Copper alloy wire preparation method

Abstract

The invention is applicable to the technical field of alloy wire preparation, and particularly relates to a copper alloy wire preparation method which comprises the following steps: acquiring historical production data and a target production plan of a copper alloy wire; determining a target preparation parameter and a first range of the target preparation parameter according to the historical production data and the target production plan; sampling according to the historical production data and the first range to obtain a sample parameter value of the target preparation parameter; determining a second parameter value of the target preparation parameter according to the target production plan and the sample parameter value; and controlling copper alloy wire preparation equipment to prepare the copper alloy wire based on the second parameter value. According to the copper alloy wire preparation method provided by the embodiment of the invention, the problem of low production efficiency caused by inflexible control of parameters of copper alloy wire preparation equipment can be solved.

Description

Technical Field

[0001] This application belongs to the technical field of alloy wire preparation, and particularly relates to a method for preparing copper alloy wire. Background Art

[0002] The preparation of copper alloy wire mainly refers to converting raw materials into copper alloy wire products that meet specific requirements through a series of process steps and precise control means using copper alloy wire preparation equipment. In each link, precise control of the preparation parameters is required to ensure the quality and performance of the copper alloy wire.

[0003] In the prior art, there are certain limitations in parameter control in the method for preparing copper alloy wire, and manual intervention is still required to set and adjust parameters in the production process. With the continuous change and upgrade of market demand, the types and specification requirements of copper alloy wire are becoming more and more diverse. If it cannot be adjusted in real time according to market demand, it will lead to low production efficiency of copper alloy wire. Therefore, there is a problem that the production efficiency is low due to inflexible parameter control in the current method for preparing copper alloy wire. Summary of the Invention

[0004] The embodiments of this application provide a method for preparing copper alloy wire, which can solve the problem of low production efficiency caused by inflexible parameter control.

[0005] In a first aspect, the embodiments of this application provide a method for preparing copper alloy wire, including:

[0006] Obtain the historical production data and target production plan of the copper alloy wire; wherein, the historical production data is at least one production record corresponding to different types of copper alloy wire, and the production record includes the type, specification, and first parameter value of the historical preparation parameters of the copper alloy wire. The historical preparation parameters are one of the preparation parameters of temperature, time, speed, and / or pressure corresponding to each production link respectively. The production links include rolling, stretching, and heat treatment. The target production plan includes the type and specification of the copper alloy wire, and the specification includes diameter, tensile strength, and elongation after fracture;

[0007] Determine the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan; wherein, the target preparation parameters are the temperature, time, speed, and / or pressure corresponding to each of the production links respectively, and the first range is the value range of each preparation parameter in the target preparation parameters;

[0008] Sample the sample parameter values of the target preparation parameters according to the historical production data and the first range;

[0009] Determine the second parameter value of the target preparation parameter according to the target production plan and the sample parameter values;

[0010] Control the copper alloy wire preparation equipment to prepare copper alloy wire based on the second parameter value.

[0011] In the technical solution described above in the embodiments of the present application, at least the following technical effects are achieved:

[0012] The copper alloy wire preparation method provided by the embodiments of the present application includes: obtaining the historical production data and the target production plan of the copper alloy wire; determining the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan; sampling the sample parameter values of the target preparation parameters according to the historical production data and the first range; determining the second parameter value of the target preparation parameters according to the target production plan and the sample parameter values; and controlling the copper alloy wire preparation equipment to prepare copper alloy wire based on the second parameter value. Therefore, the copper alloy wire preparation method provided by the embodiments of the present application can achieve precise control of the preparation parameters, flexibly adjust the preparation parameters, and adapt to the production of copper alloy wires with different types and specification requirements through parameter range setting and simulation optimization based on historical production data and the target production plan; determine the parameter values of the copper alloy wire preparation equipment through simulation and apply them to actual production, reducing the trial-and-error time and cost and improving the production efficiency.

[0013] In a possible implementation manner of the first aspect, the determining the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan includes:

[0014] Determine at least one first production data corresponding to the type of copper alloy wire in the target production plan in the historical production data;

[0015] Determine the target preparation parameters according to the first production data;

[0016] Calculate the first similarity between the specification of the copper alloy wire in the first production data and the specification in the target production plan;

[0017] If there is a first similarity exceeding the first threshold, determine the corresponding first production data as the second production data;

[0018] Determine the first range of the target preparation parameters based on the second production data.

[0019] In a possible implementation manner of the first aspect, the determining the first range of the target preparation parameters based on the second production data includes:

[0020] If the second production data only contains the production record once, set a first tolerance interval for the first parameter value and determine the first tolerance interval as the first range of the target preparation parameters;

[0021] If the second production data includes multiple pieces of the production records, determine a first range of the target preparation parameters according to the maximum value and the minimum value of the first parameter values of the respective historical preparation parameters.

[0022] In a possible implementation manner of the first aspect, the determining the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan further includes:

[0023] If there is no first similarity exceeding the first threshold, calculate a first distance between the diameter in the first production data and the corresponding target production plan, and a second distance between the tensile strength and the elongation after fracture.

[0024] Determine a first type of parameter that affects the diameter and a second type of parameter that affects the tensile strength and the elongation after fracture in the target preparation parameters according to the first production data.

[0025] If there is the first distance or the second distance exceeding a second threshold, determine the corresponding first production data as third production data.

[0026] Determine a second range of the corresponding first type of parameter and / or the second type of parameter based on the third production data.

[0027] If each of the first distances or each of the second distances does not exceed the second threshold, determine the corresponding first production data as fourth production data.

[0028] Determine a third range of the corresponding first type of parameter and / or the second type of parameter based on the fourth production data and the target production plan.

[0029] Determine the first range of the target preparation parameters according to the second range and / or the third range.

[0030] In a possible implementation manner of the first aspect, the determining the first type of parameter that affects the diameter and the second type of parameter that affects the tensile strength and the elongation after fracture in the target preparation parameters according to the first production data includes:

[0031] Obtain a correlation coefficient between the target preparation parameters and the diameter, the tensile strength, and the elongation after fracture of the copper alloy wire according to the first production data.

[0032] Determine the first type of parameter and the second type of parameter according to the correlation coefficient.

[0033] In a possible implementation of the first aspect, determining the corresponding second range of the first type of parameter and / or the second type of parameter based on the third production data includes:

[0034] If there is only one production record in the third production data, set a second tolerance interval for the first parameter value and determine the second tolerance interval as the second range of the first type of parameter and / or the second type of parameter;

[0035] If there are multiple production records in the third production data, determine the corresponding second range of the first type of parameter and / or the second type of parameter according to the maximum and minimum values of the first parameter values of each historical preparation parameter.

[0036] In a possible implementation of the first aspect, determining the corresponding third range of the first type of parameter and / or the second type of parameter based on the fourth production data and the target production plan includes:

[0037] Select feature data from the fourth production data;

[0038] According to the feature data, assign different weights to different feature data to obtain a feature vector;

[0039] Use the feature vector as input to train an initial model;

[0040] Verify the trained initial model according to the cross-validation method to obtain a standard model; wherein, the cross-validation method is to repeatedly use subsets of the feature data to train and test the initial model to predict the performance of the initial model;

[0041] Input the preprocessed target production plan into the standard model for prediction;

[0042] Obtain the predicted values of the corresponding first type of parameter and / or the second type of parameter according to the output of the standard model;

[0043] Calculate the third tolerance interval of the predicted values and determine the third tolerance interval as the third range of the first type of parameter and / or the second type of parameter.

[0044] In a possible implementation of the first aspect, sampling the sample parameter values of the target preparation parameter according to the historical production data and the first range includes:

[0045] Determine the sampling quantity according to the historical production data and the first range;

[0046] Stratified sampling is performed within the first range according to the sampling quantity to obtain the sample parameter values of the target preparation parameters.

[0047] In a possible implementation manner of the first aspect, determining the second parameter value of the target preparation parameter according to the target production plan and the sample parameter values includes:

[0048] Performing simulation according to the sample parameter values to obtain the actual diameter, actual tensile strength, and actual elongation after fracture;

[0049] Calculating the errors between the actual diameter, the actual tensile strength, and the actual elongation after fracture and the specifications of the copper alloy wire in the target production plan, and calculating the first error by assigning weights;

[0050] Sorting the sample parameter values according to each of the first errors to obtain a better solution; wherein, the better solution is the sample parameter value corresponding to the smallest first error;

[0051] Judging whether the first error corresponding to the better solution is less than a third threshold;

[0052] If the first error corresponding to the better solution is less than the third threshold, then determining the better solution as the second parameter value.

[0053] In a possible implementation manner of the first aspect, judging whether the first error corresponding to the better solution is less than a third threshold includes:

[0054] If the first error corresponding to the better solution is not less than the third threshold, then generating a candidate solution according to the better solution; wherein, the candidate solution is a candidate parameter value of the target preparation parameter different from the sample parameter value;

[0055] Performing iterative optimization according to the candidate solution to obtain the second parameter value.

[0056] In a second aspect, an embodiment of the present application provides a copper alloy wire preparation device, including:

[0057] An acquisition module, configured to acquire historical production data and a target production plan of copper alloy wire; wherein, the historical production data is at least one production record corresponding to different types of copper alloy wire, the production record includes the type, specifications, and the first parameter value of the historical preparation parameters of the copper alloy wire, the historical preparation parameter is one of the preparation parameters of temperature, time, speed, and / or pressure corresponding to each production link respectively, the production links include rolling, stretching, and heat treatment, the target production plan includes the type and specifications of the copper alloy wire, and the specifications include diameter, tensile strength, and elongation after fracture;

[0058] A range module for determining a target preparation parameter and a first range of the target preparation parameter according to the historical production data and the target production plan; wherein, the target preparation parameter is the temperature, time, speed, and / or pressure respectively corresponding to each production link, and the first range is the value range of each preparation parameter in the target preparation parameter;

[0059] A sampling module for sampling the sample parameter values of the target preparation parameter according to the historical production data and the first range;

[0060] A simulation module for determining a second parameter value of the target preparation parameter according to the target production plan and the sample parameter values;

[0061] A control module for controlling a copper alloy wire preparation device to prepare copper alloy wires based on the second parameter value.

[0062] In a third aspect, an embodiment of the present application provides a copper alloy wire preparation device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of the above first aspects when executing the computer program.

[0063] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, and the computer program implements the method according to any one of the above first aspects when executed by a processor.

[0064] In a fifth aspect, an embodiment of the present application provides a computer program product, and when the computer program product runs on a copper alloy wire preparation device, the copper alloy wire preparation device is enabled to execute the method according to any one of the above first aspects.

[0065] It can be understood that the beneficial effects of the above second to fifth aspects can refer to the relevant descriptions in the above first aspect and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0067] Figure 1 It is a flowchart of a copper alloy wire preparation method provided by an embodiment of the present application;

[0068] Figure 2It is a schematic flowchart showing the implementation processes of steps S200, S250, S202, S204, and S206 in the method for preparing a copper alloy wire provided in an embodiment of the present application;

[0069] Figure 3 It is a schematic flowchart showing the implementation processes of steps S300, S400, and S440 in the method for preparing a copper alloy wire provided in an embodiment of the present application;

[0070] Figure 4 It is a schematic structural diagram of the copper alloy wire preparation device provided in an embodiment of the present application;

[0071] Figure 5 It is a schematic structural diagram of the copper alloy wire preparation equipment provided in an embodiment of the present application. Detailed implementation manners

[0072] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0073] It should be understood that when used in the specification and appended claims of the present application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0074] It should also be understood that the term "and / or" as used in the specification and appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0075] As used in the specification and appended claims of the present application, the term "if" can be interpreted as "when", "once", "in response to determining", or "in response to detecting" according to the context. Similarly, the phrase "if determined" or "if detected [the described condition or event]" can be interpreted as meaning "once determined", "in response to determining", "once detected [the described condition or event]", or "in response to detecting [the described condition or event]" according to the context.

[0076] In addition, in the description of the specification and appended claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0077] References to "one embodiment" or "some embodiments" etc. described in the specification of the present application mean that specific features, structures or characteristics described in connection with that embodiment are included in one or more embodiments of the present application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments" etc. that appear at different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized.

[0078] In the related art, there are certain limitations in the parameter control of the copper alloy wire preparation method, and manual intervention is still required in the production process to set and adjust parameters. With the continuous change and upgrade of market demands, the types and specification requirements of copper alloy wires are becoming more and more diverse. If it is impossible to adjust in real time according to market demands, it will lead to a low production efficiency of copper alloy wires. Therefore, there is a problem that the production efficiency is low due to the inflexible parameter control in the current copper alloy wire preparation method.

[0079] To solve the above problems, an embodiment of the present application provides a copper alloy wire preparation method. In this method, historical production data and a target production plan of the copper alloy wire are obtained; a target preparation parameter and a first range of the target preparation parameter are determined according to the historical production data and the target production plan; sample parameter values of the target preparation parameter are obtained by sampling according to the historical production data and the first range; a second parameter value of the target preparation parameter is determined according to the target production plan and the sample parameter values; and a copper alloy wire preparation device is controlled based on the second parameter value to prepare a copper alloy wire. Therefore, the copper alloy wire preparation method provided by the embodiment of the present application can achieve precise control of the preparation parameters, flexibly adjust the preparation parameters, and adapt to the production of copper alloy wires with different types and specification requirements through parameter range setting and simulation optimization based on historical production data and a target production plan; determine the parameter values of the copper alloy wire preparation device through simulation and apply them to actual production, reducing the trial-and-error time and cost and improving the production efficiency.

[0080] The copper alloy wire preparation method provided by the embodiment of the present application can be applied to a copper alloy wire preparation device. At this time, the copper alloy wire preparation device is the execution subject of the copper alloy wire preparation method provided by the embodiment of the present application, and the embodiment of the present application does not impose any restrictions on the specific type of the copper alloy wire preparation device.

[0081] For example, the copper alloy wire manufacturing equipment may be a cellular phone, cordless phone, Session Initiation Protocol (SIP) phone, mobile phone, tablet computer, wearable device, vehicle-mounted device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), desktop computer, smart large screen, smart TV, handheld device with wireless communication function, computing device or other processing device connected to a wireless modem, vehicle-mounted device, vehicle networking terminal, computer, laptop computer, handheld communication device, handheld computing device, satellite wireless device, etc., but not limited thereto.

[0082] To better understand the copper alloy wire manufacturing method provided by the embodiments of the present application, the following provides an exemplary introduction to the specific implementation process of the copper alloy wire manufacturing method provided by the embodiments of the present application.

[0083] Figure 1 The schematic flowchart of the copper alloy wire manufacturing method provided by the embodiments of the present application is shown. The copper alloy wire manufacturing method includes:

[0084] S100, obtaining the historical production data and target production plan of the copper alloy wire. Among them, the historical production data is at least one production record corresponding to different types of copper alloy wires. The production record includes the type, specification of the copper alloy wire, and the first parameter value of the historical preparation parameters. The historical preparation parameters are one of the preparation parameters of temperature, time, speed, and / or pressure corresponding to each production link. The production links include rolling, drawing, and heat treatment. The target production plan includes the type and specification of the copper alloy wire. The specification includes diameter, tensile strength, and elongation after fracture.

[0085] It can be understood that the diameter of the copper alloy wire refers to the diameter of its cross-section. For non-circular cross-sections (such as rectangular, square, etc.), the opposite side distance of the cross-section is used to replace the diameter of the cross-section.

[0086] Exemplarily, the historical production data of the copper alloy wire can be exported from a database, and the copper alloy wire manufacturing device receives the target production plan from a terminal (such as a mobile phone, laptop computer, etc.).

[0087] S200. Determine the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan. Among them, the target preparation parameters are the temperature, time, speed, and / or pressure corresponding to each production link respectively, and the first range is the value range of each preparation parameter in the target preparation parameters.

[0088] Exemplarily, the target preparation parameters can be determined according to the historical production data, and the first range of the target preparation parameters can be determined according to the historical production data and the target production plan.

[0089] In a possible implementation, please refer to Figure 2 , S200. Determine the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan, including:

[0090] S210. Determine at least one first production data corresponding to the type of copper alloy wire in the target production plan in the historical production data according to the target production plan.

[0091] Exemplarily, all production records corresponding to the type of copper alloy wire (such as brass wire, bronze wire, or white copper wire, etc.) in the target production plan can be screened out from the database.

[0092] S220. Determine the target preparation parameters according to the first production data.

[0093] Exemplarily, the target preparation parameters can be determined according to the preparation parameters included in the first production data. For example, if the preparation parameters included in the first production data are as shown in Table 1 below, then the target preparation parameters include the pressure (MPa) in the rolling link, the time (min) and speed (mm / min) in the stretching link, and the temperature (°C) and speed (°C / min) in the heat treatment link.

[0094]

[0095] Table 1

[0096] S230. Calculate the first similarity between the specifications of the copper alloy wire in the first production data and the specifications in the target production plan.

[0097] Exemplarily, methods such as Euclidean distance and Manhattan distance can be used to calculate the first similarity between the specifications of the copper alloy wire in the first production data and the specifications in the target production plan. For example, if the first production data is as shown in Table 2 below, and the target production plan is: diameter 2mm, tensile strength 400MPa, elongation after fracture 15%, the Euclidean distance can be used to calculate the first similarity: Among them, d1, σ1, and δ1 are the diameter, tensile strength, and elongation after fracture in the first production data respectively, d target , σ target , δtarget They are the diameter, tensile strength, and elongation after fracture in the target production plan. Substitute the values. For the production record with serial number 1: d≈5.01, and for the production record with serial number 2: d≈5.025.

[0098] Serial number Type Diameter (mm) Tensile strength (MPa) Elongation after fracture (%) … 1 Brass wire 1.98 395 14.5 … 2 Brass wire 2.02 405 15.5 … … … … … … …

[0099] Table 2

[0100] S240. If there is a first similarity exceeding the first threshold, then determine the corresponding first production data as the second production data.

[0101] It can be understood that the first threshold is that the first similarity does not exceed a preset specified value, and this preset specified value can be set by those of ordinary skill in the art according to actual needs and is not uniquely limited here.

[0102] Exemplarily, a reasonable first threshold can be determined according to historical data and industry standards. For example, the first threshold is 5, and the production records in the first production data with a first similarity greater than 5 are selected as the second production data.

[0103] S250. Determine the first range of the target preparation parameters based on the second production data.

[0104] Exemplarily, the value range of the target preparation parameters in the second production data can be statistically obtained to get the first range of the target preparation parameters.

[0105] Through the above steps S210 to S250, determining the target preparation parameters and the value range of the target preparation parameters according to historical production data and the target production plan is beneficial to improving production efficiency and product quality. Using the similarity screening method makes the determination of the target preparation parameters more scientific and reasonable, reduces the trial - and - error cost, and is beneficial to realizing the intelligence and automation of the production process.

[0106] Optionally, please refer to Figure 2 , S250. Determining the first range of the target preparation parameters based on the second production data includes:

[0107] S251. If the second production data only contains one production record, set a first tolerance interval for the first parameter value and determine the first tolerance interval as the first range of the target preparation parameters.

[0108] Exemplarily, a reasonable first tolerance interval can be determined according to historical data and industry standards. For example, if the second production data is as shown in Table 3 below, then based on the first parameter value ±10%, the first tolerance interval, that is, the first range, is obtained as shown in Table 4 below.

[0109]

[0110] Table 3

[0111]

[0112] Table 4

[0113] S252. If the second production data contains multiple production records, determine the first range of the target preparation parameters according to the maximum and minimum values of the first parameter values of each historical preparation parameter.

[0114] Exemplarily, the maximum and minimum values of the first parameter values of each historical preparation parameter in the second production data can be calculated, and this value range can be determined as the first range of the target preparation parameters. For example, if the second production data is as shown in Table 5 below, then the first range is as shown in Table 6 below.

[0115]

[0116] Table 5

[0117]

[0118] Table 6

[0119] Through the above steps S251 to S252, when the production records are limited, by setting a reasonable tolerance interval, it is beneficial to improve the accuracy of the preparation parameters and avoid excessive adjustment due to insufficient data; when there are multiple production records, by calculating the maximum and minimum values to determine the range, the parameter changes in actual production can be accurately reflected, which is beneficial to improving the stability and consistency of the preparation.

[0120] In a possible implementation manner, please refer to Figure 2 , S200. Determining the target preparation parameters and the first range of the target preparation parameters according to the historical production data and the target production plan further includes:

[0121] S201. If there is no first similarity exceeding the first threshold, calculate the first distance between the diameter in the first production data and the corresponding target production plan, and the second distances between the tensile strength and the elongation after fracture.

[0122] Exemplarily, the first distance between the diameter in the first production data and the corresponding target production plan, and the second distances between the tensile strength and the elongation after fracture can be calculated. For example, for the first production data: diameter D1 = 2.5 mm, tensile strength TS1 = 400 MPa, elongation after fracture El1 = 15%, and the target production plan: diameter D2 = 2.6 mm, tensile strength TS2 = 410 MPa, elongation after fracture El2 = 16%, then the first distance: D dist = ∣D1 - D2∣ = ∣2.5 - 2.6∣ = 0.1 mm; the second distance: TSdist = |TS1 - TS2| = |400 - 410| = 10 MPa, El dist = |El1 - El2| = |0.15 - 0.16| = 0.01.

[0123] S202. Determine the first type of parameters that affect the diameter and the second type of parameters that affect the tensile strength and elongation after fracture in the target preparation parameters according to the first production data.

[0124] Exemplarily, statistical methods (such as correlation analysis, regression analysis, variance analysis, etc.) can be used according to the first production data to evaluate the relationship between each preparation parameter in the target preparation parameters and the diameter, tensile strength, and elongation after fracture, and determine the first type of parameters that affect the diameter and the second type of parameters that affect the tensile strength and elongation after fracture in the target preparation parameters.

[0125] Optionally, please refer to Figure 2 , S202. Determine the first type of parameters that affect the diameter and the second type of parameters that affect the tensile strength and elongation after fracture in the target preparation parameters according to the first production data, including:

[0126] S2021. Obtain the correlation coefficients between the target preparation parameters and the diameter, tensile strength, and elongation after fracture of the copper alloy wire according to the first production data.

[0127] Exemplarily, correlation coefficients (such as Pearson correlation coefficient, Spearman rank correlation coefficient, Kendall correlation coefficient, etc.) can be used according to the first production data to calculate the correlation coefficients between each preparation parameter in the target preparation parameters and the diameter, tensile strength, and elongation after fracture of the copper alloy wire respectively. For example, the correlation coefficient is calculated using the Pearson correlation coefficient formula, where r is the correlation coefficient, X i is each preparation parameter in the target preparation parameters, is the mean value of each preparation parameter in the first production data, Y i is the diameter, tensile strength, or elongation after fracture, is the mean value of the diameter, tensile strength, or elongation after fracture in the first production data.

[0128] S2022. Determine the first type of parameters and the second type of parameters according to the correlation coefficients.

[0129] Exemplarily, a reasonable correlation threshold (such as 0.5) can be determined according to historical data and industry standards. The preparation parameters in the target preparation parameters with a correlation coefficient greater than the correlation threshold with the diameter are determined as the first type of parameters, and the preparation parameters in the target preparation parameters with a correlation coefficient greater than the correlation threshold with the tensile strength or elongation after fracture are determined as the second type of parameters.

[0130] Through the above steps S2021 to S2022, calculating the correlation coefficient and determining the parameter type can more accurately understand the influence degree of each preparation parameter on the product quality, so as to provide a scientific basis for the adjustment of subsequent preparation parameters.

[0131] S203, if the first distance or the second distance exceeds the second threshold, determine the corresponding first production data as the third production data.

[0132] It can be understood that the second threshold is that the first distance and the second distance do not exceed the corresponding preset specified value, and this preset specified value can be set by those of ordinary skill in the art according to actual needs and is not uniquely limited here.

[0133] Exemplarily, a reasonable second threshold can be determined according to historical data and industry standards. For example, the second threshold is: where D threshold is the diameter, TS threshold is the tensile strength, and El threshold is the elongation after fracture.

[0134] S204, determine the second range of the corresponding first type parameter and / or second type parameter based on the third production data.

[0135] Exemplarily, the value range of the first type parameter and / or the second type parameter in the third production data can be statistically obtained to get the second range of the first type parameter and / or the second type parameter.

[0136] Optionally, please refer to Figure 2 , S204, determining the second range of the corresponding first type parameter and / or second type parameter based on the third production data includes:

[0137] S2041, if there is only one production record in the third production data, set a second tolerance interval for the first parameter value and determine the second tolerance interval as the second range of the first type parameter and / or the second type parameter.

[0138] Exemplarily, a reasonable second tolerance interval can be determined according to historical data and industry standards. For example, based on the first parameter value ±10%, the second tolerance interval, that is, the second range, is obtained.

[0139] S2042, if there are multiple production records in the third production data, determine the second range of the corresponding first type parameter and / or second type parameter according to the maximum and minimum values of the first parameter values of each historical preparation parameter.

[0140] Exemplarily, the maximum and minimum values of the first parameter values of the respective historical preparation parameters in the third production data can be calculated, and the second range of the corresponding first type parameter and / or second type parameter can be obtained.

[0141] By the above steps S2041 to S2042, setting reasonable ranges for different types of parameters is beneficial to more precisely and stably control the preparation parameters of the copper alloy wire preparation equipment.

[0142] S205, if each of the first distances or each of the second distances does not exceed the second threshold, then determine the corresponding first production data as the fourth production data.

[0143] It can be understood that if each of the first distances or each of the second distances does not exceed the second threshold, then determine the corresponding first production data as the fourth production data.

[0144] S206, determine the third range of the corresponding first type parameter and / or second type parameter based on the fourth production data and the target production plan.

[0145] Exemplarily, the third range of the corresponding first type parameter and / or second type parameter can be predicted based on the fourth production data and the target production plan through a model (such as a random forest model, a support vector machine regression model, a K-nearest neighbor regression model, etc.).

[0146] Optionally, please refer to Figure 2 , S206, determining the third range of the corresponding first type parameter and / or second type parameter based on the fourth production data and the target production plan includes:

[0147] S2061, select feature data from the fourth production data.

[0148] Exemplarily, the specifications of the copper alloy wire can be selected from the fourth production data as the feature data.

[0149] S2062, assign different weights to different feature data according to the feature data to obtain a feature vector.

[0150] It can be understood that a feature vector is a vector containing all feature data and their corresponding weights.

[0151] Exemplarily, weights can be assigned to the feature data according to the importance of different feature data for predicting the third range of the first type parameter and / or second type parameter to obtain a feature vector. For example, the feature vector is [diameter (mm), tensile strength (MPa), elongation after fracture (%)].

[0152] S2063, use the feature vector as the input to train the initial model.

[0153] It can be understood that the initial model is a model that has not been trained or has only been preliminarily trained.

[0154] Exemplarily, the initial model can be a random forest model, and the feature vector can be used as the training data set to train the initial model.

[0155] S2064, verify the trained initial model according to the cross - validation method to obtain the standard model. Among them, the cross - validation method is to repeatedly use subsets of the feature data to train and test the initial model to predict the performance of the initial model.

[0156] It can be understood that the subsets of the feature data are realized by dividing the original feature data set into multiple non - overlapping parts.

[0157] Exemplarily, K - fold cross - validation can be adopted. The original feature data set is divided into K subsets. One subset is used as the test set in turn, and the remaining K - 1 subsets are used as the training set for K iterations. The results of the K iterations are averaged to obtain an overall performance evaluation of the model and determine the standard model.

[0158] S2065, input the pre - processed target production plan into the standard model for prediction.

[0159] Exemplarily, a new feature vector with the same format as the feature vector of the training data set can be obtained according to the pre - processed target production plan, and this feature vector is input into the standard model for prediction. For example, the feature vector is [Diameter: 5(mm), Tensile strength: 400(MPa), Elongation after fracture: 15(%)].

[0160] S2066, obtain the predicted values of the corresponding first - type parameters and / or second - type parameters according to the output of the standard model.

[0161] Exemplarily, the standard model can make a prediction based on the input feature vector and output the prediction result to obtain the predicted values of the first - type parameters and / or second - type parameters.

[0162] S2067, calculate the third tolerance interval of the predicted value and determine the third tolerance interval as the third range of the first - type parameters and / or second - type parameters.

[0163] Exemplarily, a reasonable third tolerance interval can be determined according to historical data and industry standards. For example, on the basis of the predicted value ±5%, the third tolerance interval, that is, the third range, is obtained.

[0164] Through the above steps S2061 to S2067, machine learning technology can be used to extract useful information from a large amount of data, establish a prediction model to accurately predict the third range of the first type of parameter and / or the second type of parameter, improve the accuracy and reliability of the prediction, reduce the subjectivity and uncertainty of human judgment, and provide more accurate and reliable parameter guidance for the subsequent preparation process.

[0165] S207. Determine the first range of the target preparation parameters according to the second range and / or the third range.

[0166] It can be understood that when the second range or the third range includes the value range of all the preparation parameters in the target preparation parameters, the second range or the third range is determined as the first range of the target preparation parameters; when the second range or the third range includes the value range of some of the preparation parameters in the target preparation parameters, the first range of the target preparation parameters is determined according to the second range and the third range.

[0167] Through the above steps S201 to S207, historical production data, the target production plan, and machine learning technology are comprehensively used to determine the first range of the target preparation parameters, which is beneficial to improving the stability and consistency of the preparation process, improving the reliability and stability of the product quality, and providing a more scientific and systematic parameter optimization method for the preparation process of the copper alloy wire.

[0168] S300. Sample the sample parameter values of the target preparation parameters according to the historical production data and the first range.

[0169] Exemplarily, methods such as random sampling, systematic sampling, or stratified sampling can be used to extract the sample parameter values according to the historical production data and the first range.

[0170] In a possible implementation manner, please refer to Figure 3 , S300. Sampling the sample parameter values of the target preparation parameters according to the first range includes:

[0171] S310. Determine the sampling quantity according to the historical production data and the first range.

[0172] Exemplarily, the standard deviation corresponding to each preparation parameter can be determined according to the first production data in the historical production data, and the error range corresponding to each preparation parameter can be determined according to the first range, so as to determine the sampling quantity. For example, the range of the temperature (°C) in the heat treatment link in the first range is [720, 880], the corresponding standard deviation σ = 10, the acceptable error range does not exceed 5%, and the confidence level needs to reach 95%. Then the error range (E): (b - a) × 5% = (880 - 720) × 0.05 = 8. For a 95% confidence level, Z = 1.96, and the sampling quantity: Rounding up gives a sampling quantity of 7. Alternatively, the required sampling quantity can be obtained using statistical software (such as Statistical Product and Service Solutions, General Power Analysis, Power Analysis and Sample Size, etc.) based on historical production data and the first range.

[0173] S320. Stratified sampling is performed within the first range according to the sampling quantity to obtain the sample parameter values of the target preparation parameters.

[0174] Exemplarily, the first range can be divided into corresponding sub - intervals (i.e., layers) according to the sampling quantity, and then sample parameter values are respectively extracted within each sub - interval.

[0175] Through the above steps S310 to S320, the sample parameter values can be representative within the first range, which is conducive to accurately reflecting the true situation of the target preparation parameters. Through stratified sampling, the sampling error can be further reduced, which is conducive to improving the accuracy and reliability of the sample.

[0176] S400. Determine the second parameter value of the target preparation parameters according to the target production plan and the sample parameter values.

[0177] Exemplarily, simulation software (such as Design Environment for Forming, Adviser for metal Forming process Design EXpert, etc.) can be used to perform simulation according to the sample parameter values to obtain the specifications of the corresponding copper alloy wire, and determine the second parameter value of the target preparation parameters according to the target production plan.

[0178] In a possible implementation, please refer to Figure 3 , S400. Determining the second parameter value of the target preparation parameters according to the target production plan and the sample parameter values includes:

[0179] S410. Perform simulation according to the sample parameter values to obtain the actual diameter, actual tensile strength, and actual elongation after fracture.

[0180] Exemplarily, the sample parameter values can be input into a finite - element analysis system (Design Enviroment for Forming), and the finite - element analysis system outputs the corresponding actual diameter, actual tensile strength, and actual elongation after fracture, as shown in Table 7 below.

[0181]

[0182] Table 7

[0183] S420. Calculate the errors between the actual diameter, actual tensile strength, and actual elongation after fracture and the specifications of the copper alloy wire in the target production plan, and assign weights to calculate the first error.

[0184] Exemplarily, according to the diameter, tensile strength, and elongation after fracture given in the target production plan, the errors between the actual values and the corresponding target production plan can be calculated respectively. Different weights are assigned to the errors of the diameter, tensile strength, and elongation after fracture, and the weighted errors are added to obtain the first error. For example, the actual diameter, actual tensile strength, and actual elongation after fracture are as shown in Table 7 above, the target production plan: diameter 50mm, tensile strength 420MPa, elongation after fracture 20%, diameter error weight: 0.3, tensile strength error weight: 0.4, elongation after fracture error weight: 0.3, then the first error is as shown in Table 8 below.

[0185]

[0186] Table 8

[0187] S430. Sort the sample parameter values according to each first error to obtain a better solution. Among them, the better solution is the sample parameter value corresponding to the smallest first error.

[0188] Exemplarily, the first errors corresponding to each sample parameter value can be sorted, and the sample parameter value with the smallest first error is selected as the better solution. For example, if the first error is as shown in Table 8 above, the sample parameter value of No. 2 is the better solution. As shown in Table 7 above, the better solution is the pressure in the rolling process: 350 (MPa), the time in the stretching process: 15 (min) and the speed: 7 (mm / min), the temperature in the heat treatment process: 850 (°C) and the speed: 12 (°C / min).

[0189] S440. Judge whether the first error corresponding to the better solution is less than the third threshold.

[0190] It can be understood that the third threshold is that the first error corresponding to the better solution does not exceed a preset specified value, and this preset specified value can be set by those of ordinary skill in the art according to actual needs and is not uniquely limited here.

[0191] Exemplarily, a reasonable third threshold can be determined according to historical data and industry standards. For example, the third threshold is 2.

[0192] Optionally, please refer to Figure 3 , S440. Judging whether the first error corresponding to the better solution is less than the third threshold includes:

[0193] S441, if the first error corresponding to the better solution is not less than the third threshold, a candidate solution is generated according to the better solution. Here, the candidate solution is a candidate parameter value of the target preparation parameter that is different from the sample parameter value.

[0194] Exemplarily, the value range of each preparation parameter is determined according to the better solution (for example, ±5% based on the better solution), and a set of parameter values is randomly selected within the value range as the candidate solution.

[0195] S442, iterative optimization is performed according to the candidate solution to obtain the second parameter value.

[0196] It can be understood that if the first error obtained by simulating according to the candidate solution is less than the first error corresponding to the better solution, then the candidate solution becomes the new better solution; if the first error obtained by simulating according to the candidate solution is not less than the first error corresponding to the better solution, then a new set of candidate solutions is regenerated according to the better solution.

[0197] Exemplarily, in each iteration, simulation can be performed according to the candidate solution, the first error can be calculated, and the better solution can be determined. When the maximum number of iterations (such as 10 times) is reached or the first error of the better solution is less than the third threshold, the optimized second parameter value can be obtained.

[0198] Through the above steps S441 to S442, the first error can be further reduced, and the second parameter value of the target preparation parameter can be made closer to the expected value of the target production plan. Through the iterative optimization process, a better combination of preparation parameters can be found, which is beneficial to improving the preparation quality and performance of the copper alloy wire.

[0199] S450, if the first error corresponding to the better solution is less than the third threshold, the better solution is determined as the second parameter value.

[0200] It can be understood that if the first error corresponding to the better solution is already less than the third threshold, then the better solution is directly determined as the second parameter value.

[0201] Through the above steps S410 to S450, the second parameter value of the target preparation parameter can be determined by using the simulation and iterative optimization methods, so that the preparation quality and performance of the copper alloy wire meet the requirements of the target production plan. By comparing and analyzing the simulation results and error conditions corresponding to different sample parameter values, the preparation parameter combination can be selected and optimized more scientifically.

[0202] S500, control the copper alloy wire preparation equipment to prepare copper alloy wire based on the second parameter value.

[0203] Exemplarily, the preparation parameters of the copper alloy wire preparation equipment can be adjusted according to the second parameter value to control the copper alloy wire preparation equipment to prepare copper alloy wire.

[0204] It should be understood that the sequence numbers of the steps in the above embodiments do not indicate the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0205] Corresponding to the copper alloy wire preparation method described in the above embodiments, an embodiment of the present application further provides a copper alloy wire preparation device, and each module of the device can implement each step of the copper alloy wire preparation method. Figure 4 The structural block diagram of the copper alloy wire preparation device provided by the embodiment of the present application is shown. For the convenience of description, only the parts related to the embodiment of the present application are shown.

[0206] Referring Figure 4 , the device includes:

[0207] An acquisition module, configured to acquire historical production data and a target production plan of the copper alloy wire; wherein, the historical production data is at least one production record corresponding to different types of copper alloy wires, and the production record includes the type, specification and the first parameter value of the historical preparation parameters of the copper alloy wire, the historical preparation parameters are one of the preparation parameters of temperature, time, speed and / or pressure corresponding to each production link respectively, the production links include rolling, stretching and heat treatment, the target production plan includes the type and specification of the copper alloy wire, and the specification includes diameter, tensile strength and elongation after fracture;

[0208] A range module, configured to determine target preparation parameters and a first range of the target preparation parameters according to the historical production data and the target production plan; wherein, the target preparation parameters are the temperature, time, speed and / or pressure corresponding to each of the production links respectively, and the first range is the value range of each preparation parameter in the target preparation parameters;

[0209] A sampling module, configured to sample the sample parameter values of the target preparation parameters according to the historical production data and the first range;

[0210] A simulation module, configured to determine a second parameter value of the target preparation parameters according to the target production plan and the sample parameter values;

[0211] A control module, configured to control a copper alloy wire preparation device to prepare a copper alloy wire based on the second parameter value.

[0212] It should be noted that for the information interaction, execution process, etc. between the above devices / modules, since they are based on the same concept as the method embodiments of the present application, their specific functions and the technical effects brought, for details, please refer to the method embodiment part, and will not be elaborated here.

[0213] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working processes of the units and modules in the above device can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0214] The embodiment of the present application also provides a copper alloy wire preparation device. Figure 5 It is a schematic structural diagram of the copper alloy wire preparation device / copper alloy wire preparation equipment provided in an embodiment of the present application. As Figure 5 shown, the copper alloy wire preparation device / copper alloy wire preparation equipment 6 of this embodiment includes: at least one processor 60 ( Figure 5 only one is shown in the figure), at least one memory 61 ( Figure 5 only one is shown in the figure), 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, the copper alloy wire preparation device / copper alloy wire preparation equipment 6 realizes the steps in any of the above-mentioned copper alloy wire preparation method embodiments, or the copper alloy wire preparation device / copper alloy wire preparation equipment 6 realizes the functions of each module / unit in the above device embodiments.

[0215] Exemplarily, the computer program 62 can be divided into one or more modules / units. The one or more modules / units are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing specific functions, and these instruction segments are used to describe the execution process of the computer program 62 in the copper alloy wire preparation equipment 6.

[0216] The copper alloy wire preparation device / copper alloy wire preparation equipment 6 can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The copper alloy wire preparation device / copper alloy wire preparation equipment can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Figure 5This is only an example of the copper alloy wire preparation device / copper alloy wire preparation equipment 6, and does not constitute a limitation on the copper alloy wire preparation device / copper alloy wire preparation equipment 6. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, buses, etc.

[0217] The processor 60 may be a central processing unit (CPU), and the processor 60 may also 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 may be a microprocessor or the processor may also be any conventional processor, etc.

[0218] In some embodiments, the memory 61 may be an internal storage unit of the copper alloy wire preparation device / copper alloy wire preparation equipment 6, such as the hard disk or memory of the copper alloy wire preparation device / copper alloy wire preparation equipment 6. In other embodiments, the memory 61 may also be an external storage device of the copper alloy wire preparation device / copper alloy wire preparation equipment 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the copper alloy wire preparation device / copper alloy wire preparation equipment 6. Further, the memory 61 may also include both the internal storage unit and the external storage device of the copper alloy wire preparation device / copper alloy wire preparation equipment 6. The memory 61 is used to store operating systems, application programs, boot loaders, data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store data that has been output or will be output.

[0219] The embodiment of the present application also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0220] The embodiment of the present application provides a computer program product, and when the computer program product runs on the copper alloy wire preparation equipment, the copper alloy wire preparation equipment implements the steps in any of the above method embodiments.

[0221] When the integrated unit is implemented in the form of 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, to implement all or part of the processes in the above-described embodiment methods of the present application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium that can carry the computer program code to the copper alloy wire preparation device / copper alloy wire preparation equipment. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0222] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0223] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0224] In the embodiments provided by the present application, it should be understood that the disclosed copper alloy wire preparation device / copper alloy wire preparation equipment and method can be implemented in other ways. For example, the copper alloy wire preparation device / copper alloy wire preparation equipment embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection to each other can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in an electrical, mechanical, or other form.

[0225] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0226] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements 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 the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for preparing a copper alloy wire, characterized in that: include: Obtaining historical production data and a target production plan of the copper alloy wire; wherein the historical production data is at least one production record corresponding to different types of copper alloy wires, the production record includes the type, specification and first parameter value of a historical preparation parameter of the copper alloy wire, the historical preparation parameter is one of the preparation parameters of temperature, time, speed and / or pressure corresponding to each production link, the production link includes rolling, stretching and heat treatment, the target production plan includes the type and specification of the copper alloy wire, the specification includes diameter, tensile strength and elongation after fracture; Determine a target preparation parameter and a first range of the target preparation parameter according to the historical production data and the target production plan; wherein the target preparation parameter is the temperature, time, speed and / or pressure corresponding to each of the production links, and the first range is the value range of each preparation parameter in the target preparation parameter; Obtaining a sample parameter value of the target preparation parameter by sampling according to the historical production data and the first range; Determining a second parameter value of the target preparation parameter according to the target production plan and the sample parameter value; The copper alloy wire manufacturing equipment is controlled to manufacture the copper alloy wire based on the second parameter value.

2. The method for preparing a copper alloy wire according to claim 1, wherein: The step of determining the target production parameter and the first range of the target production parameter according to the historical production data and the target production plan includes: Determining, according to the target production plan, at least one first production data corresponding to the type of copper alloy wire of the target production plan in the historical production data; determining the target preparation parameter according to the first production data; calculating a first similarity between specifications of the copper alloy wire in the first production data and specifications in the target production plan; If the first similarity exceeds the first threshold, the corresponding first production data is determined as the second production data; A first range of the target manufacturing parameter is determined based on the second production data.

3. The method for preparing a copper alloy wire according to claim 2, wherein: The determining the first range of the target preparation parameter based on the second production data comprises: If the second production data includes the production record only once, setting a first tolerance interval for the first parameter value, and determining the first tolerance interval as a first range of the target preparation parameter; If the second production data includes multiple production records, the first range of the target production parameter is determined according to the maximum and minimum values ​​of the first parameter values ​​of each of the historical production parameters.

4. The method for preparing a copper alloy wire according to claim 2, wherein: The determining of the target preparation parameter and the first range of the target preparation parameter according to the historical production data and the target production plan further includes: If the first similarity does not exceed the first threshold, calculating a first distance between the first production data and the corresponding diameter in the target production plan, and a second distance between the tensile strength and the elongation after fracture; Determining, according to the first production data, a first type of parameter affecting diameter and a second type of parameter affecting tensile strength and elongation after fracture among the target manufacturing parameters; If the first distance exists or the second distance exceeds a second threshold, determining the corresponding first production data as third production data; determining a second range of the corresponding first type parameter and / or second type parameter based on the third production data; If each of the first distances or each of the second distances does not exceed the second threshold, determining the corresponding first production data as fourth production data; Determining a third range of the corresponding first type parameter and / or second type parameter based on the fourth production data and the target production plan; The first range of the target preparation parameter is determined according to the second range and / or the third range.

5. The method for preparing a copper alloy wire according to claim 4, characterized in that: The determining, according to the first production data, a first type parameter affecting the diameter and a second type parameter affecting the tensile strength and the elongation after fracture in the target preparation parameters comprises: Obtaining, according to the first production data, a correlation coefficient between the target preparation parameter and the diameter, tensile strength and elongation after fracture of the copper alloy wire; The first type parameter and the second type parameter are determined according to the correlation coefficient.

6. The method for preparing a copper alloy wire according to claim 4, wherein: The determining, based on the third production data, a second range of the corresponding first type parameter and / or second type parameter comprises: If the third production data contains only one production record, setting a second tolerance interval for the first parameter value, and determining the second tolerance interval as a second range of the first type parameter and / or the second type parameter; If the third production data includes multiple production records, the second range of the corresponding first type parameter and / or second type parameter is determined according to the maximum and minimum values ​​of the first parameter values ​​of each historical preparation parameter.

7. The method for preparing a copper alloy wire according to claim 4, wherein: The determining, based on the fourth production data and the target production plan, a third range of the corresponding first type parameter and / or second type parameter comprises: selecting characteristic data from the fourth production data; According to the feature data, different weights are assigned to different feature data to obtain feature vectors; Taking the feature vector as input, training an initial model; The trained initial model is validated according to a cross-validation method to obtain a standard model; wherein the cross-validation method is to train and test the initial model by repeatedly using a subset of the feature data to predict the performance of the initial model; Inputting the preprocessed target production plan into the standard model for prediction; Obtaining a corresponding predicted value of the first type parameter and / or the second type parameter according to the standard model output; A third tolerance interval of the predicted value is calculated, and the third tolerance interval is determined as a third range of the first type parameter and / or the second type parameter.

8. The method for preparing a copper alloy wire according to claim 1, wherein: The step of obtaining the sample parameter value of the target preparation parameter by sampling according to the historical production data and the first range includes: Determine the sampling quantity according to the historical production data and the first range; Sample parameter values ​​of the target preparation parameters are obtained by stratified sampling within the first range according to the sampling quantity.

9. The method for preparing a copper alloy wire according to claim 1, wherein: The step of determining the second parameter value of the target preparation parameter according to the target production plan and the sample parameter value comprises: Perform simulation according to the sample parameter values ​​to obtain the actual diameter, actual tensile strength and actual elongation after fracture; Calculating the errors between the actual diameter, the actual tensile strength and the actual elongation after fracture and the specifications of the copper alloy wire in the target production plan, and allocating weights to calculate and obtain a first error; The sample parameter values ​​are sorted according to the first errors to obtain a better solution; wherein the better solution is the sample parameter value corresponding to the smallest first error; Determine whether the first error corresponding to the optimal solution is less than a third threshold; If the first error corresponding to the better solution is smaller than the third threshold, the better solution is determined as the second parameter value.

10. The method for preparing a copper alloy wire according to claim 9, wherein: The determining whether the first error corresponding to the optimal solution is less than a third threshold comprises: If the first error corresponding to the better solution is not less than the third threshold, generating a candidate solution according to the better solution; wherein the candidate solution is a candidate parameter value of the target preparation parameter different from the sample parameter value; The second parameter value is obtained by performing iterative optimization according to the candidate solution.

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