Method and equipment for preparing high-conductivity copper material

Abstract

The invention is suitable for the technical field of power transmission conductor materials, and particularly relates to a high-conductivity copper material preparation method and equipment, and the method comprises the steps: obtaining material information and a preparation step information base; according to the material information and a preparation step information base, determining connection characteristics in preparation ergodic steps; wherein the preparation steps are used for reflecting the preparation steps of the material information, and the connection characteristics are used for representing the connection strength between the process operation and the procedure steps; analyzing according to the contact features, the preparation steps and a preparation step information base to obtain indication information, and controlling the preparation equipment to perform preparation operation corresponding to the indication information according to the indication information and operation information of the preparation equipment; wherein the indication information is used for indicating the next preparation action of the preparation equipment. According to the high-conductivity copper material preparation method and equipment provided by the invention, the stability of the finished product qualification rate of the prepared high-conductivity copper material can be improved.

Description

Technical Field

[0001] The present application belongs to the technical field of power transmission conductor materials, and in particular relates to a method and equipment for preparing high-conductivity copper materials. Background Art The preparation of high-conductivity copper materials refers to improving the conductivity of copper materials through processes such as raw material purification, alloying treatment, and heat treatment. Generally, the conductivity of copper materials is close to or reaches more than 97% of the International Annealed Copper Standard (IACS). It is widely used in power transmission, electronic devices, high-frequency cables and other fields.

[0002] In related technologies, mainstream production processes for high-conductivity copper wire, such as high-purity raw material purification, alloying modification, and the coordinated use of plastic deformation and heat treatment, often rely on pre-set fixed process parameters for production, covering key indicators such as melting temperature, cold deformation, and annealing time. However, in actual production, factors such as fluctuations in raw material purity or changes in ambient temperature and humidity may cause the finished high-conductivity copper material to have problems such as excessive impurities and abnormal grain size. Consequently, the desired high-conductivity copper material cannot be produced, and the entire batch of products may even be scrapped, resulting in not only a waste of raw materials and energy, but also increased production costs. Summary of the Invention

[0003] The embodiments of the present application provide a method and apparatus for preparing a high-conductivity copper material, which can improve the problem of unstable qualified rate of finished products of the high-conductivity copper material.

[0004] In a first aspect, an embodiment of the present application provides a method for preparing a high-conductivity copper material, comprising: Obtaining material information and a preparation step information library; wherein the material information is used to reflect the state of the copper material in the current preparation process, and the preparation step information library is used to reflect the different steps of preparing high-conductivity copper material and the different preparation parameters corresponding to the different steps; Determining, based on the material information and the preparation step information library, connection features in the preparation steps; wherein the preparation steps are used to reflect the preparation steps that the material information has undergone, and the connection features are used to characterize the connection strength between the process operations and the process steps; An analysis is performed based on the connection characteristics, the preparation steps and the preparation step information library to obtain instruction information, and the preparation equipment is controlled to perform the instruction operation corresponding to the instruction information based on the instruction information and the operation information of the preparation equipment; wherein the instruction information is used to indicate the next preparation action of the preparation equipment.

[0005] The above technical solutions in the embodiments of the present application have at least the following technical effects: The method for preparing a high-conductivity copper material provided in an embodiment of the present application first obtains a preparation step information library for reflecting the state of the copper material in the current preparation process and for reflecting the different steps in preparing the high-conductivity copper material and the different preparation parameters corresponding to the different steps. Then, based on the material information and the preparation step information library, a connection feature for characterizing the connection strength between the process operation and the process step in the preparation history step for reflecting the preparation steps that the material information has undergone is determined. Then, analysis is performed based on the connection feature, the preparation history step, and the preparation step information library to obtain instruction information for instructing the next preparation action of the preparation equipment. Finally, based on the instruction information and the operation information on the preparation equipment, the preparation equipment is controlled to perform the preparation operation corresponding to the instruction information.

[0006] This method can effectively select, based on the material information of the prepared material after the preparation steps, the most suitable preparation parameters for preparing the current material in the preparation step after the preparation steps from a preparation step information library including different steps and different preparation parameters corresponding to the different steps as indication information, and then control the preparation equipment to perform the next preparation action based on the indication information. Based on the current material characteristics of the material, a preparation parameter that best suits the current material characteristics can be selected in real time, thereby being able to adopt the preparation parameters that are most suitable for the different physical conditions of the material in different preparation steps. Furthermore, even in the face of material deviations, the finished product qualification rate of the prepared high-conductivity copper material can be stabilized and not reduced.

[0007] In a possible implementation of the first aspect, determining, based on the material information and the preparation step information library, connection features among the preparation steps includes: Matching the preparation steps and their correlation from the preparation step information library based on the current material characteristics of the material information; wherein the current material characteristics are used to reflect the physical state of the copper material after completing the preparation steps, and the correlation degree is used to characterize the connection strength between adjacent processes of the preparation steps; The first preparation feature in the preparation steps and the correlation degree in the preparation steps are processed to obtain a connection feature; wherein the first preparation feature is used to reflect the preparation parameters corresponding to each preparation step.

[0008] In a possible implementation of the first aspect, obtaining the preparation steps and their correlation levels from the preparation step information library according to the current material characteristics of the material information includes: According to the current material feature of the material information, a relevant step having the greatest similarity to the current material feature is matched from a plurality of second preparation features in the preparation step information library; wherein the second preparation feature is used to reflect the physical state that the copper material corresponding to each preparation step needs to achieve; The relevant step and the step before the relevant step in the preparation step information database are jointly identified as preparation steps; Based on the preparation sequence of the preparation steps, the state compatibility analysis is performed on the i-th step and the i+1-th step in the preparation steps to obtain an initial matching value, and then weighted correction is performed based on the initial matching value and the process weight to obtain the degree of correlation; wherein, the initial matching value is used to reflect the degree of connection between the i-th step and the i+1-th step, and the process weight is used to reflect the connection strength weight of the preparation parameters between adjacent processes.

[0009] In a possible implementation of the first aspect, the analyzing according to the connection feature, the preparation steps, and the preparation step information database to obtain the indication information includes: Processing the preparation steps and the connection features to obtain a first correlation feature and a second correlation feature; wherein the first correlation feature is used to characterize the intensity of the influence of the completed process on the next process, and the second correlation feature is used to characterize the degree of influence of different processes in the process on the preparation result of the process itself; Instruction information is obtained according to the first association feature, the second association feature and the preparation step information library.

[0010] In a possible implementation of the first aspect, the processing according to the preparation steps and the connection feature to obtain the first correlation feature and the second correlation feature includes: Analyzing the first and second preparation characteristics of the preparation steps to obtain a first correlation and a second correlation; wherein the first correlation is used to characterize the causal strength between the process and the preparation result within a single process, and the second correlation is used to reflect the dependence strength of the preparation results between adjacent processes; A first association feature is generated based on the connection feature and the first correlation, and a second association feature is generated based on the connection feature and the second correlation.

[0011] In a possible implementation of the first aspect, analyzing the first preparation feature and the second preparation feature in the preparation steps to obtain the first correlation and the second correlation includes: Performing a simulation comparison process on a plurality of first preparation features and a corresponding plurality of second preparation features according to a preparation sequence of the preparation steps, to obtain a first correlation between an i-th first preparation feature and an i-th second preparation feature in the preparation steps; A state compatibility analysis is performed on multiple second preparation features according to the preparation order of the preparation steps to obtain a state compatibility coefficient between the i-th second preparation feature and the i+1-th second preparation feature in the preparation steps, and then a weighted fusion is performed based on the state compatibility coefficient and the process weight to obtain a second correlation; wherein the state compatibility coefficient is used to reflect the degree of matching between the output state of the i-th step in the preparation steps and the input requirement of the i+1-th step, and the process weight is used to reflect the matching strength weight of material features between adjacent processes.

[0012] In a possible implementation of the first aspect, obtaining the indication information according to the first association feature, the second association feature, and the preparation step information library includes: Acquire a plurality of indicative preparation features from the preparation step information library; wherein the indicative preparation features are used to reflect the preparation parameters of the next step of the last step in the preparation process; After fusing the second correlation feature with the plurality of the indicative preparation features respectively, performing feature comparison with the first correlation feature to obtain a plurality of feature intensities; wherein the feature intensities are used to reflect the suitability between the indicative preparation features and the material information; The indicative preparation feature corresponding to the feature intensity of the maximum value among the plurality of feature intensities is used as the indication information.

[0013] In a possible implementation of the first aspect, controlling the preparation device to perform the preparation operation corresponding to the instruction information according to the instruction information and the operation information on the preparation device includes: When the indication information is the same as the preset preparation feature, the preparation equipment is controlled to perform the preparation operation at the moment when the current material feature of the material information is the same as the physical state required to be achieved by the copper material in the preparation step corresponding to the indication information; wherein the preset preparation feature refers to a pre-set preparation parameter in the preparation step corresponding to the indicated preparation feature.

[0014] In a possible implementation of the first aspect, controlling the preparation device to perform a preparation operation corresponding to the instruction information according to the instruction information and the operation information on the preparation device further includes: When the indication information is different from the preset preparation characteristics, a first icon is displayed on the control interface of the preparation device, and in response to a first operation on the first icon, a second icon is superimposed; wherein the first icon is used to indicate that the preset preparation characteristics are adjusted, and the second icon is used to reflect the adjustment of the preset preparation characteristics; In response to a second operation on the second icon, the preset preparation feature is modified to the indication information, and then the preparation operation is performed.

[0015] In a second aspect, an embodiment of the present application provides a high-conductivity copper material preparation system, comprising: An acquisition module is used to acquire material information and a preparation step information library; wherein the material information is used to reflect the full life cycle data of the copper material during the preparation process, and the preparation step information library includes different steps for reflecting the preparation of high-conductivity copper materials and different preparation parameters corresponding to different steps; an analysis module for determining, based on the material information and the preparation step information library, connection features among the preparation steps; wherein the preparation steps are used to reflect the preparation steps that the prepared material has undergone, and the connection features are used to characterize the connection strength between the process operations and the process steps; An analysis and control module is used to analyze the connection characteristics, the preparation steps and the preparation step information library to obtain instruction information, and control the preparation equipment to perform a preparation operation corresponding to the instruction information based on the instruction information and the operation information of the preparation equipment; wherein the instruction information is used to indicate the next preparation action of the preparation equipment.

[0016] In a third aspect, an embodiment of the present application provides a high-conductivity copper material preparation device, comprising a preparation device and a control device, wherein the preparation device is electrically connected to the control device, the preparation device comprising a raw material processing device, a smelting device, a casting device, a plastic processing device, an annealing device, and a transportation detection device, and the control device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the method described in any one of the first aspects above.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the first aspects above is implemented.

[0018] In a fifth aspect, an embodiment of the present application provides a computer program. When the computer program is run on a high-conductivity copper material preparation device, the high-conductivity copper material preparation device executes the high-conductivity copper material preparation method described in any one of the first aspects above.

[0019] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 This is a schematic flow chart of a method for preparing a high-conductivity copper material provided in one embodiment of the present application; Figure 2 This is a schematic diagram of the implementation process of the method for preparing a high-conductivity copper material provided in one embodiment of the present application; Figure 3 This is a structural diagram of a high-conductivity copper material preparation system provided in one embodiment of the present application; Figure 4 It is a structural schematic diagram of a control device of a high-conductivity copper material preparation device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0022] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may 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 obscuring the description of the present application with unnecessary detail.

[0023] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0024] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0025] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0026] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in 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 "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0028] In related technologies, mainstream production processes for high-conductivity copper wire, such as high-purity raw material purification, alloying modification, and the coordinated use of plastic deformation and heat treatment, often rely on pre-set fixed process parameters for production, covering key indicators such as melting temperature, cold deformation, and annealing time. However, in actual production, factors such as fluctuations in raw material purity or changes in ambient temperature and humidity may cause the finished high-conductivity copper material to have problems such as excessive impurities and abnormal grain size. Consequently, the desired high-conductivity copper material cannot be produced, and the entire batch of products may even be scrapped, resulting in not only a waste of raw materials and energy, but also increased production costs.

[0029] To address the above-mentioned issues, embodiments of the present application provide a method and apparatus for preparing high-conductivity copper materials. This method first obtains a preparation step information library that reflects the state of the copper material during the current preparation process, reflects the different steps in preparing the high-conductivity copper material, and the different preparation parameters corresponding to the different steps. Then, based on the material information and the preparation step information library, a connection feature is determined in the preparation history step that reflects the preparation steps that the material information has already undergone, which characterizes the connection strength between the process operation and the process step. Then, analysis is performed based on the connection feature, the preparation history step, and the preparation step information library to obtain instruction information for instructing the next preparation action of the preparation equipment. Finally, based on the instruction information and operation information for the preparation equipment, the preparation equipment is controlled to perform the preparation operation corresponding to the instruction information.

[0030] The high-conductivity copper material preparation method provided in the embodiment of the present application can be applied to high-conductivity copper material preparation equipment. In this case, the high-conductivity copper material preparation equipment is the executor of the high-conductivity copper material preparation method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of high-conductivity copper material preparation equipment.

[0031] High-conductivity copper material production equipment includes a production line and a control device. The production line is electrically connected to the control device. The production line comprises a raw material processing unit, a smelting unit, a casting unit, a plastic working unit, an annealing unit, and a transport and inspection unit. The production sequence is the production sequence of the production line. The raw material processing unit, smelting unit, casting unit, plastic working unit, and annealing unit are connected by a transport unit in the transport and inspection unit. The raw material processing unit is used to crush electrolytic copper into fragments and screen out copper materials of appropriate size. For example, the raw material processing unit can be a combination of a crusher and a screen. The smelting unit is used to heat and melt the copper material. For example, the smelting unit can be a combination of a heating coil and a smelting furnace. The casting unit is used to cast the molten copper into copper ingots. For example, the casting unit can be a combination of a continuous casting machine and an ingot heating furnace. The plastic working unit is used to draw the copper ingots into copper wire. For example, the plastic working unit can be a combination of a hot rolling mill and a cold drawing mill. The annealing unit is used to anneal the drawn copper wire. For example, the annealing device can be a box-type annealing furnace. The transport and detection device includes a transport mechanism and a detection mechanism. The transport mechanism is used to transfer copper material from the previous process to the next process. For example, the transport mechanism can be a transport pipeline or a robotic arm. The detection mechanism is used to monitor the conductivity, temperature, physical condition, and other indicators of the copper wire in real time. For example, the detection device can be a combination of a conductivity tester and a temperature sensor. The control device is used to monitor and control the high-conductivity copper material production process.

[0032] For example, the control device can be a mobile phone, a tablet computer, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a smart screen, a smart TV, a handheld device with wireless communication function, a desktop computer, a handheld device with wireless communication function, a computer, a laptop computer, a handheld computing device, etc.

[0033] In order to better understand the method for preparing the high-conductivity copper material provided in the embodiment of the present application, the specific implementation process of the method for preparing the high-conductivity copper material provided in the embodiment of the present application is exemplarily introduced below.

[0034] Figure 1 and Figure 2 A schematic flow chart showing a method for preparing a high conductivity copper material according to an embodiment of the present invention is shown. Figure 1 and Figure 2 , the method for preparing high conductivity copper material includes: S100, obtaining material information and a preparation step information library; wherein the material information is used to reflect the full life cycle data of the copper material during the preparation process, and the preparation step information library includes different steps for reflecting the preparation of high-conductivity copper materials and different preparation parameters corresponding to different steps.

[0035] It can be understood that in the process of producing high-conductivity copper materials, the production process is prepared according to fixed preparation procedures. For example, the selection of raw materials and pretreatment, smelting and alloying treatment, deoxidation and refining, casting, plastic processing and annealing treatment and other preparation processes are all carried out according to fixed processes, and different preparation processes exist in the same process to meet the preparation requirements of different preparation materials.

[0036] Exemplarily, material information can be obtained through manual input by humans, and can also be obtained through the machine detection system of the preparation equipment. The preparation step information library can be manually input by humans. It can also be directly obtained through production files. Production files refer to files that include different preparation parameters corresponding to different preparation steps of different high-conductivity copper materials and different high-conductivity copper materials during the production process. The production files can directly burn the key parameters corresponding to each step in the historical production process into the high-conductivity copper material preparation system to form production files corresponding to different preparation steps. The machine detection system refers to a detection system composed of detection devices such as temperature sensors and machine vision detection devices.

[0037] S200, determining the connection characteristics of the preparation steps based on the material information and the preparation step information library; wherein the preparation steps are used to reflect the preparation steps that the preparation material has gone through, and the connection characteristics are used to characterize the connection strength between the process operation and the process steps.

[0038] It can be understood that there is a close connection between the various preparation steps of high-conductivity copper materials. This connection stems from the systematic demand for material property regulation, that is, the goal of each step is not only to complete a single process operation, but also to lay the foundation for subsequent steps, and ultimately achieve maximum conductivity through the synergistic effect of multiple steps.

[0039] Exemplarily, the material information is used to obtain the preparation steps that the material has gone through from the preparation step information library. The connection strength between adjacent processes within the preparation steps is then analyzed based on the preparation steps. The connection strength between adjacent processes is then processed with the preparation process of the corresponding preparation step within the preparation steps to obtain the preparation parameters. Alternatively, the preparation steps can be directly obtained from the Manufacturing Execution System (MES system), and the connection strength between adjacent processes within the preparation steps is then analyzed based on the preparation steps. A Manufacturing Execution System refers to a system in which, during the preparation of high-conductivity copper materials, operators enter relevant information about the preparation process, including step name, completion time, and operator, into the MES system after completing each step.

[0040] In a possible implementation, in step S200, determining the connection features of the preparation steps based on the material information and the preparation step information library includes: S210, matching the preparation steps and the degree of correlation from the preparation step information library based on the current material characteristics of the material information; wherein the current material characteristics are used to reflect the physical state reached by the copper material after completing the preparation steps, and the degree of correlation is used to characterize the connection strength between adjacent processes of the preparation steps.

[0041] It is understandable that the prepared materials exhibit different physical states after undergoing different preparation steps. For example, copper material changes from solid raw material to liquid copper after smelting, and changes from liquid copper to solid ingot after casting, and so on.

[0042] For example. The step with the greatest similarity between the physical state of the prepared material after the completion of the different process steps and the current material characteristics can be obtained by matching the different process steps in the preparation step information library, and the step and all the steps before the step are jointly confirmed as the preparation process steps. After obtaining the preparation process steps, the preparation process steps are analyzed according to a fixed preparation sequence to obtain the degree of correlation. The degree of correlation can also be obtained through learning model analysis, that is, the preparation process steps are input into the learning model, and the learning model outputs the corresponding degree of correlation. The training process of the learning model can use the data after data processing of the preparation process steps and the corresponding degree of correlation as the training data set of the learning model, and then input the training data set of the learning model into the learning model for training and learning, and finally obtain the learning model.

[0043] In one possible implementation, in step S210, determining the connection features of the preparation steps based on the material information and the preparation step information library includes: S211, according to the current material feature of the material information, a plurality of second preparation features in the preparation step information library are matched to obtain a related step with the greatest similarity to the current material feature; wherein the second preparation feature is used to reflect the physical state that the copper material corresponding to each preparation step needs to achieve.

[0044] It can be understood that the second preparation characteristic refers to the state that the prepared material needs to reach during different preparation processes. For example, during the casting process, the material needs to reach a liquid state, and during the raw material pretreatment stage, the electrolytic copper needs to reach a purity of 99.95% or above and an oxygen content of ≤0.005%. The relevant step refers to the final step in the preparation process, that is, the step in which the prepared material is completed at the end of the preparation process.

[0045] For example, when comparing the similarity of multiple second preparation features in the preparation step information library with the current material features, it is necessary to compare the multi-dimensional state of the preparation material, that is, it is necessary to compare the temperature dimension, state dimension (solid, liquid), conductivity and other dimensions of the current state of the preparation material.

[0046] S212, jointly confirming the relevant steps and the steps preceding the relevant steps in the preparation step information library as preparation steps.

[0047] It can be understood that because the preparation process for preparing copper materials is fixed, that is, the preparation order is also fixed, that is, when the current material characteristics reflect the material state of having completed the relevant step in the preparation step information library, the prepared material has also gone through all the steps before the relevant step, that is, the relevant step and the steps before the relevant step are jointly confirmed as the preparation steps.

[0048] S213, based on the preparation sequence of the preparation steps, the state compatibility analysis of the i-th step and the i+1-th step in the preparation steps is performed to obtain the initial matching value, and then weighted correction is performed according to the initial matching value and the process weight to obtain the degree of correlation; wherein, the initial matching value is used to reflect the degree of connection between the i-th step and the i+1-th step, and the process weight is used to reflect the connection strength weight of the preparation parameters between adjacent processes.

[0049] For example, the output state parameter set after the completion of the i-th preparation step and the input state parameter set before the start of the i+1-th preparation step can be obtained. The state matching degree of each dimension corresponding to one or more compatibility dimensions between the output state parameter set and the input state parameter set is calculated. Finally, the state matching degree of each compatibility dimension obtained by multiplication and aggregation is generated to generate a single initial matching value. Then, a weighted sum is performed based on the pre-set process weight and the corresponding initial matching value to finally obtain the degree of correlation. The output state parameter set and the input state parameter set contain key attributes that characterize the material or equipment at the corresponding step conversion node. The key attributes include but are not limited to: the physical state of the material (such as solid state, liquid state), the chemical composition of the material (such as the ratio of metal elements, impurity content), and the equipment setting parameters (such as melting temperature, rolling pressure, holding time, annealing temperature, etc.). Among them, the compatibility dimension is pre-defined based on the specific characteristics of the preparation process and may include: physical state compatibility: evaluating whether the physical state of the output of the i-th step meets the requirements of the physical state of the input of the i+1-th step (for example: whether the liquid output is suitable for pressing input, and whether the solid output is suitable for rolling input); chemical compatibility: evaluating whether the chemical composition of the output of the i-th step (such as oxygen content, impurity content) is within the acceptable threshold range of the chemical composition of the input of the i+1-th step; equipment parameter compatibility: evaluating whether the final setting parameters of the equipment at the output of the i-th step (such as melting temperature, rolling pressure) are consistent with the initial setting parameter requirements of the equipment at the input of the i+1-th step or can be smoothly transitioned.

[0050] With this setup, a preparation path optimization system based on similarity calculation and weight correction was constructed through intelligent matching of material characteristics and preparation step information database and dynamic analysis of process compatibility, which effectively improved the adaptability, continuity and production efficiency of copper processing technology.

[0051] S220, processing the first preparation feature in the preparation steps and the correlation degree in the preparation steps to obtain a connection feature; wherein the first preparation feature is used to reflect the preparation parameters corresponding to each preparation step.

[0052] Exemplarily, a first preparation feature vector defined for each preparation step in the preparation process is obtained; wherein the first preparation feature vector contains quantitative values ​​or codes of one or more core preparation parameters characterizing a preparation step in the preparation process, and the preparation parameters include but are not limited to: operating temperature, operating pressure, reaction time, stirring speed, raw material ratio, target product morphology requirements, etc., and then a feature fusion processing operation is performed through the first preparation feature vector and the correlation degree data to generate a connection feature characterizing the strength of the connection between a specific process operation and a specific process step.

[0053] With this setting, a process optimization system based on connection characteristics was constructed through the association modeling of material state and preparation parameters and the analysis of process connection strength, which effectively improved the parameter adaptability, process coordination and production intelligence level in the copper material preparation process.

[0054] S300, analyze according to the contact characteristics, the preparation steps and the preparation step information library to obtain instruction information, and control the preparation equipment to perform the preparation operation corresponding to the instruction information according to the instruction information and the operation information of the preparation equipment; wherein the instruction information is used to indicate the next preparation action of the preparation equipment.

[0055] It is understandable that during the production process, the preparation materials may fluctuate in purity or change in the environment, resulting in the preparation parameters of the originally set preparation process being insufficiently compatible with the current preparation materials. That is, it is necessary to find the preparation parameters with the greatest compatibility with the current preparation materials from the preparation step information library as indication information.

[0056] For example, the connection characteristics and the preparation steps can be processed first to obtain the intensity of the influence of the completed process on the next process and the degree of influence of the different processes of the process on the preparation result of the process itself. Then, according to the intensity of the influence of the completed process on the next process, the degree of influence of the different processes of the process on the preparation result of the process itself and the preparation step information library, analysis is performed to obtain indication information. It is also possible to match the matching material characteristics that are the same as the current material characteristics in the historical preparation database, and then match the preparation parameters corresponding to the matching material characteristics from the historical preparation database as indication information based on the matching material characteristics. If the matching material characteristics that are the same as the current material characteristics are not matched in the historical preparation database, then the analysis model is used to directly output the indication information corresponding to the current material characteristics based on the current material characteristics. The analysis model refers to the process of inputting the experienced preparation parameters of the current material characteristics and the current material characteristics into the analysis model, and the analysis model then outputs the corresponding indication information.

[0057] With such a setting, a preparation parameter that best suits the current material characteristics can be selected in real time according to the current material characteristics of the material, so that the preparation parameter that best suits the physical conditions of the material can be adopted according to the different physical conditions of the material in different preparation steps. Furthermore, even when the material deviates, the qualified rate of the prepared high-conductivity copper material can be stabilized and not reduced.

[0058] In a possible implementation, in step S300, analysis is performed based on the contact characteristics, the preparation steps, and the preparation step information database to obtain indication information, including: S310, processing is performed based on the preparation steps and the connection features to obtain a first correlation feature and a second correlation feature; wherein the first correlation feature is used to characterize the intensity of the influence of the completed process on the next process, and the second correlation feature is used to characterize the degree of influence of different processes of the process on the preparation result of the process itself.

[0059] For example, the first preparation feature and the second preparation feature of each step in the preparation process can be obtained, and then the first preparation feature and the second preparation feature are analyzed to obtain the causal strength characterizing the process and the preparation result within a single process and the dependence strength reflecting the preparation results between adjacent processes. Then, the connection feature is analyzed with the causal strength characterizing the process and the preparation result within a single process to obtain the first correlation feature, and the connection feature is analyzed with the causal strength characterizing the process and the preparation result within a single process to obtain the second correlation feature.

[0060] In a possible implementation, in step S310, processing is performed based on the preparation steps and the associated features to obtain the first associated features and the second associated features, including: S311, analyze the first preparation feature and the second preparation feature in the preparation steps to obtain the first correlation and the second correlation; wherein the first correlation is used to characterize the causal strength between the process and the preparation result within a single process, and the second correlation is used to reflect the dependence strength of the preparation results between adjacent processes.

[0061] Exemplarily, according to the preparation order of the preparation steps, a first correlation between the i-th first preparation feature and the i-th second preparation feature, and a second correlation between the i-th second preparation feature and the i+1-th second preparation feature can be obtained from the first preparation feature and the second preparation feature.

[0062] In a possible implementation, in step S311, analyzing the first preparation feature and the second preparation feature in the preparation process to obtain the first correlation and the second correlation includes: S3111, simulate and compare multiple first preparation features and corresponding multiple second preparation features according to the preparation order of the preparation steps to obtain a first correlation between the i-th first preparation feature and the i-th second preparation feature in the preparation steps.

[0063] Exemplarily, for each preparation step in the preparation process, a corresponding first preparation feature vector is defined and obtained. The first preparation feature vector contains one or more quantified values ​​or codes representing the process parameters applied or controlled during the execution of the corresponding preparation step. Process parameters include, but are not limited to, operating setpoints (e.g., target temperature, target pressure, set speed, set flow rate), operating range limits (e.g., temperature fluctuation range, upper pressure limit), raw material input characteristics (e.g., batch number, purity level, initial form), real-time equipment parameters (e.g., actual power, valve opening), and environmental control parameters (e.g., shielding gas flow rate, vacuum level). A corresponding second preparation feature vector is defined and obtained. The second preparation feature vector contains one or more quantified values ​​or codes representing the preparation result indicators produced or achieved after the corresponding preparation step is completed. Preparation result indicators include, but are not limited to, product characteristics (e.g., conductivity, purity, grain size, surface roughness), process status (e.g., actual end temperature, actual end pressure), and process monitoring data (e.g., time required for the prepared material to reach the target state, energy consumption, and abnormal event count). According to the established order of the preparation process, feature alignment is performed on the first preparation feature vector and the second preparation feature vector of each process to ensure that the first preparation feature vector and the second preparation feature vector accurately correspond to the same preparation process in terms of data. Then, through simulation and comparative modeling, using machine learning methods such as Causal Forest (CausalForest) and Bayesian Additive Regression Tree (BART), under the premise of controlling potential confounding variables, the specific result indicators of the second preparation feature vector when the specific process parameters (intervention variables) in the first preparation feature vector are changed are estimated, and then the characteristic result indicators are confirmed as the first correlation.

[0064] In a possible implementation, in step S3111, a simulation comparison process is performed on a plurality of first preparation features and a corresponding plurality of second preparation features according to a preparation sequence of the preparation steps to obtain a first correlation between the i-th first preparation feature and the i-th second preparation feature in the preparation steps, further comprising: S31111, perform preparation control simulation according to the first preparation feature of the i-th step to obtain a predicted material output state; wherein the predicted material output state is the preparation material state obtained after the prepared material is prepared according to the first preparation feature in the i-th preparation step.

[0065] It can be understood that the preset process response model is input based on the first preparation feature of the i-th preparation step, and the process response model directly performs dynamic simulation calculations and then outputs the predicted material output state. The process response model can be constructed by training the model using different preparation processes of different preparation steps as input conditions and the material output state corresponding to the preparation process as output conditions, thereby obtaining a process response model.

[0066] S31112, perform deviation analysis on the predicted material output state and the second preparation feature of the i-th step to obtain the parameter compliance rate; wherein, the parameter compliance rate is used to reflect the degree of deviation between the first preparation feature and the corresponding process standard preparation parameter.

[0067] It can be understood that deviation analysis refers to analysis under the same dimensional conditions. This is because the output state of a material has multiple dimensions, such as the physical state (such as solid or liquid) and the chemical composition (such as the ratio of metal elements and impurity content).

[0068] For example, the predicted material output state and the second preparation feature of the i-th step can be subjected to dimensional analysis to obtain different features of the predicted material output state and the second preparation feature in the same dimension, and then feature comparison can be performed. According to the dimensional weights of different dimensions, the feature comparison results in the same dimension are weighted summed to finally obtain the parameter compliance rate.

[0069] S31113, obtain the actual output state, perform deviation analysis based on the actual output state and the target state, and obtain the result compliance rate; wherein the result compliance rate is used to reflect the degree of consistency between the actual output material state of the process and the standard material state.

[0070] Exemplarily, the process of obtaining the result compliance rate can be obtained by the method of obtaining the parameter compliance rate in step S31112, which will not be repeated here.

[0071] S31114: The parameter compliance rate and the result compliance rate are integrated according to the preset weights to generate a first correlation.

[0072] It can be understood that the preset weight refers to the degree of influence between the preset actual preparation parameters and the standard actual preparation parameters on the actual output result of the preparation result and the standard output result.

[0073] Exemplarily, the first correlation = parameter compliance rate × preset weight + result compliance rate × (1-preset weight).

[0074] S3112, perform state compatibility analysis on multiple second preparation features according to the preparation order of the preparation steps, obtain the state compatibility coefficient between the i-th second preparation feature and the i+1-th second preparation feature in the preparation steps, and then perform weighted fusion based on the state compatibility coefficient and the process weight to obtain the second correlation; wherein, the state compatibility coefficient is used to reflect the degree of matching between the output state of the i-th step in the preparation steps and the input requirement of the i+1-th step, and the process weight is used to reflect the matching strength weight of the material features between adjacent processes.

[0075] It can be understood that, according to the preparation order, a state compatibility analysis operation can be performed on each pair of adjacent preparation steps to calculate the state compatibility coefficient, and then the state compatibility coefficient and the corresponding process weight are weightedly fused to generate a second correlation.

[0076] Exemplarily, a second preparation feature vector corresponding to each preparation step in the preparation process can be obtained, and the second preparation feature vector contains one or more quantitative values ​​or codes that characterize the preparation result state achieved by the prepared material after the corresponding preparation step is completed. Then, the output state parameter set is obtained from the second preparation feature vector of the previous preparation process, and the input state parameter set is obtained from the second preparation feature vector of the next preparation process. Then, for one or more compatibility dimensions corresponding to the output state parameter set of the previous preparation process and the input state parameter set of the next preparation process, the state matching degree of each dimension is calculated. Then, the state matching degree of each compatibility dimension obtained by multiplication aggregation is generated to generate a single state compatibility coefficient. Finally, a weighted fusion is performed based on the state compatibility coefficient and the corresponding process weight to generate a second correlation.

[0077] With this setting, the first preparation feature and the second preparation feature are simulated and compared according to the preparation order to obtain the correlation, and the state compatibility analysis is carried out on the second preparation feature. The state compatibility coefficient is obtained by combining the process weighted fusion, which realizes the quantitative evaluation of the consistency of feature transfer and the matching degree of process connection in the preparation process, providing an analytical basis for optimizing the preparation process sequence and improving the reliability of the production process.

[0078] S312: Generate a first correlation feature based on the connection feature and the first correlation, and generate a second correlation feature based on the connection feature and the second correlation.

[0079] For example, a predefined fusion function can be used to fuse the connection feature with the first correlation to generate the first association feature, and the connection feature with the second correlation to generate the second association feature. Specifically, the connection feature and the first correlation are first normalized to ensure that the connection feature and the first correlation are in the range of [0, 1]. The connection feature and the first correlation are then directly multiplied and fused. The value obtained by the multiplication and fusion is confirmed as the first connection feature. Similarly, the second association feature can be obtained through the same processing steps.

[0080] In this way, by analyzing the first preparation feature and the second preparation feature in the preparation step, the first correlation characterizing the causal strength of the single process and the second correlation characterizing the dependence strength of the adjacent processes are obtained, and the first association feature and the second association feature are generated based on the connection feature and the two types of correlations respectively. This can provide a basis for the subsequent screening of parameters from the preparation step information library, and through the connection between the single process and the adjacent processes and the preparation results, a quantitative analysis of the degree of influence of the single process and the dependence relationship between the results across processes is achieved.

[0081] S320: Obtain instruction information according to the first correlation feature, the second correlation feature, and the preparation step information library.

[0082] Exemplarily, the indication information can be obtained by obtaining multiple preparation parameters reflecting the next step at the end of the preparation process from the preparation step information library, and then fusing the multiple preparation parameters reflecting the next step at the end of the preparation process with the associated features respectively, and then performing feature comparison with the first associated feature.

[0083] In this way, by analyzing and processing the preparation steps and connection features, a first correlation feature characterizing the intensity of influence between processes and a second correlation feature reflecting the degree of influence of the process within the process on the preparation result are generated respectively, and the indication information is obtained in combination with the preparation step information library.

[0084] In a possible implementation, in step S320, obtaining instruction information according to the first correlation feature, the second correlation feature, and the preparation step information library includes: S321, obtaining a plurality of indicative preparation features from a preparation step information library; wherein the indicative preparation features are used to reflect the preparation parameters of the next step of the last step in the preparation process.

[0085] It can be understood that the preparation step information library includes different steps for preparing high conductivity copper materials and different preparation parameters corresponding to different steps. The multiple indicative preparation features are the multiple preparation parameters included in the preparation step information library for the next step of the relevant step.

[0086] For example, a 0.1 mm copper foil is kept at 400°C for 15 minutes, and its conductivity reaches 102%. A 10 mm copper rod is kept at 550°C for 2 hours, and its conductivity increases from 98% to 103%. And so on.

[0087] S322, after fusing the second associated feature with the multiple indicative preparation features respectively, perform feature comparison with the first associated feature to obtain multiple feature intensities; wherein the feature intensities are used to reflect the suitability between the indicative preparation feature and the material information.

[0088] It can be understood that the first association feature is used to characterize the intensity of the impact of the completed process on the next process, and the second association feature is used to characterize the degree of influence of different processes of the process on the preparation results of the process itself, that is, the second association feature, the indicative preparation feature and the first association feature can all be represented by specific numerical values.

[0089] For example, the step of fusing the second correlation feature with the multiple indicative preparation features can be performed by using the same method used to obtain the first correlation feature in step S312 to obtain fusion results. This will not be described in detail here. The normalized first correlation feature is then compared with the multiple fusion results to obtain multiple feature strengths. Specifically, feature strength = fusion result - first correlation feature.

[0090] S323: Taking the indicative preparation feature corresponding to the maximum feature intensity among the plurality of feature intensities as the indication information.

[0091] It can be understood that among multiple characteristic intensities, the preparation characteristic indicated by the largest characteristic intensity is the preparation parameter that is most suitable for the current material.

[0092] In this way, by extracting the indicative preparation features reflecting the preparation parameters of the subsequent process from the preparation step information library, fusing them with the second associated features characterizing the process influence within the process, and then comparing them with the first associated features characterizing the influence between processes, the suitability of the indicative preparation features and the material information is quantified by the feature intensity, and then by selecting the parameters corresponding to the maximum value of the feature intensity as the indicative information, it is achieved that the preparation parameters that are most suitable for the physical conditions of the materials in different preparation steps are adopted.

[0093] In a possible implementation, in step S300, controlling the preparation device to perform a preparation operation corresponding to the instruction information according to the instruction information and the operation information on the preparation device includes: S330, when the indication information is the same as the preset preparation feature, at the moment when the current material feature of the material information is the same as the physical state that the copper material needs to reach in the preparation step corresponding to the indication information, control the preparation equipment to perform the preparation operation; wherein the preset preparation feature refers to the pre-set preparation parameters in the preparation step corresponding to the indicated preparation feature.

[0094] It can be understood that the preset preparation characteristics refer to the originally set preparation parameters, that is, the preparation parameters originally set by the preparation equipment when the preparation material reaches the next step of the relevant step without purity fluctuation or change in ambient temperature and humidity. The indication information carries the preparation parameters of the next step of the relevant step that are most suitable for the characteristics of the current preparation material. When the preparation parameters carried by the indication information are the same as the preset preparation characteristics, it indicates that the originally set preparation parameters are the preparation parameters that are most suitable for the current preparation material, that is, the preparation operation can be performed according to the original settings, but the current material characteristics must be the same as the physical state required for the preparation material corresponding to the originally set preparation parameters before the originally set preparation operation can be performed.

[0095] With this setting, differentiated control is achieved by comparing the indication information with the preset preparation characteristics. When there is no difference between the indication information and the preset preparation characteristics, when the indication information matches the preset preparation characteristics and the material status meets the standards, there is no need to adjust the original preparation parameters and the preparation equipment is automatically triggered to run.

[0096] In a possible implementation, in step S300, controlling the preparation device to perform a preparation operation corresponding to the instruction information according to the instruction information and the operation information on the preparation device further includes: S340, when the indication information is different from the preset preparation characteristics, a first icon is displayed on the control interface of the preparation equipment, and a second icon is superimposed in response to the first operation on the first icon; wherein, the first icon is used to indicate the adjustment of the preset preparation characteristics, and the second icon is used to reflect the icon for adjusting the preset preparation characteristics.

[0097] It is understood that when the indication information is different from the preset preparation characteristics, it indicates that the originally set preparation parameters are different from the preparation parameters that are most suitable for the current preparation material, and it is necessary to replace the originally set preparation parameters with the preparation parameters that are most suitable for the current preparation material. The first icon is used to remind the staff or the preparation system that the preset preparation characteristics need to be adjusted. The first operation refers to the staff triggering the first icon, and the triggering operation includes but is not limited to clicking, long pressing, etc. The second icon is the adjustment page for adjusting the parameters of the preset preparation characteristics.

[0098] For example, if the preset preparation feature is to perform stress relief annealing at 200°C, and the instruction information is to perform stress relief annealing at 180°C, a first icon is displayed on the control interface to remind the high conductivity copper material preparation system or staff to adjust the preset preparation feature.

[0099] S350 , in response to a second operation on the second icon, modifying the preset preparation feature into indication information, and then executing the preparation operation.

[0100] It can be understood that the second operation refers to a triggering operation on the second icon. After performing the second operation on the second icon, the staff or the preparation system modifies the preset preparation feature into instruction information, and when executing the next preparation step of the relevant step, the current preparation material is prepared according to the instruction information.

[0101] With this setting, when there is a discrepancy between the indicated information and the preset preparation characteristics, an early warning will be issued through the control interface icon and a visual interactive entrance will be provided to support the operator to quickly modify the preset parameters. This not only ensures the automation and accuracy of the production process, but also can efficiently handle parameter abnormalities, providing a reliable solution for intelligent control and flexible adjustment of the preparation process.

[0102] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean 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.

[0103] Corresponding to the high conductivity copper material preparation method described in the above embodiment, the embodiment of the present application also provides a high conductivity copper material preparation system, and each module of the high conductivity copper material preparation system can implement each step of the high conductivity copper material preparation method. Figure 3 A structural block diagram of a high-conductivity copper material preparation system provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0104] Reference Figure 3 , high conductivity copper material preparation system includes: The acquisition module is used to obtain material information and a preparation step information library; wherein the material information is used to reflect the state of the copper material in the current preparation process, and the preparation step information library includes different steps for reflecting the preparation of high-conductivity copper materials and different preparation parameters corresponding to different steps.

[0105] The analysis module is used to determine the connection characteristics in the preparation steps based on the material information and the preparation step information library; wherein the preparation steps are used to reflect the preparation steps that the material information has gone through, and the connection characteristics are used to characterize the connection strength between the process operation and the process steps.

[0106] The analysis and control module is used to analyze the connection characteristics, preparation steps and preparation step information library to obtain instruction information, and control the preparation equipment to perform the preparation operation corresponding to the instruction information based on the instruction information and the operation information of the preparation equipment; wherein the instruction information is used to indicate the next preparation action of the preparation equipment.

[0107] It should be noted that the information interaction, execution process, etc. between the above-mentioned systems / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0108] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0109] An embodiment of the present application further provides a high-conductivity copper material preparation device, which includes a preparation device and a control device, and the preparation device is electrically connected to the control device. Figure 4 This is a schematic diagram of the structure of the control device 4 provided in one embodiment of the present application. Figure 4 As shown, the control device 4 of this embodiment includes: at least one processor 40 ( Figure 4 Only one is shown), at least one memory 41 ( Figure 4 Only one is shown in the figure) and a computer program 42 stored in the at least one memory 41 and executable on the at least one processor 40. When the processor 40 executes the computer program 42, the control device 4 implements the steps of any of the above-mentioned embodiments of the method for preparing a high-conductivity copper material, or implements the functions of the modules / units in the above-mentioned embodiments of the system.

[0110] For example, the computer program 42 may be divided into one or more modules / units, which are stored in the memory 41 and executed by the processor 40 to implement the present application. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 42 in the control device 4.

[0111] The control device 4 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The control device 4 can include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will understand that Figure 4 This is merely an example of the control device 4 and does not constitute a limitation on the control device 4. The control device 4 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, buses, etc.

[0112] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0113] In some embodiments, the memory 41 may be an internal storage unit of the control device 4, such as a hard drive or memory of the control device 4. In other embodiments, the memory 41 may also be an external storage device of the control device 4, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the control device 4. Furthermore, the memory 41 may include both the internal storage unit of the control device 4 and an external storage device. The memory 41 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 41 may also be used to temporarily store data that has been output or is about to be output.

[0114] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0115] An embodiment of the present application provides a computer program product. When the computer program product is run on a high-conductivity copper material manufacturing device, the high-conductivity copper material manufacturing device implements the steps of any of the above-mentioned method embodiments.

[0116] If the integrated unit is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the high-conductivity copper material production equipment, a recording medium, computer memory, read-only memory (ROM), random access memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Examples include a USB flash drive, a removable hard drive, a magnetic disk, or an optical disk.

[0117] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0118] Those skilled in the art will appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel 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.

[0119] In the embodiments provided herein, it should be understood that the disclosed high-conductivity copper material preparation system and high-conductivity copper material preparation equipment can be implemented in other ways. For example, the embodiments of the high-conductivity copper material preparation system described above are merely illustrative. For example, the division of the modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not implemented. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0120] The units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0121] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for preparing a high conductivity copper material, characterized in that: include: Obtaining material information and a preparation step information library; wherein the material information is used to reflect the full life cycle data of the copper material during the preparation process, and the preparation step information library includes different steps for reflecting the preparation of high-conductivity copper materials and different preparation parameters corresponding to different steps; Determining, based on the material information and the preparation step information library, connection features in the preparation steps; wherein the preparation steps are used to reflect the preparation steps that the prepared material has undergone, and the connection features are used to characterize the connection strength between the process operations and the process steps; An analysis is performed based on the connection characteristics, the preparation steps and the preparation step information library to obtain instruction information, and the preparation equipment is controlled to perform a preparation operation corresponding to the instruction information based on the instruction information and the operation information of the preparation equipment; wherein the instruction information is used to indicate the next preparation action of the preparation equipment.

2. The method for preparing a high-conductivity copper material according to claim 1, wherein: Determining the connection features among the preparation steps according to the material information and the preparation step information library includes: Matching the preparation steps and their correlation from the preparation step information library based on the current material characteristics of the material information; wherein the current material characteristics are used to reflect the physical state of the copper material after completing the preparation steps, and the correlation degree is used to characterize the connection strength between adjacent processes of the preparation steps; The first preparation feature in the preparation steps and the correlation degree in the preparation steps are processed to obtain a connection feature; wherein the first preparation feature is used to reflect the preparation parameters corresponding to each preparation step.

3. The method for preparing a high-conductivity copper material according to claim 2, wherein: The matching of the preparation steps and the degree of correlation from the preparation step information library according to the current material characteristics of the material information includes: According to the current material feature of the material information, a relevant step having the greatest similarity to the current material feature is matched from a plurality of second preparation features in the preparation step information library; wherein the second preparation feature is used to reflect the physical state that the copper material corresponding to each preparation step needs to achieve; The relevant step and the step before the relevant step in the preparation step information database are jointly identified as preparation steps; Based on the preparation sequence of the preparation steps, the state compatibility analysis is performed on the i-th step and the i+1-th step in the preparation steps to obtain an initial matching value, and then weighted correction is performed based on the initial matching value and the process weight to obtain the degree of correlation; wherein, the initial matching value is used to reflect the degree of connection between the i-th step and the i+1-th step, and the process weight is used to reflect the connection strength weight of the preparation parameters between adjacent processes.

4. The method for preparing a high-conductivity copper material according to claim 1, wherein: The analysis based on the connection characteristics, the preparation steps and the preparation step information library to obtain the indication information includes: Processing the preparation steps and the connection features to obtain a first correlation feature and a second correlation feature; wherein the first correlation feature is used to characterize the intensity of the influence of the completed process on the next process, and the second correlation feature is used to characterize the degree of influence of different processes in the process on the preparation result of the process itself; Instruction information is obtained according to the first association feature, the second association feature and the preparation step information library.

5. The method for preparing a high-conductivity copper material according to claim 4, wherein: The processing according to the preparation steps and the connection features to obtain the first correlation feature and the second correlation feature includes: Analyzing the first and second preparation characteristics of the preparation steps to obtain a first correlation and a second correlation; wherein the first correlation is used to characterize the causal strength between the process and the preparation result within a single process, and the second correlation is used to reflect the dependence strength of the preparation results between adjacent processes; A first association feature is generated based on the connection feature and the first correlation, and a second association feature is generated based on the connection feature and the second correlation.

6. The method for preparing a high-conductivity copper material according to claim 5, wherein: The analyzing the first preparation feature and the second preparation feature in the preparation steps to obtain the first correlation and the second correlation includes: Performing a simulation comparison process on a plurality of first preparation features and a corresponding plurality of second preparation features according to a preparation sequence of the preparation steps, to obtain a first correlation between an i-th first preparation feature and an i-th second preparation feature in the preparation steps; A state compatibility analysis is performed on multiple second preparation features according to the preparation order of the preparation steps to obtain a state compatibility coefficient between the i-th second preparation feature and the i+1-th second preparation feature in the preparation steps, and then a weighted fusion is performed based on the state compatibility coefficient and the process weight to obtain a second correlation; wherein the state compatibility coefficient is used to reflect the degree of matching between the output state of the i-th step in the preparation steps and the input requirement of the i+1-th step, and the process weight is used to reflect the matching strength weight of material features between adjacent processes.

7. The method for preparing a high-conductivity copper material according to claim 4, wherein: The obtaining of indication information according to the first association feature, the second association feature, and the preparation step information library includes: Acquire a plurality of indicative preparation features from the preparation step information library; wherein the indicative preparation features are used to reflect the preparation parameters of the next step of the last step in the preparation process; After fusing the second correlation feature with the plurality of the indicative preparation features respectively, performing feature comparison with the first correlation feature to obtain a plurality of feature intensities; wherein the feature intensities are used to reflect the suitability between the indicative preparation features and the material information; The indicative preparation feature corresponding to the feature intensity of the maximum value among the plurality of feature intensities is used as the indication information.

8. The method for preparing a high-conductivity copper material according to claim 1, wherein: The controlling the preparation device to perform the preparation operation corresponding to the instruction information according to the instruction information and the operation information on the preparation device includes: When the indication information is the same as the preset preparation feature, the preparation equipment is controlled to perform the preparation operation at the moment when the current material feature of the material information is the same as the physical state required to be achieved by the copper material in the preparation step corresponding to the indication information; wherein the preset preparation feature refers to a pre-set preparation parameter in the preparation step corresponding to the indicated preparation feature.

9. The method for preparing a high-conductivity copper material according to claim 8, wherein: The controlling the preparation device to perform a preparation operation corresponding to the instruction information according to the instruction information and the operation information on the preparation device further includes: When the indication information is different from the preset preparation characteristics, a first icon is displayed on the control interface of the preparation device, and in response to a first operation on the first icon, a second icon is superimposed; wherein the first icon is used to indicate that the preset preparation characteristics are adjusted, and the second icon is used to reflect the adjustment of the preset preparation characteristics; In response to a second operation on the second icon, the preset preparation feature is modified to the indication information, and then the preparation operation is performed.

10. A high conductivity copper material preparation device, characterized in that: The method comprises a preparation device and a control device, wherein the preparation device is electrically connected to the control device, the control device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

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