation coefficient to be achieved) set for the 3rd pass is 1.23, then the coefficient baseline difference is 1.25 - 1.23 = 0.02. This clearly reflects the inherent difference that the baseline value is 0.02 higher than the target value under standard operating conditions, providing a basis for subsequent adjustments based on real-time deviations.

[0036] As an optional embodiment of this application, S200, based on the matching reference parameters of each pass of the bare copper wire and the preset matching target parameters, obtains the coefficient reference difference value of each pass of the bare copper wire, including: S210, obtain the reference features corresponding to the reference parameters of each pass and the target features corresponding to the preset target parameters of the pass.

[0037] It can be understood that baseline characteristics are low-frequency stable characteristics strongly correlated with the die-matching baseline parameters. These refer to characteristics with low frequency of change and small fluctuations, such as the inherent properties of the die and stable parameters under standard operating conditions, like die hardness and the average standard drawing speed. Target characteristics are high-frequency target characteristics strongly correlated with the preset die-matching target parameters. These refer to characteristics that are highly targeted and adjusted according to production needs, such as finished product quality requirements and dynamic control targets, like target drawing force and target temperature. For example, the baseline characteristics corresponding to the die-matching baseline parameter 1.25 for the third pass are low-frequency stable characteristics such as the die hardness (280HB) and the average standard drawing speed (15m / s) for the third pass. These characteristics do not change with slight fluctuations in real-time operating conditions. The target characteristics corresponding to the preset die-matching target parameter 1.23 are high-frequency target characteristics such as the target drawing force (80kN) and target temperature (60℃) to be achieved in the third pass. These characteristics need to be dynamically adjusted according to the finished product requirements.

[0038] S220, Based on the baseline features and target features, a first combined feature is generated. The first combined feature is used to characterize the degree of correlation between the mold matching baseline parameters and the preset mold matching target parameters.

[0039] It is understandable that the baseline features provide stable theoretical reference information, while the target features provide precise target-oriented information. The first combined feature is a composite feature formed by fusing the two types of features. It can comprehensively characterize the correlation between the mold matching baseline parameters and the preset mold matching target parameters, eliminating the influence of the one-sidedness of single feature information. For example, by fusing the baseline features (hardness 280HB, speed 15m / s) and the target features (tensile force 80kN, temperature 60℃), the first combined feature is generated. The first combined feature can simultaneously reflect the correlation between "inherent mold properties and standard working conditions" and "target control parameters and finished product requirements," thereby accurately reflecting the intrinsic correlation between the mold matching baseline parameter 1.25 and the target parameter 1.23, providing comprehensive feature support for subsequent difference calculations.

[0040] In one possible implementation, S220, based on the baseline features and the target features, generates a first combined feature, including: S221, preprocess the baseline features and target features respectively to obtain the baseline feature vector and the target feature vector.

[0041] It's understandable that the baseline and target features are raw feature data, which may have issues such as inconsistent dimensions and large differences in numerical ranges. Preprocessing refers to cleaning, normalizing, and dimensionality matching of the raw features to eliminate data interference. The baseline and target feature vectors are fixed-length one-dimensional vectors formed after preprocessing, facilitating subsequent weighted fusion and model calculation. For example, after cleaning and normalizing the baseline features (hardness 280HB, speed 15m / s) and target features (tensile force 80kN, temperature 60℃), they are converted into fixed-length one-dimensional vectors, such as the baseline feature vector [0.82, 0.75] and the target feature vector [0.78, 0.80], laying the foundation for subsequent feature fusion.

[0042] For example, in S221, the baseline features and target features are preprocessed separately to obtain the baseline feature vector and the target feature vector, including: S2211, Feature cleaning process, removes outlier data from the baseline and target features.

[0043] It is understandable that during the acquisition process, baseline and target features may generate abnormal data due to factors such as sensor malfunctions and environmental interference. This data deviates from the reasonable range and does not conform to the process logic. Feature cleaning is the operation of removing such abnormal data to ensure that the feature data in subsequent processing is true and valid. For example, if the mold hardness data in the third pass baseline feature is 350 HB (far exceeding the reasonable range of 260-290 HB for molds) and the tensile force data in the target feature is 120 kN (exceeding the target range of 60-90 kN), then these two data points are determined to be abnormal and removed. Only valid data such as hardness 280 HB and tensile force 80 kN are retained to avoid abnormal data affecting the accuracy of subsequent calculations.

[0044] S2212, normalize the cleaned baseline features and target features respectively to obtain the original baseline feature values ​​and the original target feature values.

[0045] It's understandable that the cleaned features are the original features after removing outliers, but their numerical units and ranges differ significantly (e.g., hardness is in HB, speed is in m / s), making direct fusion impossible. Normalization is the operation of mapping feature data of different dimensions and ranges to a unified interval (e.g., [0,1]). The original baseline feature values ​​and the original target feature values ​​are the feature data obtained after normalization, eliminating the influence of differences in numerical ranges. For example, for the cleaned baseline features (hardness 280HB, speed 15m / s), mapping them to the [0,1] interval using the formula yields original baseline feature values ​​of 0.82 (hardness) and 0.75 (speed). After normalization, the target features (tensile force 80kN, temperature 60℃) yield original target feature values ​​of 0.78 (tensile force) and 0.80 (temperature), making the two types of features fusionable.

[0046] S2213, perform dimension matching on the normalized original baseline feature values ​​and the original target feature values ​​to obtain effective baseline features and effective target features.

[0047] It's understandable that standardized feature values ​​are normalized feature data, which may lead to inconsistencies between the baseline and target feature dimensions (e.g., the baseline feature has 2 dimensions, and the target feature has 3 dimensions). Dimension matching is an operation that makes the dimensions of the two types of features consistent by removing redundant dimensions and adding key dimensions. Valid baseline features and valid target features are the feature data obtained after dimension matching. For example, if the baseline features have 2 dimensions after normalization (hardness, speed), and the target features have 3 dimensions (tensile force, temperature, roughness), then removing the "roughness" dimension from the target features, which has extremely low correlation with the elongation coefficient, will result in both having 2 dimensions, yielding valid baseline features (hardness 0.82, speed 0.75) and valid target features (tensile force 0.78, temperature 0.80).

[0048] S2214 converts the effective baseline features and effective target features, after cleaning, standardization, and dimensional unification, into fixed-length one-dimensional vectors to obtain the baseline feature vector and the target feature vector.

[0049] It is understandable that effective baseline features and effective target features are cleaned, normalized, and dimension-matched feature data, which need to be converted into vector form to adapt to subsequent weighted fusion and model calculation. Fixed-length one-dimensional vectors are a vector format that meets the calculation requirements, with the length consistent with the feature dimension. For example, effective baseline features (hardness 0.82, speed 0.75) are converted into a one-dimensional vector [0.82, 0.75] as the baseline feature vector. Effective target features (tensile force 0.78, temperature 0.80) are converted into a one-dimensional vector [0.78, 0.80] as the target feature vector, both with a length of 2 and consistent dimension.

[0050] By adopting the above steps S2211 to S2214, it is helpful to systematically optimize the quality of feature data: feature cleaning removes abnormal interference, normalization eliminates differences in numerical range, dimension matching solves data adaptation problems, vector transformation adapts to subsequent calculations, and multi-step collaboration makes the feature data more authentic, consistent and usable, thereby improving the accuracy of process optimization from the source.

[0051] S222: Based on the historical drawing process patterns of bare copper wire, the initial weights of the baseline and target features are determined. Among them, the features with higher correlation to the elongation coefficient have higher weights.

[0052] It is understandable that historical drawing process patterns are accumulated process data and experience summaries from past copper wire drawing production, reflecting the correlation between characteristics and elongation coefficients. Initial weights are importance coefficients assigned to each characteristic based on the correlation between the characteristic and the elongation coefficient; the higher the correlation, the greater the weight, and the more dominant the characteristic. For example, based on historical drawing data statistics, the correlation between die hardness and elongation coefficient is 0.8 (high correlation), and the correlation between drawing speed and elongation coefficient is 0.5 (moderate correlation). The correlation between target tensile force and elongation coefficient is 0.7 (high correlation), and the correlation between temperature and elongation coefficient is 0.4 (moderate correlation). Therefore, the baseline characteristic weights are set as follows: hardness 0.6, speed 0.4. The target characteristic weights are: tensile force 0.7, temperature 0.3, highlighting the influence of highly correlated characteristics.

[0053] S223, the preprocessed baseline feature vector and target feature vector are weighted and fused according to the initial weights, and the fused combined feature vector is output.

[0054] It can be understood that the baseline feature vector and the target feature vector are preprocessed vector data, and the initial weights are the importance coefficients of each feature. Weighted fusion calculates the vector elements according to their weights to generate a combined feature vector that comprehensively reflects the differences in importance between the two types of features. For example, the baseline feature vector [0.82, 0.75] is calculated with weights of 0.6 and 0.4 to be 0.82×0.6+0.75×0.4=0.792. The target feature vector [0.78, 0.80] is calculated with weights of 0.7 and 0.3 to be 0.78×0.7+0.80×0.3=0.786. The fused combined feature vector is [0.792, 0.786], which comprehensively reflects the core information of the two types of features.

[0055] S224, perform validity verification on the fused combined feature vector. If the variance of the combined feature vector is within the preset effective threshold range, the combined feature vector is used as the first combined feature.

[0056] It is understandable that variance is an indicator of the dispersion of elements in a combined feature vector, reflecting the stability of feature fusion. The preset effective threshold is a reasonable variance range set according to process requirements, used to judge the effectiveness of the fused features. The first combined feature is the fused feature vector that has passed the validity check and can be used for subsequent difference calculations. For example, if the preset effective threshold is 0.001-0.01, the variance of the combined feature vector [0.792, 0.786] is calculated to be 0.000018, which is far below the lower limit of the threshold, indicating that the feature fusion is stable and the data fluctuation is small. Therefore, the combined feature vector is used as the first combined feature.

[0057] By adopting the above steps S221 to S224, it is helpful to achieve accurate feature fusion and effective control: preprocessing improves the data quality of the benchmark feature and the target feature, weight setting highlights the influence of key features, weighted fusion integrates the two types of feature information, effectiveness verification eliminates unstable fusion results, and finally generates a high-quality first combined feature, improving the calculation accuracy of the first combined feature.

[0058] S230, the first combined features are input into the difference calculation model to obtain the initial difference features for each passage. Here, the difference calculation model represents a machine learning model that takes the first combined features as input and the initial difference features as output. The initial difference features are candidate differences matched by the difference calculation model.

[0059] It is understandable that the first combined feature is a high-quality fused feature obtained after multiple processing steps, providing input for difference calculation. Please refer to Table 1. The difference calculation model is a pre-trained machine learning model. Its core function is to output the initial difference feature corresponding to the first combined feature based on the input first combined feature. For example, if the first combined feature [0.792, 0.786] of the third pass is input into the machine learning model, the model, based on the training results, outputs the initial difference feature of the third pass as 0.020, providing support for accurately determining the baseline difference of the coefficients.

[0060] Table 1 S240, analyzes the initial difference characteristics to obtain the coefficient benchmark difference for each pass.

[0061] It can be understood that the initial difference feature is the candidate difference value output by the difference calculation model, which is the original reference data for the coefficient benchmark difference. Analytical processing involves validity verification and deviation correction operations performed on the initial difference feature, aiming to eliminate model prediction errors and adapt to actual process constraints. The coefficient benchmark difference is the final difference value obtained after analytical processing, accurately reflecting the inherent gap between the mold matching benchmark parameters and the preset mold matching target parameters under standard operating conditions. For example, taking the third pass as an example, the initial difference feature output by the difference calculation model is 0.020. First, the initial difference feature is verified against process constraints. The reasonable range for the preset coefficient benchmark difference is [-0.03, 0.03]. 0.020 is within the reasonable range and is determined to be valid data; that is, 0.02 is the coefficient benchmark difference for the third pass.

[0062] By employing the steps S210 to S240 described above, it is possible to accurately calculate the coefficient benchmark difference: feature extraction and fusion provide a comprehensive basis for the difference calculation, and multi-step collaboration eliminates the deviation caused by single calculation and data interference, so that the coefficient benchmark difference can truly reflect the inherent gap between the benchmark parameter and the target parameter under standard working conditions.

[0063] S300, based on the coefficient offset and the coefficient baseline difference, obtains the actual coefficient difference for each pass of the bare copper wire. The actual coefficient difference represents the amount of extension coefficient that needs to be adjusted to achieve the preset mold matching target parameters under real-time production parameters.

[0064] It can be understood that the coefficient offset quantifies the deviation between real-time operating conditions and standard operating conditions, the coefficient benchmark difference quantifies the inherent gap between the benchmark and the target under standard operating conditions, and the actual coefficient difference is the comprehensive result of the two. Specifically, it represents the magnitude of the extension coefficient that needs to be adjusted to achieve the preset mold matching target parameter under the current real-time production parameters, and is the core basis for process optimization. For example, if the coefficient offset of the 3rd pass is -0.03 (actually 0.03 lower than the benchmark), and the coefficient benchmark difference is 0.02 (benchmark 0.02 higher than the target), the actual coefficient difference can be calculated as -(0.02+(-0.03)) = 0.01 (actually 0.01 lower than the target) using the formula "actual coefficient difference = -(coefficient benchmark difference + coefficient offset)". This means that the real-time production parameters of the 3rd pass need to be increased by 0.01 to achieve the preset mold matching target parameter of 1.23.

[0065] As an optional embodiment of this application, in step S300, the actual difference in coefficients for each pass of the bare copper wire is obtained based on the coefficient offset and the coefficient reference difference, including: S310, determine the first offset coefficient sequence based on the coefficient offset of each pass of the bare copper line.

[0066] It can be understood that the coefficient offset is a quantified value of the working condition deviation of a single pass. The first offset coefficient sequence is an ordered set formed by arranging the coefficient offsets of each pass in the drawing order, which can reflect the working condition deviation of each pass in the entire process. For example, bare copper wire has a total of 5 passes, and the coefficient offsets of each pass are -0.01, -0.02, -0.03, -0.02, and -0.01, respectively. Arranged in the order of passes 1 to 5, it forms the first offset coefficient sequence [-0.01, -0.02, -0.03, -0.02, -0.01]. Overall, it shows a pattern that the deviation is larger in the middle passes and smaller in the first and last passes.

[0067] S320, based on the coefficient reference difference of each pass of the bare copper line, obtains the second offset coefficient sequence.

[0068] It can be understood that the coefficient benchmark difference is the quantified value of the theoretical inherent gap of a single track, while the second offset coefficient sequence is an ordered set formed by arranging the coefficient benchmark differences of each track in the order of pull-out, which can reflect the inherent difference between the theoretical benchmark and the target of each track in the entire process. For example, the coefficient benchmark differences of the 5 tracks are 0.01, 0.015, 0.02, 0.015, and 0.01, respectively. Arranged in the order of tracks 1 to 5, they form the second offset coefficient sequence [0.01, 0.015, 0.02, 0.015, 0.01], which shows the distribution characteristic of larger inherent gaps in the middle tracks.

[0069] S330, based on the first offset coefficient sequence and the second offset coefficient sequence, obtain the actual difference of coefficients for each pass of the bare copper wire.

[0070] It is understandable that the first sequence reflects the deviation of the entire process operating conditions, while the second sequence reflects the inherent theoretical gap of the entire process. By calculating the corresponding pass data, the actual difference of the coefficients for each pass in the entire process can be obtained, thus gaining an overall understanding of the magnitude of the extension coefficients that need to be adjusted for the entire process. For example, by adding the corresponding pass data of the first sequence [-0.01,-0.02,-0.03,-0.02,-0.01] and the second sequence [0.01,0.015,0.02,0.015,0.01] and taking the negative value, the actual difference of the coefficients for the 5 passes is obtained as 0.00, 0.005, 0.01, 0.005, and 0.00, respectively, and the actual difference of the coefficient for the 3rd pass is 0.01, thus achieving overall data coordination for the entire process.

[0071] By employing steps S310 to S330, it is possible to achieve a comprehensive calculation of the actual difference in coefficients across the entire process: transforming single-pass parameters into an ordered sequence facilitates the overall analysis and corresponding calculations of the entire process conditions, avoiding the isolation of single-pass calculations. Simultaneously, through serialization, key passes with significant deviations can be quickly located, improving the efficiency and targeting of the entire process optimization.

[0072] In one possible implementation, S330, based on the first offset coefficient sequence and the second offset coefficient sequence, obtains the actual difference in coefficients for each pass of the bare copper wire, including: S331, perform trace alignment processing on the first offset coefficient sequence and the second offset coefficient sequence to form an aligned double sequence group.

[0073] It is understandable that track alignment is an operation that precisely matches each element in two sequences with its corresponding track number, avoiding calculation errors caused by disordered order. A double-sequence set is a set of one-to-one corresponding data pairs formed after alignment. Each data pair contains the operating condition deviation and theoretical inherent gap for the corresponding track, providing precisely matched data for subsequent calculations. For example, the first sequence [-0.01,-0.02,-0.03,-0.02,-0.01] and the second sequence [0.01,0.015,0.02,0.015,0.01] are matched one-to-one with tracks 1 to 5, forming a double-sequence set [(-0.01,0.01),(-0.02,0.015),(-0.03,0.02),(-0.02,0.015),(-0.01,0.01)], ensuring a precise correspondence of the two parameters for each track.

[0074] S332, the rationality of the double sequence group and the preset process constraints is judged to obtain the actual difference sequence of the initial coefficients.

[0075] It is understandable that the preset process constraints are reasonable ranges for the actual differences of coefficients set based on the copper wire material, equipment performance, and quality requirements. Differences exceeding these ranges may lead to production failures or quality problems. The initial sequence of actual coefficient differences is the set of differences obtained after calculating the corresponding data of the double sequence group. Its rationality needs to be verified by the process constraints. For example, if the preset process constraint is that the actual difference of coefficients ∈ [-0.02, 0.02], after adding the corresponding pass data of the double sequence group and taking the negative value, the initial sequence of actual coefficient differences is obtained as [0.00, 0.005, 0.01, 0.005, 0.00]. All data are within the constraint range and do not need to be eliminated, so the process can proceed directly to the next step.

[0076] S333 processes the initial coefficient actual difference sequence to obtain the coefficient actual difference for each pass.

[0077] It is understandable that although the initial coefficient difference sequence passes the rationality check, it may still contain minor data fluctuations, requiring further processing. Processing operations typically include smoothing and extreme value removal, aiming to eliminate fluctuations and obtain final coefficient differences that better reflect actual production needs. For example, smoothing the initial sequence [0.00, 0.005, 0.01, 0.005, 0.00] eliminates minor fluctuations, ultimately yielding the actual coefficient differences for each pass, with the third pass still showing 0.01, maintaining data consistency and stability.

[0078] By adopting the above steps S331 to S333, the accuracy and reliability of the actual difference calculation of the coefficients can be improved: the pass alignment ensures that the data matches correctly, the process constraint verification eliminates unreasonable differences, the smoothing process eliminates data fluctuations, and the multi-step collaborative optimization of the difference results can ultimately reflect the adjustment requirements of each pass in a true and accurate manner.

[0079] S400: Based on the actual difference in coefficients and the preset extension threshold, an optimization scheme for the matching coefficient of bare copper wires is obtained.

[0080] It is understandable that the actual difference in coefficients represents the magnitude of the extension coefficient that needs to be adjusted for each pass, and is the core basis for optimization. The preset extension threshold is a critical adjustment range set based on process stability and quality requirements, divided into an upper and lower threshold. Optimization is required if the threshold is exceeded; otherwise, the existing process is maintained. The die matching coefficient optimization scheme is a plan for adjusting the extension coefficient and optimizing related parameters for passes that exceed the threshold. For example, if the preset extension threshold is [-0.015, 0.015], and the actual difference in coefficients for the 3rd pass is 0.01, which is within the threshold range, no adjustment is needed. If the actual difference in coefficients for a certain pass is 0.02 (exceeding the upper limit), then an optimization scheme for generating the die matching coefficient is required.

[0081] As an optional embodiment of this application, in step S400, an optimization scheme for the bare copper wire matching coefficient is obtained based on the actual difference in coefficients and a preset extension threshold, including... S410, when the actual difference in coefficients is greater than the upper limit of the preset extension threshold or less than the lower limit of the preset extension threshold, a modulus adjustment amount is generated. The modulus adjustment amount represents the absolute value of the actual difference in coefficients plus the adjustment direction.

[0082] It is understandable that the upper and lower limits of the preset extension threshold are the critical values ​​for process adjustment. If the actual difference in the coefficient exceeds the upper or lower limit, it indicates that the existing process cannot meet the target requirements, and an adjustment amount for the mold matching coefficient needs to be generated. The adjustment amount of the mold matching coefficient is the extension coefficient value that needs to be adjusted to bring the actual difference in the coefficient back to the target range. Its absolute value is positively correlated with the absolute value of the actual difference in the coefficient, that is, the larger the difference, the larger the adjustment amount, and the more accurately it returns to the target range. For example, if the preset extension threshold has an upper limit of 0.015 and a lower limit of -0.015, and the actual difference in the coefficient of a certain pass is 0.02 (exceeding the upper limit of 0.005), because the adjustment amount is positively correlated with the absolute value of the actual difference in the coefficient, the mold matching coefficient adjustment amount is generated as +0.02 (increasing the extension coefficient by 0.02), so that the real-time production parameters after adjustment approach the preset mold matching target parameters.

[0083] S420 generates an optimized die-matching coefficient scheme based on the die-matching coefficient adjustment amount. This optimized scheme includes the new optimized die-matching coefficients for the required passes and the drawing speed matching parameters.

[0084] It can be understood that the die matching coefficient adjustment amount is the specific adjustment value of the elongation coefficient, and the newly optimized die matching coefficient is the elongation coefficient that needs to be implemented after the adjustment. The drawing speed matching parameter is the drawing speed adapted to the newly optimized die matching coefficient, so that the adjusted process is stable and production failures are avoided due to a single adjustment of the elongation coefficient. The drawing speed matching parameter can be obtained through database matching. The database includes the newly optimized die matching coefficient and the drawing speed matching parameter, and there is a mapping relationship between the newly optimized die matching coefficient and the drawing speed matching parameter. Optionally, the database can be established by consulting relevant literature. For example: the real-time production parameter of a certain pass is 1.24, the real-time drawing speed is 14.5m / s, the actual difference of the coefficient is 0.02, the generated die matching coefficient adjustment amount is +0.02, and the newly optimized die matching coefficient is 1.26. At the same time, the drawing speed parameter matched in the database is 14.8m / s, forming a complete optimization scheme including the elongation coefficient and speed parameter, so as to ensure process stability.

[0085] By employing steps S410 to S420, precise optimization of the die matching coefficient and process coordination can be achieved: a reasonable adjustment amount is generated based on the comparison between the actual difference in the coefficient and the preset extension threshold, ensuring that the adjusted process meets the target requirements. This improves the feasibility and stability of the optimization scheme and guarantees the quality of the finished copper wire.

[0086] S500: If the actual difference of any coefficient exceeds the extended adjustment threshold, it is determined that the current working condition has exceeded the optimization range of the mold matching coefficient, and an alarm signal is immediately output. The extended adjustment threshold is greater than the preset extended threshold.

[0087] It is understandable that the actual difference in coefficients represents the magnitude of the extension coefficient that needs to be adjusted for each pass. The extension adjustment threshold is a broader critical range for extreme operating conditions than the preset extension threshold, used to define whether the conventional optimization capability is exceeded; both its upper and lower limits are greater than the preset extension threshold. The operating condition refers to the actual state of the current drawing production. Exceeding the die matching coefficient optimization range means that the actual difference in coefficients is too large, and conventional extension coefficient adjustments cannot resolve the issue, potentially leading to risks such as die damage, copper wire breakage, and finished product scrap. The alarm signal is a warning message used to alert staff to extreme operating conditions, including the faulty pass, the magnitude of the difference, and the type of risk. For example: if the extension adjustment threshold is set to [-0.03, 0.03] (greater than the preset extension threshold [-0.015, 0.015]), and the actual difference of the coefficient in the third pass suddenly changes from 0.01 to 0.035 (exceeding the lower limit) due to sudden severe wear of the mold, it is determined that the current working condition has exceeded the optimization range of the mold matching coefficient. An alarm signal is immediately output, indicating "The actual difference of the coefficient in the third pass is 0.035, which exceeds the extension adjustment threshold. There is a risk of mold overload and copper wire breakage. Please stop the machine immediately for investigation" to avoid major production accidents.

[0088] 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.

[0089] Corresponding to the die matching coefficient optimization method for multi-pass drawing of bare copper wire described in the above embodiments, this application also provides a die matching coefficient optimization system, in which each unit can implement each step of the die matching coefficient optimization method for multi-pass drawing of bare copper wire. Figure 3 The diagram shows a structural block diagram of the model matching coefficient optimization system provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0090] Reference Figure 3 The system includes: The acquisition unit is used to obtain the coefficient offset of each pass of the bare copper wire based on the die matching reference parameters and real-time production parameters. The die matching reference parameters refer to the reference elongation coefficient after the standard die production is established for each pass. The real-time production parameters reflect the actual elongation coefficient of the bare copper wire in each pass. The coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions.

[0091] The reference unit is used to obtain the coefficient reference difference value for each pass of the bare copper wire drawing process, based on the die matching reference parameters and the preset die matching target parameters. The preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing process. The coefficient reference difference value reflects the inherent difference between the die matching reference parameters and the preset die matching target parameters under standard operating conditions.

[0092] The actual unit is used to obtain the actual coefficient difference for each pass of the bare copper wire based on the coefficient offset and the coefficient reference difference. The actual coefficient difference represents the amount of extension coefficient that needs to be adjusted to achieve the preset mold matching target parameters under real-time production parameters.

[0093] The optimization unit is used to obtain an optimization scheme for the matching coefficient of bare copper wire based on the actual difference of the coefficient and the preset extension threshold.

[0094] 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.

[0095] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units is merely an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the system can be divided into different functional units to complete all or part of the functions described above. The functional units 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 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 in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0096] This application also provides an electronic device. Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 6 of 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, wherein when the processor 60 executes the computer program 62, it causes the electronic device 6 to implement the steps in any of the above embodiments of the method for optimizing the die coefficient for multi-pass drawing of bare copper wire, or causes the electronic device 6 to implement the functions of the units in the above system embodiments.

[0097] For example, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the electronic device 6.

[0098] The electronic device 6 may be an industrial control computer, an edge computing gateway, a production scheduling server, a cloud server, an industrial tablet computer, or an intelligent scheduling terminal, etc. The electronic device includes 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 foregoing aspects. The electronic device 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 4This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, buses, etc.

[0099] 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.

[0100] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may be an external storage device of the electronic device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 6. Furthermore, the memory 61 may include both internal and external storage units of the electronic device 6. The memory 61 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0101] 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.

[0102] This application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the steps in any of the above method embodiments.

[0103] 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 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 system capable of carrying computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0104] 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.

[0105] 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.

[0106] In the embodiments provided in this application, it should be understood that the disclosed method, system, and electronic device for optimizing the die matching coefficient for multi-pass drawing of bare copper wire can be implemented in other ways. For example, the embodiments of the die matching coefficient optimization system and electronic device described above are merely illustrative. For instance, the division of 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; the indirect coupling or communication connection between units may be electrical, mechanical, or other forms.

[0107] 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.

[0108] 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. A method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire, characterized in that, include: Based on the die matching reference parameters and real-time production parameters for each pass of the bare copper wire, the coefficient offset for each pass of the bare copper wire is obtained; wherein, the die matching reference parameters refer to the reference elongation coefficient after the standard die production is determined for each pass; the real-time production parameters reflect the actual elongation coefficient of the bare copper wire for each pass; the coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions. Based on the die matching reference parameters and the preset die matching target parameters for each pass of the bare copper wire, the coefficient reference difference for each pass of the bare copper wire is obtained; wherein, the preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing; the coefficient reference difference reflects the inherent gap between the die matching reference parameters and the preset die matching target parameters under standard working conditions. Based on the coefficient offset and the coefficient reference difference, the actual coefficient difference for each pass of the bare copper wire is obtained; wherein, the actual coefficient difference represents the magnitude of the extension coefficient that needs to be adjusted to achieve the preset mold matching target parameters under the real-time production parameters; Based on the actual difference of the coefficients and the preset extension threshold, the optimization scheme of the mold coefficient of the bare copper wire is obtained.

2. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 1, characterized in that, The step of obtaining the coefficient offset for each pass of the bare copper wire based on the die matching reference parameters and real-time production parameters includes: Based on the mold production instructions for each pass of the bare copper wire, the mold matching reference parameters are obtained; Real-time production parameters are determined based on the real-time cross-sectional area values ​​of each pass of the bare copper wire; wherein, the real-time production parameters represent the ratio of the real-time cross-sectional area value of the previous pass to the real-time cross-sectional area value of the next pass. Based on the mold matching reference parameters and the real-time production parameters, the coefficient offset of each pass of the bare copper wire is obtained.

3. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 1, characterized in that, The coefficient benchmark difference value is obtained based on the matching reference parameters and the preset matching target parameters for each pass of the bare copper wire, including: Obtain the reference features corresponding to the mold matching reference parameters for each pass and the target features corresponding to the preset mold matching target parameters; Based on the benchmark features and the target features, a first combined feature is generated; wherein, the first combined feature is used to characterize the degree of correlation between the mold matching benchmark parameters and the preset mold matching target parameters; The first combined features are input into the difference calculation model to obtain the initial difference features for each pass; wherein, the difference calculation model represents a machine learning model that takes the first combined features as input and the initial difference features as output; the initial difference features are candidate differences matched by the difference calculation model; The initial difference features are analyzed to obtain the coefficient benchmark difference for each pass.

4. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 3, characterized in that, The generation of the first combined feature based on the benchmark feature and the target feature includes: The baseline features and the target features are preprocessed respectively to obtain the baseline feature vector and the target feature vector; Based on the historical drawing process patterns of the bare copper wire, the initial weights of the reference features and target features are determined; among them, the features with higher correlation to the elongation coefficient have higher weights. The preprocessed baseline feature vector and the target feature vector are weighted and fused according to the initial weights to output the fused combined feature vector. The combined feature vector after fusion is validated. If the variance of the combined feature vector is within a preset valid threshold range, the combined feature vector is used as the first combined feature.

5. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 4, characterized in that, The preprocessing of the baseline features and the target features to obtain the baseline feature vector and the target feature vector includes: Feature cleaning process removes outlier data from baseline and target features; The cleaned baseline features and target features are normalized to obtain the original baseline feature values ​​and the original target feature values. Dimension matching is performed on the normalized original baseline feature values ​​and the original target feature values ​​to obtain effective baseline features and effective target features; The effective baseline features and effective target features, after being cleaned, standardized, and dimensionally unified, are converted into fixed-length one-dimensional vectors to obtain the baseline feature vector and the target feature vector.

6. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 1, characterized in that, The step of obtaining the actual coefficient difference for each pass of the bare copper wire based on the coefficient offset and the coefficient reference difference includes: Based on the coefficient offset of each pass of the bare copper wire, a first offset coefficient sequence is determined; Based on the coefficient reference difference value of each pass of the bare copper wire, a second offset coefficient sequence is obtained; Based on the first offset coefficient sequence and the second offset coefficient sequence, the actual difference in coefficients for each pass of the bare copper wire is obtained.

7. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 6, characterized in that, The step of obtaining the actual difference in coefficients for each pass of the bare copper wire based on the first offset coefficient sequence and the second offset coefficient sequence includes: The first offset coefficient sequence and the second offset coefficient sequence are aligned by track number to form an aligned double sequence group. The rationality of the dual-sequence set with the preset process constraints is judged to obtain the initial coefficient actual difference sequence; The initial coefficient actual difference sequence is processed to obtain the coefficient actual difference for each pass.

8. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 1, characterized in that, The step of obtaining the mold matching coefficient optimization scheme for the bare copper wire based on the actual difference of the coefficient and the preset extension threshold includes: When the actual difference of the coefficients is greater than the upper limit of the preset extension threshold or less than the lower limit of the preset extension threshold, a matching coefficient adjustment amount is generated; wherein, the matching coefficient adjustment amount represents the absolute value of the actual difference of the coefficients plus the adjustment direction; Based on the adjustment amount of the die matching coefficient, an optimized die matching coefficient scheme is generated; wherein, the optimized die matching coefficient scheme includes a new optimized die matching coefficient for the required number of passes and drawing speed matching parameters.

9. The method for optimizing the die matching coefficient for multi-pass drawing of bare copper wire according to claim 1, characterized in that, The method further includes: If the actual difference of any of the coefficients exceeds the extension adjustment threshold, it is determined that the current working condition has exceeded the optimization range of the mold matching coefficient, and an alarm signal is immediately output; wherein, the extension adjustment threshold is greater than the preset extension threshold.

10. A system for optimizing mold matching coefficients, characterized in that, include: The acquisition unit is used to obtain the coefficient offset of each pass of the bare copper wire based on the die matching reference parameters and real-time production parameters; wherein, the die matching reference parameters refer to the reference elongation coefficient after the standard die production is determined for each pass; the real-time production parameters reflect the actual elongation coefficient of the bare copper wire in each pass; and the coefficient offset reflects the degree of deviation between the actual elongation coefficient under real-time production conditions and the reference elongation coefficient under standard conditions. A reference unit is used to obtain the coefficient reference difference for each pass of the bare copper wire based on the die matching reference parameters and the preset die matching target parameters for each pass; wherein, the preset die matching target coefficient refers to the elongation coefficient that needs to be achieved in each pass of the bare copper wire drawing; the coefficient reference difference reflects the inherent gap between the die matching reference parameters and the preset die matching target parameters under standard working conditions. The actual unit is used to obtain the actual coefficient difference of each pass of the bare copper wire based on the coefficient offset and the coefficient reference difference; wherein, the actual coefficient difference represents the magnitude of the extension coefficient that needs to be adjusted to achieve the preset mold matching target parameters under the real-time production parameters; The optimization unit is used to obtain an optimization scheme for the matching coefficient of the bare copper wire based on the actual difference of the coefficient and the preset extension threshold.

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