Intelligent scheduling method and system for copper rod large-drawing process based on capability framework

Abstract

The present application relates to the technical field of industrial automation, and discloses a copper rod large-drawing process intelligent scheduling method and system based on a capability framework, which comprises the following steps: encapsulating the processes of the copper rod large-drawing process into standardized capability units; collecting equipment state data, process parameter data, product quality detection data and capability unit signal data of the standardized capability units, and establishing a copper rod large-drawing process database; based on the copper rod large-drawing process database, connecting the standardized capability units through a scheduling framework, cooperatively scheduling according to the signal linkage logic of the standardized capability units, and cooperatively constraining the tension state through a virtual catenary; based on the cooperatively scheduling result, issuing control instructions to the standardized capability units through the scheduling framework, executing the copper rod large-drawing process, and monitoring the processes of the standardized capability units. By standardizing the processes of the copper rod large-drawing process into independent capability units, the coupling degree between the processes is reduced, and the production requirements of different specifications of copper wires can be quickly adapted.

Description

Technical Field

[0001] This invention relates to the field of industrial automation technology, specifically to an intelligent scheduling method and system for large-scale copper rod pulling processes based on a capability framework. Background Technology

[0002] The copper rod drawing process, a core pre-process in wire and cable production, involves four continuous steps: unwinding, drawing, annealing, and winding, to process copper rods into fine copper wires of specific specifications. However, as industrial production demands increasingly higher quality (such as diameter accuracy and mechanical properties) and higher production efficiency for copper wires, the traditional scheduling methods for the copper rod drawing process have revealed numerous shortcomings. Firstly, the unwinding, drawing, annealing, and winding stages rely heavily on fixed parameters and manually set thresholds, making adjustments difficult based on equipment fluctuations or differences in copper rod material, easily leading to uneven wire stretching or production interruptions. Secondly, existing systems often monitor only a single key parameter, such as drawing liquid temperature or annealing current; any abnormalities still require manual judgment and intervention, resulting in long response times and increased risks of material scrap and equipment damage. Furthermore, the scheduling system cannot accurately identify the actual processing capacity of each process, leading to cumbersome operations and low scheduling flexibility when switching between production of multiple specifications of copper wire. Finally, scheduling decisions rely on experience, resulting in poor product quality stability and difficulty meeting the precision requirements of high-end applications. Summary of the Invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] To address the aforementioned technical problems, this invention provides the following technical solution: an intelligent scheduling method for large-scale copper rod pulling processes based on a capability framework, comprising:

[0005] The process of drawing copper rods is encapsulated into standardized capability units; the standardized capability units include a wire feeding capability unit, a pre-drawing anomaly judgment capability unit, a wire drawing capability unit, a pre-annealing anomaly judgment capability unit, an annealing capability unit, and a take-up capability unit connected in sequence by signals; each standardized capability unit includes input parameters, output results, operating status, and triggering conditions.

[0006] Collect equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability units to establish a copper rod large-scale drawing process database;

[0007] Based on the copper rod pulling process database, the standardized capability unit is connected through a scheduling framework, and coordinated scheduling is performed according to the signal linkage logic of the standardized capability unit; wherein, the output result of the previous capability unit serves as the trigger condition for the next capability unit, and the tension state is coordinated between the wire feeding capability unit and the wire taking-up capability unit through a virtual catenary.

[0008] Based on the collaborative scheduling results, control commands are issued to the standardized capability unit through the scheduling framework to execute the large-scale copper rod pulling process, and the standardized capability unit is monitored for the process.

[0009] As a preferred embodiment of the intelligent scheduling method for the large-scale copper rod pulling process based on the capability framework described in this invention, the step of collecting equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit includes collecting equipment status data through an equipment data interface; the equipment status data includes the operating status of the standardized capability unit.

[0010] Process parameter data is collected through a sensor network; the process parameter data includes the wire feeding speed corresponding to the wire feeding capacity unit, the wire drawing liquid temperature corresponding to the wire drawing pre-drawing anomaly judgment capacity unit, the annealing current, annealing coefficient, annealing voltage and annealing liquid temperature corresponding to the annealing pre-annealing anomaly judgment capacity unit, and the wire taking speed corresponding to the wire taking capacity unit.

[0011] Product quality inspection data is collected using quality inspection equipment; the product quality inspection data includes the initial diameter of the copper rod and the diameter of the copper wire after drawing.

[0012] The capability unit signal data is acquired in real time; the capability unit signal data includes the input start signal and output control signal of the standardized capability unit.

[0013] As a preferred embodiment of the intelligent scheduling method for large-scale copper rod pulling process based on the capability framework described in this invention, the signal linkage logic of the wire laying capability unit includes receiving the copper rod and the wire laying speed as input parameters, using the operating state as a trigger condition, and when the operating state switches from standby to running, performing wire laying processing on the copper rod according to the wire laying speed.

[0014] The output signal for handling wire drawing abnormalities is used as the output result, and the real-time wire feeding speed is synchronously output to the scheduling framework.

[0015] The signal linkage logic of the pre-drawing anomaly judgment capability unit includes receiving the drawing anomaly handling start signal and the drawing fluid temperature as input parameters, and using the drawing anomaly handling start signal as a trigger condition to switch the operating state from standby to running.

[0016] Determine whether the temperature of the drawing fluid is within the preset drawing fluid temperature compliance range. When the temperature of the drawing fluid is within the specified range, output a valid drawing start signal as the output result. When the temperature of the drawing fluid exceeds the specified range, output an invalid drawing start signal and trigger a drawing fluid temperature abnormality warning.

[0017] As a preferred embodiment of the intelligent scheduling method for the large-scale copper rod drawing process based on the capability framework described in this invention, the signal linkage logic of the drawing capability unit includes receiving the drawing start signal and the drawing die specifications as input parameters, using the drawing start signal as a trigger condition, and when the drawing start signal is a valid signal, switching the running state from standby to running; when the drawing start signal is an invalid signal, maintaining standby and not starting.

[0018] The copper rod is drawn according to the specifications of the drawing die; wherein, the specifications of the drawing die are determined according to the target copper wire size.

[0019] The output result is the annealing anomaly detection start signal.

[0020] The signal linkage logic of the pre-annealing anomaly judgment capability unit includes receiving the annealing anomaly judgment start signal, annealing current, annealing coefficient, annealing voltage and annealing liquid temperature as input parameters, and using the annealing anomaly judgment start signal as a trigger condition to switch the operating state from standby to operation.

[0021] The system determines whether the annealing current, annealing coefficient, annealing voltage, and annealing liquid temperature are all within their respective preset compliance ranges. When all three parameters are within their preset compliance ranges, a valid annealing start signal is output as the output result. When any one of the parameters exceeds its corresponding compliance range, an invalid annealing start signal is output and an abnormality warning for the corresponding parameter is triggered.

[0022] As a preferred embodiment of the intelligent scheduling method for the large-scale copper rod pulling process based on the capability framework described in this invention, the signal linkage logic of the annealing capability unit includes: receiving the annealing start signal as an input parameter, using the annealing start signal as a trigger condition, and when the annealing start signal is a valid signal, switching the running state from standby to running; when the annealing start signal is an invalid signal, maintaining standby and not starting.

[0023] The drawn copper rod is then annealed.

[0024] The output signal is used to initiate the take-up process.

[0025] The signal linkage logic of the take-up capability unit includes receiving the take-up start signal, the take-up reel specifications and the take-up speed as input parameters, and using the take-up start signal as a trigger condition to switch the operating state from standby to operation;

[0026] The annealed copper rod is wound up according to the specifications of the take-up reel and the take-up speed, and the real-time take-up speed is synchronously output to the scheduling framework; wherein, the specifications of the take-up reel are determined according to the copper wire length requirements;

[0027] The output includes a finished copper wire take-up completion signal and a task completion signal; the task completion signal indicates that the large-scale copper rod pulling process has been completed.

[0028] As a preferred embodiment of the intelligent scheduling method for the large-scale copper wire drawing process based on the capability framework described in this invention, the collaborative scheduling includes setting the benchmark parameters of the standardized capability unit according to the target copper wire specifications, combined with historical data, and through the scheduling interface; the benchmark parameters include wire feeding speed, wire drawing fluid temperature, annealing current, annealing coefficient, annealing voltage, annealing fluid temperature, and wire take-up speed.

[0029] The scheduling framework receives the output results of the standardized capability unit in real time and displays the output results synchronously on the scheduling interface.

[0030] The scheduling framework implements the orderly triggering of processes based on the signal linkage logic. The next capability unit is triggered to start execution based on the output result of the previous capability unit. When the parameters of a certain capability unit are non-compliant, an invalid signal is output, triggering the corresponding exception handling mechanism.

[0031] When switching to the production of copper wire of different specifications, the baseline parameters are updated through the scheduling interface, and the updated baseline parameters are automatically synchronized to the corresponding standardized capability unit.

[0032] As a preferred embodiment of the intelligent scheduling method for the large-scale copper rod pulling process based on the capability framework described in this invention, the collaborative constraint of tension state through virtual catenary includes: constructing virtual catenary geometric constraints based on the equipment spacing between the wire feeding capacity unit and the wire taking-up capacity unit, and setting a target virtual sag as a parameter of the ideal tension state; and generating a reference virtual arc length corresponding to the target virtual sag using a parabolic approximation fitting strategy.

[0033] The timing line length deviation is generated by accumulating the difference sequence between the real-time wire feeding speed and the real-time wire taking speed. When the take-up reel is replaced or the production task is switched, the timing line length deviation is reset to zero. The timing line length deviation is superimposed on the reference virtual arc length to obtain the real-time virtual arc length that reflects the current physical extension state of the copper wire.

[0034] Based on the geometric constraints of the virtual catenary, the real-time virtual sag of the copper wire is obtained by inversely solving the problem based on the geometric relationship between the equipment spacing and the real-time virtual arc length.

[0035] The real-time virtual sag is compared with the target virtual sag to obtain the sag deviation. When the sag deviation is within the preset normal deviation range, the current take-up speed remains unchanged. When the sag deviation exceeds the normal deviation range, the speed compensation amount is determined according to the positive and negative direction and deviation magnitude of the sag deviation, and the speed compensation amount is added to the take-up speed of the take-up capability unit.

[0036] A capability-based intelligent scheduling system for large-scale copper rod pulling processes, wherein:

[0037] The standardized packaging module encapsulates the processes of the large-scale copper rod drawing process into standardized capability units. The standardized capability unit includes a wire feeding capability unit, a pre-drawing anomaly judgment capability unit, a wire drawing capability unit, a pre-annealing anomaly judgment capability unit, an annealing capability unit, and a take-up capability unit, which are connected in sequence by signals. Each standardized capability unit includes input parameters, output results, operating status, and triggering conditions.

[0038] The data acquisition module collects equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit to establish a copper rod large-scale drawing process database.

[0039] The scheduling framework operation module, based on the copper rod pulling process database, connects to the standardized capability unit through the scheduling framework and performs coordinated scheduling according to the signal linkage logic of the standardized capability unit; wherein, the output result of the previous capability unit serves as the trigger condition for the next capability unit, and the tension state is coordinated between the wire laying capability unit and the wire taking capability unit through a virtual catenary.

[0040] The process monitoring module, based on the collaborative scheduling results, issues control commands to the standardized capability unit through the scheduling framework to execute the large-scale copper rod pulling process and monitors the process of the standardized capability unit.

[0041] A computer device includes: a memory and a processor; the memory stores a computer program, wherein: when the processor executes the computer program, it implements the steps of the method described in any one of the present invention.

[0042] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the present invention.

[0043] The beneficial effects of this invention are as follows: This invention standardizes the wire feeding, pre-drawing anomaly detection, drawing, pre-annealing anomaly detection, annealing, and take-up processes in the large-scale copper rod drawing process into independent capability units. Each capability unit clearly defines its input parameters, output results, operating status, and triggering conditions. An orderly linkage is achieved through a scheduling framework, reducing the coupling between processes and enabling rapid adaptation to the production needs of different copper wire specifications. Through the linkage of input and output signals of each capability unit, the next capability unit can only start when the previous unit outputs a valid signal, ensuring precise process connection, avoiding process disconnection, and improving production efficiency. By constructing a virtual catenary geometric constraint, the tension state coordination between wire feeding and take-up is achieved. Take-up speed compensation is performed based on speed difference accumulation and geometric inverse solution, avoiding wire breakage or slack jitter caused by tension fluctuations. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 The overall flowchart of the intelligent scheduling method for large-scale copper rod pulling process based on the capability framework provided in the embodiments of the present invention is shown. Detailed Implementation

[0046] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0047] Example 1, referring to Figure 1 As an embodiment of the present invention, a smart scheduling method for a large-scale copper rod pulling process based on a capability framework is provided, comprising:

[0048] S1: The process of drawing copper rods is encapsulated into standardized capability units; the standardized capability unit includes a wire feeding capability unit, a pre-drawing anomaly judgment capability unit, a wire drawing capability unit, a pre-annealing anomaly judgment capability unit, an annealing capability unit, and a take-up capability unit connected in sequence by signals; each standardized capability unit includes input parameters, output results, operating status, and triggering conditions.

[0049] In this embodiment, the copper rod drawing process is a core pre-process in wire and cable production. It mainly involves continuous processes such as laying, drawing, annealing, and winding to process 8mm copper rods into fine copper wires of specific specifications. In this embodiment, the copper rod drawing process is encapsulated into standardized capability units. By encapsulating the six core processes and anomaly handling into independent standardized capability units, the scheduling framework can accurately identify the operating status and processing capacity of each unit, achieving precise coordination between processes and rapid response to anomalies.

[0050] Specifically, the standardized capability unit includes a wire feeding capability unit, a wire drawing pre-abortion judgment capability unit, a wire drawing capability unit, a annealing pre-abortion judgment capability unit, an annealing capability unit, and a wire take-up capability unit connected in sequence by signals; each standardized capability unit includes input parameters, output results, operating status, and triggering conditions.

[0051] By embedding anomaly detection before wire drawing and anomaly detection before annealing as independent capability units into the process chain, a complete process flow is formed, including wire feeding, anomaly detection before wire drawing, wire drawing, anomaly detection before annealing, annealing, and wire take-up. Anomaly detection is treated as an independent capability unit, making it an active access control mechanism. Anomalies must be detected before proceeding to the next process, thereby achieving proactive interception of anomalies rather than passive monitoring, effectively avoiding material waste or equipment damage caused by delayed anomaly handling.

[0052] Furthermore, the standardized capability unit's operating state includes standby and running, with standby being the initial state. The trigger condition for each capability unit is to switch from standby to running and start execution after receiving a valid signal output from the previous capability unit. Through this signal linkage mechanism, an orderly process connection relationship is formed between the capability units, with the output result of the previous capability unit serving as the trigger condition for the next capability unit, ensuring that the processes are executed sequentially according to the preset order.

[0053] Specifically, the wire feeding capacity unit includes: a double-head large drawing machine (DL06 / DL04 / DL05 / DL07 / DL08); operating states include standby and running, initially in standby; input parameters include 8mm copper rod and wire feeding speed; the trigger condition is the switching of the operating state from standby to running; the output result is a wire drawing abnormality handling start signal (fixed output 1), and the real-time wire feeding speed is synchronously output to the scheduling framework; it supports video visualization display, and the video automatically turns off after a preset display time, which is 3 seconds in this embodiment.

[0054] The abnormal judgment ability unit before wire drawing includes: The operating state includes standby and running, initially in standby; The input parameters are the wire drawing abnormal handling start signal and the wire drawing liquid temperature; The trigger condition is receiving the wire drawing abnormal handling start signal output by the wire feeding ability unit; The output result is the wire drawing start signal. Only when the wire drawing liquid temperature is within the preset compliance range of the wire drawing liquid temperature, a valid wire drawing start signal is output. When the wire drawing liquid temperature exceeds the compliance range, an invalid wire drawing start signal is output and a wire drawing liquid temperature abnormal prompt is triggered. In this embodiment, the preset compliance range of the wire drawing liquid temperature is 35 - 45°C, and the wire drawing start signal output when the wire drawing liquid temperature is compliant is 1; It supports video visualization display, and the video automatically closes after the preset display time, which is 3 seconds in this embodiment.

[0055] The wire drawing ability unit includes: The equipment is a wire drawing module supporting a double-head large wire drawing machine; The operating state includes standby and running, initially in standby; The input parameters are the wire drawing start signal and the wire drawing die specification, where the wire drawing die specification is determined by matching the target copper wire size; The trigger condition is receiving the wire drawing start signal output by the abnormal judgment ability unit before wire drawing. When the wire drawing start signal is a valid signal, it switches from standby to running, and when the wire drawing start signal is an invalid signal, it remains in standby and does not start; The output result is the annealing abnormal judgment start signal (output 1 when the wire drawing ability unit starts); It supports video visualization display, and the video automatically closes after the preset display time, which is 3 seconds in this embodiment, and the interface shows "Performing wire drawing treatment on the copper rod".

[0056] The abnormal judgment ability unit before annealing includes: The operating state includes standby and running, initially in standby; The input parameters include the annealing abnormal judgment start signal, the annealing current, the annealing coefficient, the annealing voltage, and the annealing liquid temperature; The trigger condition is receiving the annealing abnormal judgment start signal output by the wire drawing ability unit; The output result is the annealing start signal. Only when the annealing current, the annealing coefficient, the annealing voltage, and the annealing liquid temperature are all within their respective preset compliance ranges, a valid annealing start signal is output. When any parameter exceeds the corresponding compliance range, an invalid annealing start signal is output and an abnormal prompt for the corresponding parameter is triggered; The parameters support small-range fluctuation display; It supports video visualization display, and the video automatically closes after the preset display time, which is 4 seconds in this embodiment.

[0057] Exemplarily, in this embodiment, it is set that the compliance range of the annealing current is 0 - 8500A, the compliance range of the annealing coefficient is 7.9 - 13, the compliance range of the annealing voltage is 0 - 48V, and the compliance range of the annealing liquid temperature is 30 - 42°C. When all parameters are within their respective compliance ranges, the annealing start signal 1 is output. When any parameter exceeds the compliance range, the annealing start signal 0 is output, and the video visualization display time is set to automatically close after 4 seconds.

[0058] The annealing capability unit includes: a double-head large drawing machine annealing device; operating states include standby and running, initially in standby; input parameters include an annealing start signal; the trigger condition is receiving the annealing start signal output by the pre-annealing anomaly judgment capability unit, switching from standby to running when the annealing start signal is valid, and remaining in standby without starting when the annealing start signal is invalid; the output result is a take-up start signal (output 1 if the annealing capability unit is started); it supports video visualization display, and the video automatically closes after a preset display time, which is 3 seconds in this embodiment, and the interface displays "Annealing treatment is performed on the drawn copper rod".

[0059] The take-up capability unit includes: a double-head large-draw take-up module; operating states include standby and operation, initially in standby; input parameters include take-up start signal, take-up reel specifications, and take-up speed, the take-up reel specifications are determined according to the copper wire length requirements, and in this embodiment, the value is 500mm; the trigger condition is receiving the take-up start signal output by the annealing capability unit; output results include finished copper wire take-up completion signal and task completion signal, wherein when the take-up capability unit is activated, the task completion signal output is 1, the task completion signal indicates that the large-draw process of the copper rod has been completed, and the real-time take-up speed is synchronously output to the scheduling framework; it supports video visualization display, the video automatically closes after a preset display time, which is 3 seconds in this embodiment, and the interface displays "The annealed copper rod is taken into the take-up reel".

[0060] It should be noted that, in response to the problems of lack of capacity management and delayed anomaly monitoring requiring manual intervention in the traditional copper rod drawing process, the six processes are encapsulated into standardized capacity units. Each standardized capacity unit clearly defines its input parameters, output results, operating status, and triggering conditions. Anomaly judgment is embedded as an independent capacity unit into the process chain to form an active access control mechanism, thereby achieving standardized and modular management of the processes. The capacity units are linked by signals to achieve orderly connection, reducing the coupling between processes. This allows the scheduling framework to accurately identify the operating status and processing capacity of each unit, enabling it to quickly adapt to the production needs of different specifications of copper wire, while also achieving proactive interception of anomalies.

[0061] S2: Collect equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit to establish a copper rod large-scale drawing process database.

[0062] After completing the encapsulation of the standardized capability units in S1, a comprehensive data acquisition system needs to be established to provide data support for subsequent collaborative scheduling decisions. In this embodiment, the system collects equipment status data, process parameter data, product quality inspection data, and capability unit signal data in real time through sensor networks and equipment data interfaces, and establishes a copper rod pulling process database to ensure the real-time performance and accuracy of scheduling decisions.

[0063] It should be noted that some of the four types of data collected in this embodiment correspond to the structural elements defined in S1 for the standardized capability unit: equipment status data corresponds to the operating status of the standardized capability unit, process parameter data corresponds to the input parameters of the standardized capability unit, and capability unit signal data corresponds to the output results and triggering conditions of the standardized capability unit. By establishing this correspondence, the collected data can accurately reflect the real-time operating status of each capability unit, providing complete status information for the scheduling framework.

[0064] Specifically, the process of collecting equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit includes the following steps:

[0065] First, equipment status data is collected through the equipment data interface; the equipment status data includes the operating status of the standardized capability units, that is, whether each standardized capability unit is currently in standby or running. The operating status information of equipment such as the double-head drawing machine, wire drawing module, annealing device, and take-up module is collected through the PLC data interface to reflect the working status of each capability unit in real time.

[0066] Secondly, process parameter data is collected through a sensor network; the process parameter data includes the wire feeding speed corresponding to the wire feeding capacity unit, the wire drawing liquid temperature corresponding to the wire drawing pre-drawing anomaly judgment capacity unit, the annealing current, annealing coefficient, annealing voltage and annealing liquid temperature corresponding to the annealing pre-annealing anomaly judgment capacity unit, and the wire taking speed corresponding to the wire taking capacity unit.

[0067] It should be noted that the collection of the above process parameter data is closely related to the functional positioning of each capability unit: the wire feeding speed, as an input parameter of the wire feeding capability unit, directly affects the conveying stability of the copper rod; the wire drawing fluid temperature, as an input parameter of the pre-drawing anomaly judgment capability unit, is used to determine whether the start conditions of the wire drawing process are met; the annealing current, annealing coefficient, annealing voltage, and annealing fluid temperature, as input parameters of the pre-annealing anomaly judgment capability unit, are used to determine whether the start conditions of the annealing process are met; the wire take-up speed, as an input parameter of the take-up capability unit, affects the take-up quality of the finished copper wire; the above process parameter data are collected by temperature sensors, pressure sensors, etc., installed on the equipment and transmitted to the scheduling framework database in real time.

[0068] Furthermore, product quality inspection data is collected through quality inspection equipment. The product quality inspection data includes the initial diameter of the copper rod and the diameter of the copper wire after drawing. The initial diameter of the copper rod is collected before the wire laying process and the diameter of the copper wire is collected after the wire drawing process using quality inspection equipment such as a laser diameter gauge. This data is used to monitor whether the product quality meets the specifications.

[0069] Furthermore, the capability unit signal data is collected in real time, wherein the capability unit signal data includes the input start signal and output control signal of the standardized capability unit, specifically including: the wire drawing anomaly handling start signal output by the wire feeding capability unit, the wire drawing start signal output by the wire drawing pre-drawing anomaly judgment capability unit, the annealing anomaly judgment start signal output by the wire drawing capability unit, the annealing start signal output by the annealing pre-annealing anomaly judgment capability unit, the wire take-up start signal output by the annealing capability unit, and the finished copper wire take-up completion signal and task completion signal output by the wire take-up capability unit.

[0070] Capability unit signal data is the core data for realizing signal linkage logic. By collecting the input start signals and output control signals of each capability unit in real time, the scheduling framework can accurately grasp the execution status of the current process and the triggering conditions of the next process. When the abnormal judgment capability unit before wire drawing or the abnormal judgment capability unit before annealing outputs an invalid signal, the scheduling framework can promptly detect the abnormal state and trigger the corresponding abnormal handling mechanism.

[0071] Furthermore, the collected equipment status data, process parameter data, product quality inspection data, and capacity unit signal data are stored in the copper rod large-scale pulling process database. The copper rod large-scale pulling process database is used to store the real-time operation data and historical data of each capacity unit, providing data support for the collaborative scheduling decision of the scheduling framework, and providing a data source for the generation of production reports.

[0072] It should be noted that, in response to the problem that scheduling decisions in the traditional copper rod pulling process rely on manual experience and lack a data-driven decision-making mechanism, a copper rod pulling process database is established by collecting equipment status data, process parameter data, product quality inspection data, and capacity unit signal data in real time through sensor networks and equipment data interfaces. This enables comprehensive perception of the operating status of each capacity unit. The above four types of data together constitute the data foundation of the copper rod pulling process database, providing real-time, accurate, and complete data support for the collaborative scheduling decisions of the subsequent scheduling framework.

[0073] S3: Based on the copper rod pulling process database, the standardized capability unit is connected through the scheduling framework, and coordinated scheduling is performed according to the signal linkage logic of the standardized capability unit; wherein, the output result of the previous capability unit serves as the trigger condition for the next capability unit, and the tension state is coordinated between the wire feeding capability unit and the wire taking-up capability unit through a virtual catenary.

[0074] Furthermore, after establishing the copper rod pulling process database in S2, this embodiment connects to each standardized capability unit through a standardized scheduling framework. Based on the real-time data in the copper rod pulling process database, it performs collaborative scheduling according to the signal linkage logic of each standardized capability unit to achieve precise collaboration between processes and rapid response to anomalies.

[0075] Specifically, the collaborative scheduling includes four sub-steps: initializing scheduling parameters, state awareness and feedback, dynamic scheduling decision-making, and production switchover adaptation. The specific process is as follows:

[0076] The initialization scheduling parameters include: setting the baseline parameters of the standardized capability unit according to the target copper wire specifications, combined with historical data, and through the scheduling interface; the baseline parameters include wire feeding speed, drawing fluid temperature, annealing current, annealing coefficient, annealing voltage, annealing fluid temperature, and take-up speed. In this embodiment, the wire feeding speed is set to 10 m / s, the drawing fluid temperature is set to 38℃, the annealing current is set to 5883A, the annealing coefficient is set to 10.8, the annealing voltage is set to 32.4V, the annealing fluid temperature is set to 36℃, and the take-up speed is set to 10 m / s.

[0077] It should be noted that the initialization of the reference parameters is a prerequisite for collaborative scheduling. By presetting the reference parameters of each capability unit according to the target copper wire specifications, the subsequent signal linkage logic is provided with a basis for judgment. For example, the pre-drawing anomaly judgment capability unit judges whether the current drawing fluid temperature is compliant based on the preset compliance range of the drawing fluid temperature, and the pre-annealing anomaly judgment capability unit judges whether the current parameters are compliant based on the preset compliance range of the annealing current, annealing coefficient, annealing voltage, and annealing fluid temperature.

[0078] The status perception and feedback includes: the scheduling framework receives the output results of the standardized capability unit in real time and displays the output results synchronously on the scheduling interface to intuitively present the process connection status.

[0079] Status awareness and feedback are fundamental aspects of collaborative scheduling. By receiving output signals from each capability unit in real time, the scheduling framework can accurately grasp the execution status of the current process and the triggering conditions of the next process, intuitively presenting the process connection status. The scheduling interface supports centralized display of the operating status, visual videos, and key parameters of the standardized capability units, allowing operators to intuitively view the entire process data. The visual videos are set with an automatic shutdown time and do not loop, and the video paths of the visual videos support both absolute and relative path configurations. The key parameters support both fixed value display and small-range fluctuation display.

[0080] The dynamic scheduling decision includes: the scheduling framework realizes the orderly triggering of the process according to the signal linkage logic, wherein the next capability unit is triggered to start execution according to the output result of the previous capability unit, and when the parameters of a certain capability unit are not compliant, an invalid signal is output, triggering the corresponding exception handling mechanism.

[0081] Specifically, the execution process of the signal linkage logic is as follows:

[0082] After receiving the copper rod and the wire-laying speed as input parameters, the wire-laying capacity unit uses the operating state as the trigger condition. When the operating state switches from standby to running, it performs wire-laying processing on the copper rod according to the wire-laying speed, outputs a wire-drawing abnormality processing start signal as the output result, and synchronously outputs the real-time wire-laying speed to the scheduling framework.

[0083] After receiving the drawing abnormality handling start signal and the drawing fluid temperature as input parameters, the drawing abnormality handling start signal is used as the trigger condition to switch the running state from standby to running; it determines whether the drawing fluid temperature is within the preset drawing fluid temperature compliance range; when the drawing fluid temperature is within the drawing fluid temperature compliance range, it outputs a valid drawing start signal as the output result; when the drawing fluid temperature exceeds the drawing fluid temperature compliance range, it outputs an invalid drawing start signal and triggers a drawing fluid temperature abnormality prompt.

[0084] After receiving the wire drawing start signal and the wire drawing die specifications as input parameters, the wire drawing capability unit uses the wire drawing start signal as a trigger condition. When the wire drawing start signal is valid, the operating state is switched from standby to operation; when the wire drawing start signal is invalid, it remains in standby and does not start. The copper rod is wire drawn according to the wire drawing die specifications, wherein the wire drawing die specifications are determined according to the target copper wire size. An annealing anomaly judgment start signal is output as the output result.

[0085] The pre-annealing anomaly detection unit receives the annealing anomaly detection start signal, annealing current, annealing coefficient, annealing voltage, and annealing liquid temperature as input parameters. Using the annealing anomaly detection start signal as a trigger condition, it switches the operating state from standby to operation. It determines whether the annealing current, annealing coefficient, annealing voltage, and annealing liquid temperature are all within their respective preset compliance ranges. When all three parameters are within their preset compliance ranges, it outputs a valid annealing start signal as the output result. When any one of the annealing current, annealing coefficient, annealing voltage, or annealing liquid temperature exceeds its corresponding compliance range, it outputs an invalid annealing start signal and triggers an anomaly warning for the corresponding parameter.

[0086] After receiving the annealing start signal as an input parameter, the annealing capability unit uses the annealing start signal as a trigger condition. When the annealing start signal is valid, the operating state is switched from standby to operation; when the annealing start signal is invalid, standby is maintained and the unit is not started. The copper rod after wire drawing is annealed, and a take-up start signal is output as the output result.

[0087] After receiving the take-up start signal, take-up reel specifications, and take-up speed as input parameters, the take-up start signal is used as a trigger condition to switch the operating state from standby to operation. The take-up reel specifications and take-up speed are used to perform take-up processing on the annealed copper rod, wherein the take-up reel specifications are determined according to the copper wire length requirements. The finished copper wire take-up completion signal and task completion signal are output as output results. The task completion signal indicates that the large-scale copper rod pulling process has been completed, and the real-time take-up speed is synchronously output to the scheduling framework.

[0088] It should be noted that the anomaly handling mechanism includes: when the pre-drawing anomaly judgment unit determines that the drawing fluid temperature exceeds the compliant range, the pre-drawing anomaly judgment unit outputs an invalid drawing start signal, the drawing capability unit remains in standby and does not start, and the scheduling interface provides an anomaly warning for the drawing fluid temperature, suspending subsequent processes until the temperature is adjusted to compliance; when the pre-annealing anomaly judgment unit determines that any parameter among the annealing current, the annealing coefficient, the annealing voltage, or the annealing fluid temperature exceeds the corresponding compliant range, the pre-annealing anomaly judgment unit outputs an invalid annealing start signal, the annealing capability unit remains in standby and does not start, and the scheduling interface provides an anomaly warning for the corresponding parameter; the scheduling interface supports anomaly warnings when the capability unit signal data is abnormal, and supports rapid configuration of the parameters of the standardized capability unit.

[0089] For example, suppose that when the temperature of the drawing fluid is found to be outside the range of 35-45℃, the pre-drawing anomaly judgment unit outputs a drawing start signal 0, the scheduling framework highlights the temperature anomaly on the scheduling interface, and the drawing capability unit is paused. The process resumes after the temperature is adjusted to the range of 35-45℃.

[0090] The production switching adaptation includes: when switching to the production of copper wire of different specifications, updating the baseline parameters through the scheduling interface, and automatically synchronizing the updated baseline parameters to the corresponding standardized capability unit.

[0091] Furthermore, the tension state is coordinated between the wire-laying unit and the wire-retrieving unit through a virtual catenary, the specific process of which is as follows:

[0092] It should be noted that the copper rod drawing process is a continuous high-speed production process. The copper wire between the wire feeding unit and the wire take-up unit is under tension. In this embodiment, by constructing a virtual catenary geometric constraint, the invisible and immeasurable tension control problem is transformed into a quantifiable geometric shape maintenance problem. Although the copper wire is physically straight, the algorithm mathematically assumes that there is a virtual rope with sag between the wire feeding unit and the wire take-up unit. The tension state is indirectly characterized and controlled by controlling the virtual sag.

[0093] Specifically, based on the equipment spacing between the wire feeding and take-up units, a virtual catenary geometric constraint is constructed, and a target virtual sag is set as a parameter for the ideal tension state. Since the sag is relatively small compared to the chord length, a parabolic approximation fitting strategy is used to calculate the reference virtual arc length based on the equipment spacing and the target virtual sag.

[0094] The difference between the pay-off and take-up speeds causes variations in the copper wire length between the pay-off and take-up capability units. When the pay-off speed is greater than the take-up speed, the wire length cumulatively increases; when the pay-off speed is less than the take-up speed, the wire length cumulatively decreases. Therefore, a time-series wire length deviation is generated by accumulating the difference sequence between the real-time pay-off speed and the real-time take-up speed. When the take-up reel is replaced or the production task is switched, the physical state of the copper wire is reset, and the time-series wire length deviation is reset to zero to avoid the impact of historical deviations on the new task. The time-series wire length deviation is then superimposed on the reference virtual arc length to obtain the real-time virtual arc length reflecting the current physical extension state of the copper wire.

[0095] Based on the geometric constraints of the virtual catenary, the real-time virtual sag of the copper wire is obtained by inversely solving the geometric relationship between the equipment spacing and the real-time virtual arc length. When the real-time virtual arc length is less than or equal to the equipment spacing, it indicates that the copper wire is in an over-tensioned state, and the real-time virtual sag is 0.

[0096] The real-time virtual sag is compared with the target virtual sag to obtain the sag deviation. When the sag deviation is greater than 0, it means that the virtual sag is greater than the target value and the copper wire is in a loose state. When the sag deviation is less than 0, it means that the virtual sag is less than the target value and the copper wire is in a tight state.

[0097] Furthermore, based on the sag deviation and a preset normal deviation range, when the sag deviation is within the preset normal deviation range, the current take-up speed remains unchanged; when the sag deviation exceeds the normal deviation range, the speed compensation amount is determined by multiplying the sag deviation by the proportional gain coefficient according to the positive or negative direction and deviation amplitude of the sag deviation, and the speed compensation amount is superimposed on the take-up speed of the take-up capability unit. Specifically, when the copper wire is too loose, the take-up speed is increased to tighten the copper wire, and when the copper wire is too tight, the take-up speed is decreased to loosen the copper wire.

[0098] It should be noted that, addressing the issues of rigid process coordination and slow anomaly response in traditional copper rod drawing processes, a scheduling framework is used to connect with various standardized capability units. Collaborative scheduling is performed based on real-time data from the copper rod drawing process database. This involves initializing scheduling parameters and pre-setting baseline parameters for each capability unit according to the target copper wire specifications, providing a basis for signal linkage logic. Through status perception and feedback, the scheduling framework receives output signals from each capability unit in real time and displays them synchronously on the scheduling interface, intuitively presenting the process connection status. Dynamic scheduling decisions enable orderly triggering of processes based on signal linkage logic. When parameters are non-compliant, invalid signals are output to trigger an anomaly handling mechanism, achieving proactive interception and rapid response to anomalies. Production switching adaptation supports rapid parameter configuration and automatic synchronization to each capability unit, enabling flexible switching of production specifications. A virtual catenary is used to coordinate tension state constraints between the pay-off and take-up capability units, transforming the tension control problem into a geometric shape maintenance problem. This allows for indirect monitoring and control of tension state without additional tension sensors, improving production efficiency and product quality stability.

[0099] S4: Based on the collaborative scheduling results, control commands are issued to the standardized capability unit through the scheduling framework to execute the large-scale copper rod pulling process, and the standardized capability unit is monitored for the process.

[0100] In this embodiment, control commands are sent to each standardized capability unit through a scheduling framework to execute the large-scale copper rod pulling process. At the same time, the operating status, process parameters and visualization of each standardized capability unit are monitored in real time to generate production reports, thereby achieving centralized monitoring and data recording of the entire process.

[0101] Specifically, the process of issuing control commands to the standardized capability units through the scheduling framework based on the collaborative scheduling results to execute the large-scale copper rod pulling process includes: the scheduling framework, based on the collaborative scheduling results in S3, issues control commands to each standardized capability unit through the scheduling interface, and triggers each capability unit to start execution in the order of wire laying, pre-drawing anomaly judgment, wire drawing, pre-annealing anomaly judgment, annealing, and wire take-up, thereby completing the large-scale copper rod pulling process; during the process execution, the scheduling framework calculates the tension state between the wire laying capability unit and the wire take-up capability unit in real time based on the geometric constraints of the virtual catenary, and automatically adjusts the take-up speed according to the sag deviation to achieve coordinated operation of wire laying and take-up.

[0102] Furthermore, the process monitoring of the standardized capability units includes: displaying the operating status, visual video, process parameters, and product quality data of each standardized capability unit in real time through the scheduling interface of the scheduling framework. After production is completed, the scheduling framework automatically generates a production report; the production report includes output, operating status records of each standardized capability unit, and anomaly handling records.

[0103] It should be noted that, addressing the challenges of scattered operational status and incomplete production data recording in traditional copper rod pulling processes, which lead to difficulties in problem tracing, a scheduling framework is used to issue control commands to execute the copper rod pulling process. This framework also monitors the process and generates production reports for each standardized capability unit. The scheduling interface enables centralized monitoring of the entire process, allowing operators to intuitively grasp the production status without switching between different equipment interfaces. Each standardized capability unit supports video and parameter visualization, improving operational convenience. Production reports automatically record output, operational status records of each standardized capability unit, and anomaly handling records, facilitating problem tracing and production management.

[0104] On the other hand, this embodiment also provides an intelligent scheduling system for copper rod large-scale pulling processes based on a capability framework, which includes:

[0105] The standardized packaging module encapsulates the processes of the large-scale copper rod drawing process into standardized capability units. The standardized capability units include a wire feeding capability unit, a pre-drawing anomaly judgment capability unit, a wire drawing capability unit, a pre-annealing anomaly judgment capability unit, an annealing capability unit, and a wire take-up capability unit, which are connected in sequence by signals. Each standardized capability unit includes input parameters, output results, operating status, and triggering conditions.

[0106] The data acquisition module collects equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit to establish a copper rod large-scale drawing process database.

[0107] The scheduling framework operation module, based on the copper rod pulling process database, connects to the standardized capability unit through the scheduling framework and performs coordinated scheduling according to the signal linkage logic of the standardized capability unit; wherein, the output result of the previous capability unit serves as the trigger condition for the next capability unit, and the tension state is coordinated between the wire laying capability unit and the wire taking capability unit through a virtual catenary.

[0108] The process monitoring module, based on the collaborative scheduling results, issues control commands to the standardized capability unit through the scheduling framework to execute the large-scale copper rod pulling process and monitors the process of the standardized capability unit.

[0109] If the above functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0110] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0111] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0112] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0113] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A smart scheduling method for large-scale copper rod pulling processes based on a capability framework, characterized in that: include: The process of drawing copper rods is encapsulated into standardized capability units; the standardized capability units include a wire feeding capability unit, a pre-drawing anomaly judgment capability unit, a wire drawing capability unit, a pre-annealing anomaly judgment capability unit, an annealing capability unit, and a take-up capability unit connected in sequence by signals; each standardized capability unit includes input parameters, output results, operating status, and triggering conditions. Collect equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability units to establish a copper rod large-scale drawing process database; Based on the copper rod pulling process database, the standardized capability unit is connected through a scheduling framework, and coordinated scheduling is performed according to the signal linkage logic of the standardized capability unit; wherein, the output result of the previous capability unit serves as the trigger condition for the next capability unit, and the tension state is coordinated between the wire feeding capability unit and the wire taking-up capability unit through a virtual catenary. Based on the collaborative scheduling results, control commands are issued to the standardized capability unit through the scheduling framework to execute the large-scale copper rod pulling process, and the standardized capability unit is monitored for the process.

2. The intelligent scheduling method for large-scale copper rod pulling process based on a capability framework as described in claim 1, characterized in that: The collection of equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit includes collecting equipment status data through an equipment data interface; the equipment status data includes the operating status of the standardized capability unit. Process parameter data are collected through sensor networks; The process parameter data includes the wire feeding speed corresponding to the wire feeding capacity unit, the wire drawing fluid temperature corresponding to the wire drawing pre-drawing anomaly judgment capacity unit, the annealing current, annealing coefficient, annealing voltage and annealing fluid temperature corresponding to the annealing pre-annealing anomaly judgment capacity unit, and the wire taking speed corresponding to the wire taking capacity unit. Product quality inspection data is collected using quality inspection equipment; the product quality inspection data includes the initial diameter of the copper rod and the diameter of the copper wire after drawing. The capability unit signal data is acquired in real time; the capability unit signal data includes the input start signal and output control signal of the standardized capability unit.

3. The intelligent scheduling method for large-scale copper rod pulling process based on a capability framework as described in claim 2, characterized in that: The signal linkage logic of the wire feeding capacity unit includes receiving the copper rod and the wire feeding speed as input parameters, using the operating state as a trigger condition, and when the operating state switches from standby to running, feeding the copper rod according to the wire feeding speed. The output signal for handling wire drawing abnormalities is used as the output result, and the real-time wire feeding speed is synchronously output to the scheduling framework. The signal linkage logic of the pre-drawing anomaly judgment capability unit includes receiving the drawing anomaly handling start signal and the drawing fluid temperature as input parameters, and using the drawing anomaly handling start signal as a trigger condition to switch the operating state from standby to running. Determine whether the temperature of the drawing fluid is within the preset drawing fluid temperature compliance range. When the temperature of the drawing fluid is within the specified range, output a valid drawing start signal as the output result. When the temperature of the drawing fluid exceeds the specified range, output an invalid drawing start signal and trigger a drawing fluid temperature abnormality warning.

4. The intelligent scheduling method for large-scale copper rod pulling process based on a capability framework as described in claim 3, characterized in that: The signal linkage logic of the wire drawing capability unit includes receiving the wire drawing start signal and the wire drawing die specifications as input parameters, using the wire drawing start signal as a trigger condition, and switching the operating state from standby to running when the wire drawing start signal is a valid signal; and keeping the standby state inactive when the wire drawing start signal is an invalid signal. The copper rod is drawn according to the specifications of the drawing die; wherein, the specifications of the drawing die are determined according to the target copper wire size. The output result is the annealing anomaly detection start signal. The signal linkage logic of the pre-annealing anomaly judgment capability unit includes receiving the annealing anomaly judgment start signal, annealing current, annealing coefficient, annealing voltage and annealing liquid temperature as input parameters, and using the annealing anomaly judgment start signal as a trigger condition to switch the operating state from standby to operation. The system determines whether the annealing current, annealing coefficient, annealing voltage, and annealing liquid temperature are all within their respective preset compliance ranges. When all three parameters are within their preset compliance ranges, a valid annealing start signal is output as the output result. When any one of the parameters exceeds its corresponding compliance range, an invalid annealing start signal is output and an abnormality warning for the corresponding parameter is triggered.

5. The intelligent scheduling method for large-scale copper rod pulling process based on a capability framework as described in claim 4, characterized in that: The signal linkage logic of the annealing capability unit includes receiving the annealing start signal as an input parameter, using the annealing start signal as a trigger condition, and when the annealing start signal is a valid signal, switching the operating state from standby to running; when the annealing start signal is an invalid signal, maintaining standby and not starting. The drawn copper rod is then annealed. The output signal is used to initiate the take-up process. The signal linkage logic of the take-up capability unit includes receiving the take-up start signal, the take-up reel specifications and the take-up speed as input parameters, and using the take-up start signal as a trigger condition to switch the operating state from standby to operation; The annealed copper rod is wound up according to the specifications of the take-up reel and the take-up speed, and the real-time take-up speed is synchronously output to the scheduling framework; wherein, the specifications of the take-up reel are determined according to the copper wire length requirements; The output includes a finished copper wire take-up completion signal and a task completion signal; the task completion signal indicates that the large-scale copper rod pulling process has been completed.

6. The intelligent scheduling method for large-scale copper rod pulling process based on a capability framework as described in claim 5, characterized in that: The collaborative scheduling includes setting the baseline parameters of the standardized capability unit based on the target copper wire specifications, combined with historical data, and through the scheduling interface; the baseline parameters include wire feeding speed, wire drawing solution temperature, annealing current, annealing coefficient, annealing voltage, annealing solution temperature, and wire take-up speed. The scheduling framework receives the output results of the standardized capability unit in real time and displays the output results synchronously on the scheduling interface. The scheduling framework implements the orderly triggering of processes based on the signal linkage logic. The next capability unit is triggered to start execution based on the output result of the previous capability unit. When the parameters of a certain capability unit are non-compliant, an invalid signal is output, triggering the corresponding exception handling mechanism. When switching to the production of copper wire of different specifications, the baseline parameters are updated through the scheduling interface, and the updated baseline parameters are automatically synchronized to the corresponding standardized capability unit.

7. The intelligent scheduling method for large-scale copper rod pulling process based on a capability framework as described in claim 6, characterized in that: The coordinated constraint of tension state through virtual catenary includes: constructing virtual catenary geometric constraints based on the equipment spacing between the wire feeding capacity unit and the wire taking capacity unit, and setting a target virtual sag as a parameter of the ideal tension state; and generating a reference virtual arc length corresponding to the target virtual sag using a parabolic approximation fitting strategy. The timing line length deviation is generated by accumulating the difference sequence between the real-time wire feeding speed and the real-time wire taking speed. When the take-up reel is replaced or the production task is switched, the timing line length deviation is reset to zero. The timing line length deviation is superimposed on the reference virtual arc length to obtain the real-time virtual arc length that reflects the current physical extension state of the copper wire. Based on the geometric constraints of the virtual catenary, the real-time virtual sag of the copper wire is obtained by inversely solving the problem based on the geometric relationship between the equipment spacing and the real-time virtual arc length. The real-time virtual sag is compared with the target virtual sag to obtain the sag deviation. When the sag deviation is within the preset normal deviation range, the current take-up speed is kept constant. When the sag deviation exceeds the normal deviation range, the speed compensation amount is determined according to the positive and negative direction and the deviation amplitude of the sag deviation, and the speed compensation amount is added to the take-up speed of the take-up capacity unit.

8. A capability-based intelligent scheduling system for large-scale copper rod pulling processes, employing the method described in any one of claims 1-7, characterized in that: The standardized packaging module encapsulates the processes of the large-scale copper rod drawing process into standardized capability units. The standardized capability unit includes a wire feeding capability unit, a pre-drawing anomaly judgment capability unit, a wire drawing capability unit, a pre-annealing anomaly judgment capability unit, an annealing capability unit, and a take-up capability unit, which are connected in sequence by signals. Each standardized capability unit includes input parameters, output results, operating status, and triggering conditions. The data acquisition module collects equipment status data, process parameter data, product quality inspection data, and capability unit signal data of the standardized capability unit to establish a copper rod large-scale drawing process database. The scheduling framework operation module, based on the copper rod pulling process database, connects to the standardized capability unit through the scheduling framework and performs coordinated scheduling according to the signal linkage logic of the standardized capability unit; wherein, the output result of the previous capability unit serves as the trigger condition for the next capability unit, and the tension state is coordinated between the wire laying capability unit and the wire taking capability unit through a virtual catenary. The process monitoring module, based on the collaborative scheduling results, issues control commands to the standardized capability unit through the scheduling framework to execute the large-scale copper rod pulling process and monitors the process of the standardized capability unit.

9. A computer device, comprising: A memory and a processor; the memory stores a computer program, characterized in that: when the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

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