Drawing control method for copper wire drawing device and copper wire drawing device

Abstract

The application is suitable for the technical field of copper wire drawing, and particularly relates to a copper wire drawing device tension control method and a copper wire drawing device. The method comprises the following steps: obtaining tension damping response information corresponding to an acceleration perturbation signal applied by a drawing machine in a starting stage; obtaining an initial stiffness value based on the tension damping response information; determining a yielding action type according to the initial stiffness value; determining a yielding action parameter based on the yielding action type, and controlling the drawing machine based on the yielding action parameter. Therefore, the copper wire drawing device tension control method provided by the application can solve the problem of broken wires or disordered wires caused by the inability to quickly identify the system stiffness level.

Description

Technical Field

[0001] This application belongs to the field of copper wire drawing technology, and particularly relates to a method for controlling the stretching of copper wire drawing devices and copper wire drawing devices. Background Technology

[0002] Copper wire, as a flexible transmission medium, connects multiple rigid rotating pulleys and winches. During the wire drawing process, when the copper wire encounters a local hard point, the pulling force surges instantaneously. If the force is not unloaded in time, it can easily lead to wire breakage.

[0003] When overloaded, if the unloading range is too large, the copper wire will loosen instantly, lose its wrapping angle on the pulley, and cause skipped or tangled wires; if the unloading range is too small, the peak tension cannot be effectively reduced, and the risk of wire breakage still exists.

[0004] Current technologies primarily monitor wire tension in real time using sensors and utilize controllers such as PLCs and frequency converters to adjust the drive motor speed to maintain tension stability during the stretching process. In the event of overload or other abnormal conditions, the system performs tension release or yielding actions. The permissible unloading amplitude is directly related to the current system stiffness (higher stiffness results in better copper wire wrapping, allowing for greater tension release without tangling; lower stiffness leads to looser copper wire, and significant yielding immediately causes wire overlap). However, the material uniformity, microcrystalline structure, and wear condition of different batches of copper wire can all cause significant differences in system stiffness between batches. Current technologies either pre-set a uniform yielding strategy based on copper wire specifications or only passively respond after an overload occurs, lacking proactive identification and adaptation to batch-to-batch stiffness differences. Therefore, current technologies suffer from the problem of failing to quickly identify the system stiffness level, leading to wire breakage or tangling. Summary of the Invention

[0005] This application provides a method for controlling the stretching of a copper wire drawing device and a copper wire drawing device, which can solve the problem of wire breakage or tangled wires caused by the inability to quickly identify the system stiffness level.

[0006] In a first aspect, embodiments of this application provide a stretching control method for a copper wire drawing device, applied to a copper wire drawing device, the copper wire drawing device including a drawing machine and a control device; the method includes: Obtain the tension damping response information corresponding to the acceleration perturbation signal applied during the startup phase of the wire drawing machine; The initial stiffness value is obtained based on the tension damping response information; The type of yielding action is determined based on the initial stiffness value; wherein, the type of yielding action refers to a deep yielding action or a shallow yielding action; The yielding action parameters are determined based on the yielding action type, and the wire drawing machine is controlled based on the yielding action parameters; wherein, the yielding action parameters include a torque limit value and a duration.

[0007] The technical solutions described in this application embodiment have at least the following technical effects: The copper wire drawing device tension control method provided in this application actively applies a weak acceleration perturbation signal during the startup phase and uses a tension sensor to read the system's damping response, thereby deducing the initial stiffness value of the current batch. Based on this, it automatically selects the optimal yielding action type and specific torque limit value and duration parameters. This allows the copper wire drawing device to seamlessly adapt to differences in copper wires from different batches and the wear state of the die, maintaining a low wire breakage rate and tangled wire rate throughout the entire production cycle.

[0008] In one possible implementation of the first aspect, the method further includes: The corresponding operating parameters are obtained by simulation based on different combinations of control parameter values; wherein, the control parameters include stiffness threshold, first torque limit value and first duration corresponding to deep yielding, and second torque limit value and second duration corresponding to shallow yielding; and the operating parameters include tension response sequence, wire breakage rate and tangle rate. The functional relationship between the operating parameters and the control parameters is determined based on the combination of parameter values ​​in each group and the corresponding operating parameters.

[0009] In one possible implementation of the first aspect, determining the type of yielding action based on the initial stiffness value includes: Before the formal wire drawing begins, the stiffness threshold used to distinguish between deep and shallow yielding is optimized based on the first value range and the functional relationship to obtain a first optimized value; wherein, the first optimized value is used to determine whether to select a deep yielding action or a shallow yielding action when overloaded; The type of yielding action is determined based on the first optimized value and the initial stiffness value.

[0010] In one possible implementation of the first aspect, optimizing the stiffness threshold used to distinguish between deep and shallow yielding based on a first value range and the functional relationship to obtain a first optimized value includes: Initial sampling points are generated by sampling within the first value range; The first evaluation function value is obtained based on the initial sampling points and the functional relationship; wherein, the first evaluation function value is a weighted combination of the wire breakage rate and the tangled wire rate in the operating parameters; Based on each of the first evaluation function values, the current optimal sampling point is determined; wherein, the current optimal sampling point refers to the sampling point with the smallest first evaluation function value; Random sampling is performed within a local search neighborhood centered on the current best sampling point to generate candidate sampling points; The candidate sampling points are evaluated to obtain the corresponding first evaluation function value, and the current optimal sampling point is updated. The first optimized value is determined based on the current optimal sampling point.

[0011] In one possible implementation of the first aspect, the method further includes: If the first evaluation function value of the candidate sampling point is greater than or equal to the first evaluation function value of the current optimal sampling point, then the radius of the local search neighborhood is reduced.

[0012] In one possible implementation of the first aspect, determining the yielding action parameters based on the yielding action type and controlling the wire drawing machine based on the yielding action parameters includes: The control parameters to be optimized are determined based on the type of yielding action. When an overload is determined, the control parameters to be optimized are optimized based on the first optimized value and the functional relationship to obtain a second optimized value; wherein, the second optimized value is used to determine the specific torque limit value and duration of the selected yielding action; The yielding action parameters are obtained based on the first optimized value and the second optimized value.

[0013] In one possible implementation of the first aspect, optimizing the control parameter to be optimized based on the first optimized value and the functional relationship to obtain a second optimized value includes: Substitute the set of parameters corresponding to the current iteration point into the functional relationship to calculate the corresponding second evaluation function value; At the current iteration point, calculate the gradient direction and curvature information of the second evaluation function value relative to the control parameter to be optimized; Based on the gradient direction and the curvature information, a trial point is obtained by starting from the current iteration point with an initial step size; If the decrease in the value of the second evaluation function relative to the current iteration point does not meet the preset decrease condition, the step size is reduced by a preset ratio and the test is repeated until the preset decrease condition is met, and the current iteration point is updated with the step size that meets the preset decrease condition. Calculate the convergence criterion for the current iteration point; If the convergence criterion is less than the preset convergence tolerance, or the step size is less than the preset minimum step size, or the number of iterations reaches the preset maximum number of iterations, then the second optimized value is obtained based on the current iteration point.

[0014] In one possible implementation of the first aspect, determining the type of yielding action based on the first optimized value and the initial stiffness value includes: When the initial stiffness value is greater than or equal to the first optimized value, the type of yielding action is determined to be a deep yielding action; When the initial stiffness value is less than the first optimized value, the type of yielding action is determined to be a shallow yielding action.

[0015] In one possible implementation of the first aspect, before optimizing the control parameter to be optimized based on the first optimized value and the functional relationship to obtain the second optimized value when an overload is determined, the following steps are included: Obtain real-time drawing tension; The real-time drawing tension is compared with the preset drawing tension to obtain the tension deviation; The rate of change of the tension deviation is obtained by differentiating the deviation over time. Within a sliding time window, the maximum value of the tension deviation is determined as the tension peak value for the current time period; If the absolute value of the deviation change rate exceeds the warning threshold and the tension peak exceeds the tension limit threshold, then an overload is determined.

[0016] Secondly, embodiments of this application provide a tension control device for a copper wire drawing apparatus, comprising: The acquisition module is used to acquire the tension damping response information corresponding to the acceleration perturbation signal applied to the wire drawing machine during the start-up phase; An initial stiffness value module is used to obtain an initial stiffness value based on the tension damping response information; The yielding action type module is used to determine the yielding action type based on the initial stiffness value; wherein, the yielding action type refers to a deep yielding action or a shallow yielding action; The yielding action parameter module is used to determine yielding action parameters based on the yielding action type, and to control the wire drawing machine based on the yielding action parameters; wherein, the yielding action parameters include a torque limit value and a duration.

[0017] Thirdly, embodiments of this application provide a copper wire drawing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any one of the first aspects above.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any of the first aspects above.

[0019] Fifthly, embodiments of this application provide a computer program product that, when run on a copper wire drawing device, causes the copper wire drawing device to perform the method described in any one of the first aspects above.

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

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

[0022] Figure 1 This is a schematic flowchart of a copper wire drawing device stretching control method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the implementation process of steps S300, S310 and S320 in the stretching control method of the copper wire drawing device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the implementation process of steps S400, S420 and S430 in the stretching control method of the copper wire drawing device provided in an embodiment of this application; Figure 4 This is a schematic diagram of another implementation of step S420 in the stretching control method of the copper wire drawing device provided in an embodiment of this application; Figure 5 This is a schematic diagram of tension damping response information in the tension control method of the copper wire drawing device provided in an embodiment of this application; Figure 6 This is a schematic diagram of the real-time drawing tension in the stretching control method of the copper wire drawing device provided in an embodiment of this application; Figure 7 This is a schematic diagram of the tension control device of the copper wire drawing device provided in the embodiments of this application; Figure 8 This is a schematic diagram of the copper wire drawing device provided in the embodiments of this application. Detailed Implementation

[0023] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0024] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0025] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0026] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0027] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0028] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0029] In related technologies, wire tension is primarily monitored in real time using sensors, and the speed of the drive motor is adjusted using controllers such as PLCs and frequency converters to maintain tension stability during the stretching process. In case of overload or other abnormal conditions, the system performs tension release or yielding actions. The allowable unloading range is directly related to the current system stiffness (higher stiffness results in better copper wire wrapping, allowing for greater tension release without tangling; lower stiffness leads to looser copper wire, and significant yielding will immediately cause wire overlap). However, the material uniformity, microcrystalline structure, and wear condition of different batches of copper wire can all cause significant differences in system stiffness between batches. Existing technologies either pre-set a uniform yielding strategy based on copper wire specifications or only passively respond after an overload occurs, lacking proactive identification and adaptation to batch-to-batch stiffness differences. Therefore, existing technologies suffer from the problem of failing to quickly identify the system stiffness level, leading to wire breakage or tangling.

[0030] To address the aforementioned issues, this application provides a tension control method for a copper wire drawing device and a copper wire drawing device itself. In this method, the tension damping response information corresponding to the acceleration perturbation signal applied during the start-up phase of the drawing machine is acquired; an initial stiffness value is obtained based on the tension damping response information; the type of yielding action is determined based on the initial stiffness value; yielding action parameters are determined based on the yielding action type; and the drawing machine is controlled based on the yielding action parameters. Therefore, the tension control method for the copper wire drawing device provided in this application, without generating impact tension spikes (i.e., without damage), accurately obtains the initial stiffness value using damping response characteristics. It automatically maps the unknown mechanical conditions at each start-up to known yielding action parameters through a closed loop, enabling the copper wire drawing device to seamlessly adapt to differences in copper wire batches and die wear conditions, maintaining a low wire breakage rate and tangled wire rate throughout the entire production cycle.

[0031] The copper wire drawing device stretching control method provided in this application embodiment can be applied to a copper wire drawing device. In this case, the copper wire drawing device is the executing subject of the copper wire drawing device stretching control method provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of copper wire drawing device.

[0032] For example, a copper wire drawing device may include a drawing machine and a control device. The control device is used to control the drawing machine. The control device may be an embedded control system, an industrial computer, a programmable logic controller, a distributed control system, etc., but is not limited to these.

[0033] To better understand the stretching control method of the copper wire drawing device provided in the embodiments of this application, the specific implementation process of the stretching control method of the copper wire drawing device provided in the embodiments of this application will be described by way of example below.

[0034] Figure 1This paper illustrates a schematic flowchart of a copper wire drawing device stretching control method provided in an embodiment of this application. The copper wire drawing device stretching control method includes: S100 acquires the tension damping response information corresponding to the acceleration perturbation signal applied during the start-up phase of the wire drawing machine.

[0035] It can be understood that tension damping response information refers to data on how tension changes over time, such as... Figure 5 As shown.

[0036] For example, a small and brief acceleration perturbation signal can be applied during the start-up phase of the wire drawing machine. This acceleration perturbation signal is typically in pulse or step form, and its amplitude should be controlled within a safe range (e.g., 0.05~0.2 m / s²) that will not cause plastic deformation or breakage of the copper wire. 2 The duration is approximately 0.1 to 0.3 seconds. Simultaneously, a high-response tension sensor (sampling frequency not less than 500Hz) installed on the tension lever or pressure sensor continuously collects tension change data on the copper wire to obtain the corresponding tension damping response information.

[0037] S200, the initial stiffness value is obtained based on the tension damping response information.

[0038] For example, the damping ratio ζ can be calculated from the ratio of adjacent peak values ​​of the response curve, based on the oscillation period T. d Find the undamped natural frequency ω n =2π / (T d The initial stiffness value K=m is obtained based on the system's equivalent mass m (which can be estimated through offline weighing or CAD model). ω n 2 .

[0039] On the obtained ΔT(t) curve, mark the amplitude of the first positive wave peak A1 (corresponding to the maximum tension increment) and the amplitude of the second positive wave peak A2, and calculate the logarithmic attenuation rate Λ=ln(A1 / A2), and the damping ratio ζ=Λ / Record the time t1 when one peak appears and the time t2 when another adjacent peak appears on the response curve, with the oscillation period T. d =t2−t1.

[0040] The moments of inertia of all rotating parts (motor rotor, traction wheel, guide wheel) and the mass of linear moving parts (tension swing arm, copper wire segment) can be uniformly converted into the total moment of inertia in the direction of the copper wire's linear motion, according to the principle of energy conservation. Let the total moment of inertia of the traction wheel (including the motor rotor) be J. total (Unit: kg) m 2The working radius of the traction wheel is r (unit: m). According to the law of conservation of kinetic energy (rotational kinetic energy of 0.5 Jω² equals linear kinetic energy of 0.5 m),... rot v 2 And v=ω r), equivalent mass m converted to a straight line rot =J total / r 2 The mass m of the part of the copper wire that moves directly between the traction wheel and the pay-off wheel. wire Add them in. The moment of inertia of the tension lever is converted into a linear equivalent mass m according to the lever ratio. arm The system's equivalent mass is m = m rot +m wire +m arm .

[0041] S300, determine the type of yielding action based on the initial stiffness value. The type of yielding action refers to deep yielding action or shallow yielding action.

[0042] For example, the wire drawing machine can be started at different stiffness levels, and the peak tension and breakage rate can be recorded to find the stiffness value corresponding to the critical breakage as the critical stiffness threshold. Alternatively, the equivalent stiffness corresponding to 30% of the copper wire breaking tension can be taken as the critical stiffness threshold. The initial stiffness value is compared with the critical stiffness threshold to determine the type of yielding action. If the initial stiffness value is greater than or equal to the critical stiffness threshold, it is determined to be a deep yielding action; if the initial stiffness value is less than the critical stiffness threshold, it is determined to be a shallow yielding action.

[0043] S400 determines the retraction action parameters based on the retraction action type and controls the wire drawing machine based on the retraction action parameters. The retraction action parameters include the torque limit value and the duration.

[0044] For example, the deep yield torque limit value can be set to 20% to 35% of the rated torque, and the duration of the deep yield is determined by the time required to accelerate to the target speed; the shallow yield torque limit value can be set to 60% to 85% of the rated torque, and the duration of the shallow yield is determined by the damping decay time. For example, the deep yield torque limit value T deep =T rated ×[0.20+0.15 (K−K) th ) / (K max -K th The duration of the deep retreat is t. deep =v target η / a deep , among which, T rated K is the rated torque, and K is the initial stiffness value. th K is the critical stiffness threshold. max To preset the maximum stiffness, vtarget Let a be the target linear velocity. deep The actual acceleration under deep yield limit is given by η, a safety factor (1.2~1.5) used to cover the decay time of residual oscillations after the yield ends. Shallow yield torque limit value T. shallow =T rated ×(0.85−0.25 K / K th The duration t of the shallow retreat. shallow =t decay ×λ, where t decay =3 / (ζω n ), ζ and ω n It has been calculated in S200, where λ is the redundancy coefficient (1.2~1.5).

[0045] In one possible implementation, please refer to Figure 2 The methods also include: S500 simulates and obtains the corresponding operating parameters based on different combinations of control parameter values. The control parameters include stiffness threshold, first torque limit value and first duration corresponding to deep yielding, and second torque limit value and second duration corresponding to shallow yielding. The operating parameters include tension response sequence, wire breakage rate, and wire tangle rate.

[0046] For example, a dynamic simulation model can be constructed, which includes: a mechanical dynamics model: the output torque M(t) of the drive motor is converted into a traction force F(t) through the transmission ratio and radius, acting on the equivalent mass m, and simultaneously subjected to the reaction of the elastic force (stiffness K) and damping force (damping coefficient C) of the copper wire, i.e., m (t)+C (t)+Kx(t)=F(t)−F fric Where x(t) is the difference between the arc length of the traction wheel rotation and the release length of the wire feeding wheel, i.e., the real-time elastic elongation of the copper wire. (t) is the elongation rate of the copper wire. F(t) is the elongation acceleration of the copper wire, and F(t) is derived from the motor output torque M(t) through the transmission ratio and radius conversion, i.e., F(t) = M(t) / r (where r is the radius of the traction wheel). fric (Equivalent friction) is the sliding friction from the bearing, copper wire, and mold wall as part of the system damping (usually set as a constant, such as 10N). K (equivalent stiffness) is the axial tensile stiffness of the copper wire itself, determined by the material's elastic modulus and length. C (equivalent damping coefficient) simulates the energy dissipation at the internal friction and mechanical hinges of the copper wire material, usually determined by experimental hammering or by referring to empirical values ​​(such as C=20~50 N). The torque after limiting is set (s / m). Substituting the torque after limiting, the traction force acting on the linear motion system is obtained. Then, the displacement x(t) is solved using numerical integration. Based on the displacement, the tension response sequence T(t) = K is calculated. x(t) + T0, where T0 is the initial static tension, generated by the mechanical preload. Failure model: used to calculate the wire breakage rate and the wire tangling rate. A wire breakage is determined when the tension at any moment in the simulation exceeds the known preset copper wire breaking force, based on the tension response sequence. A wire tangling is determined when the tension fluctuation is too large (e.g., the peak value minus the trough value exceeds 50% of the preset steady-state tension) or when reverse tension occurs (negative tension, indicating copper wire slack), based on the tension response sequence.

[0047] The Monte Carlo method can be used to repeatedly simulate the same set of control parameters using a dynamic simulation model, with random equipment noise (such as friction fluctuation ±5% and stiffness fluctuation ±3%) added each time. The tension response sequence is obtained through the mechanical dynamics model, and the number of wire breakages and wire tangles is statistically analyzed through the failure model to obtain the wire breakage rate and wire tangling rate.

[0048] S600 determines the functional relationship between operating parameters and control parameters based on the combination of parameter values ​​for each group and the corresponding operating parameters.

[0049] For example, an analytical function or regression model can be fitted to each set of parameter values ​​and the corresponding operating parameters to determine the functional relationship between the operating parameters and the control parameters. For instance, the sets of parameter values ​​and the corresponding operating parameters can be divided into training and test sets in an 8:2 ratio. Coefficients are fitted on the training set, and the coefficient of determination R is calculated on the test set. 2 And the root mean square error RMSE, if R 2 If the value is greater than 0.90 and RMSE is less than 1.5%, then a second-order response surface model is obtained. The functional relationship between the operating parameters and control parameters is determined based on the second-order response surface model.

[0050] Through steps S500 to S600, a functional relationship between parameters and operational performance is established through simulation, allowing parameters to be automatically matched based on actual stiffness. By incorporating both wire breakage rate and tangled wire rate as operational parameters into the functional relationship, multi-objective balanced optimization is achieved. The optimal solution can be obtained by quickly traversing parameter combinations on a computer and then downloaded to the controller, which helps shorten the debugging cycle.

[0051] In one possible implementation, please refer to Figure 2 S300, the type of yielding action is determined based on the initial stiffness value, including: S310, before the formal wire drawing begins, based on the first value range and functional relationship, the stiffness threshold used to distinguish between deep and shallow yielding is optimized to obtain a first optimized value. This first optimized value is used to determine whether to select a deep or shallow yielding action in case of overload.

[0052] For example, for each sampling point in the first value range The expected cost J is calculated using numerical integration (such as the trapezoidal integral method). )= (K, ) p(K)dK, where, [K min ,K max That is, the first range of values, C(K, The coefficient J is a weighted combination of wire breakage rate and wire scrambling rate (where the wire breakage rate and wire scrambling rate are obtained by substituting the stiffness values ​​corresponding to the sampling points into the functional relationship, based on the preset torque limit value and duration known before the formal wire drawing begins). The system stiffness K of the copper wire will randomly fluctuate within a certain range depending on the batch, wire diameter, and die wear degree. This fluctuation follows a priori distribution p(K), which is obtained by statistically analyzing historical production data. The minimum J( ) corresponding This is the first optimal value.

[0053] S320, determine the type of yielding action based on the first optimized value and the initial stiffness value.

[0054] For example, the type of yielding action can be determined by comparing the initial stiffness value with a first optimized value. If the initial stiffness value is greater than or equal to the first optimized value, it is determined to be a deep yielding action; if the initial stiffness value is less than the first optimized value, it is determined to be a shallow yielding action.

[0055] Through steps S310 to S320, the corresponding torque limit value and duration are read from a preset parameter table according to the determined action type. By introducing a cost function and a priori stiffness distribution, the threshold is quantitatively optimized so that it matches the stiffness statistical characteristics in actual production. This achieves closed-loop, adaptive selection of yielding action type, which is beneficial for improving robustness in response to fluctuations in operating conditions.

[0056] Optionally, please refer to Figure 2 In S310, based on the first value range and functional relationship, the stiffness threshold used to distinguish between deep and shallow yielding is optimized to obtain the first optimized value, including: S311, sample and generate initial sampling points within the first value range.

[0057] For example, initial sampling points can be generated using Latin hypercube sampling (LHS) or uniform random sampling within a first range of values.

[0058] S312, the corresponding first evaluation function value is obtained based on the initial sampling points and functional relationships. The first evaluation function value is a weighted combination of the wire breakage rate and the tangled wire rate in the operating parameters.

[0059] For example, it could be for a certain initial sampling point Calculate the wire breakage rate R at the stiffness value corresponding to the initial sampling point based on the functional relationship. break (K) and random line rate R tangle (K). Define a single-point cost function C(K, C(K, ) is a weighted combination of broken thread rate and tangled thread rate: )= R break (K, )+β R tangle (K, ), where the weights can be taken as follows: =1, β=0.3~0.5. First evaluation function value J( )= (K, ) p(K)dK, where, [K min ,K max That is, the first range of values, p(K), is obtained by statistically analyzing historical production data.

[0060] S313, determine the current optimal sampling point based on the values ​​of each first evaluation function. The current optimal sampling point is the sampling point with the smallest first evaluation function value.

[0061] For example, the sampling point with the smallest first evaluation function value in the initial set of sampling points can be selected as the current optimal sampling point. If multiple sampling points have the same smallest first evaluation function value, one of them (such as the sampling point with the largest value) can be selected as the current optimal sampling point.

[0062] S314, Random sampling is performed within the local search neighborhood centered on the current optimal sampling point to generate candidate sampling points.

[0063] For example, random uniform sampling or equidistant sampling can be performed within a local search neighborhood centered on the current optimal sampling point to generate multiple candidate sampling points.

[0064] S315: Evaluate the candidate sampling points to obtain the corresponding first evaluation function value, and update the current optimal sampling point.

[0065] For example, a first evaluation function value can be calculated for each candidate sampling point, and these first evaluation function values ​​can be compared with the first evaluation function value corresponding to the current optimal sampling point. If there exists a candidate sampling point whose first evaluation function value is less than the current optimal sampling point, then the candidate sampling point with the smallest first evaluation function value is updated as the current optimal sampling point.

[0066] S316, determine the first optimized value based on the current optimal sampling point.

[0067] For example, the current optimal sampling point obtained after several rounds of iteration (the maximum number of iterations can be set, such as 10 times, or stop when the neighborhood radius shrinks to less than a preset threshold) can be determined as the first optimal value.

[0068] Through the steps S311 to S316 above, by initial sampling and local search, the optimal solution can be approximated by evaluating only a few points, which helps to reduce the amount of computation.

[0069] In one possible implementation, please refer to Figure 2 The methods also include: S317 If the first evaluation function value of a candidate sampling point is greater than or equal to the first evaluation function value of the current optimal sampling point, then the radius of the local search neighborhood is reduced.

[0070] For example, in each round of local search, if the first evaluation function value of all candidate points is greater than or equal to the first evaluation function value of the current optimal sample point, then the radius of the local search neighborhood is reduced. For example, a shrinkage coefficient γ∈(0,1) can be introduced, which can be taken as γ=0.5 or 0.618, and the new radius r new =γ r old .

[0071] By using step S317 above, by gradually narrowing the neighborhood and forcing higher-density sampling near the current optimal sampling point, subtle local changes that were ignored due to the sparse initial sampling points can be revealed.

[0072] In one possible implementation, please refer to Figure 3 S400, determining the retraction action parameters based on the retraction action type, and controlling the wire drawing machine based on the retraction action parameters, including: S410, determine the control parameters to be optimized based on the type of yielding action.

[0073] For example, if it is a deep yielding action, the control parameters to be optimized are the deep yielding torque limit value and the deep yielding duration; if it is a shallow yielding action, the control parameters to be optimized are the shallow yielding torque limit value and the shallow yielding duration.

[0074] S420, under the condition of overload, optimizes the control parameters to be optimized based on the first optimized value and the functional relationship to obtain the second optimized value. The second optimized value is used to determine the specific torque limit value and duration of the selected yielding action.

[0075] For example, a tension sensor can be used to monitor in real time, and if the tension exceeds a preset threshold (e.g., 70% of the breaking tensile force) or the rate of tension change exceeds a tension change rate limit (e.g., 2000 N / s), an overload is determined. A coarse grid is then defined within the parameter range (e.g., torque limit value T). lim Divided into 5 levels, duration t hold Divided into 5 levels, with a total of 25 grid points. For deep yielding actions: T lim Take [2.0, 2.375, 2.75, 3.125, 3.5]N m; t hold Take [1.5, 1.875, 2.25, 2.625, 3.0]s. For a shallow yielding action: T lim Take [6.0, 6.625, 7.25, 7.875, 8.5]N m; t hold Using [0.3, 0.425, 0.55, 0.675, 0.8]s, calculate the cost J for all grid points. local (T) lim , t hold )= R break +β R tangle , where R break It is the disconnection rate, R tangle It is the tangled wire rate (the broken wire rate and tangled wire rate are obtained by substituting the torque limit value and duration into the functional relationship when the first optimization value, i.e. the stiffness threshold, is known). =1, β=0.5, take the torque limit value and duration corresponding to the grid point with the minimum cost as the second optimization value.

[0076] S430, the yielding action parameters are obtained based on the first optimization value and the second optimization value.

[0077] For example, the type of yielding action can be determined based on a first optimization value, and the optimal torque limit and duration under that yielding action type can be determined based on a second optimization value.

[0078] Through steps S410 to S430 above, and the real-time optimization (or offline pre-optimization + online table lookup) in S420, the yield parameters can be dynamically adjusted according to the currently estimated stiffness. In the event of overload, optimization is triggered immediately, calculating and executing the optimal yield parameters in an extremely short time (milliseconds).

[0079] Optionally, please refer to Figure 3 S420, based on the first optimized value and the functional relationship, optimize the control parameters to be optimized to obtain the second optimized value, including: S421, substitute a set of parameters corresponding to the current iteration point into the function relationship, and calculate the corresponding second evaluation function value.

[0080] For example, a functional relationship can be used. Given the first optimization value, i.e., the stiffness threshold, a set of parameters corresponding to the current iteration point can be substituted into the functional relationship to obtain the breakage rate and the scrambled rate. Based on the breakage rate and the scrambled rate, the second evaluation function value can be calculated. For example, the second evaluation function value J... local (T) lim , t hold )= R break +β R tangle , where R break It is the disconnection rate, R tangle It's the rate of random lines. =1, β=0.5.

[0081] S422, at the current iteration point, calculate the gradient direction and curvature information of the second evaluation function value relative to the control parameters to be optimized.

[0082] For example, the gradient direction can be obtained by taking the partial derivative of the quadratic response surface model fitted by S600, and the curvature information can be obtained by calculating the rate of change of the directional derivative along the gradient direction. For example, the quadratic response surface model J = β0 + β1T + β2t + β 11 T 2 +β 22 t 2 +β 12 Tt, where T and t represent the torque limiting value and duration, respectively. g T =∂J / ∂T=β1+2β 11 T+β 12 t, g t =∂J / ∂t=β²+2β 22 t+β 12 T. Set the current iteration point (T) k ,t k Substituting into the above equation, we obtain the gradient vector g = (g T ,g tThe descent direction is the negative gradient direction: d = −g = (−g) T ,−g t Hessian matrix H= The curvature of the directional derivative of direction dd (i.e., the second directional derivative, or curvature information) is H. dd =d T H d.

[0083] S423, based on the gradient direction and curvature information, starts from the current iteration point and explores with the initial step size to obtain the trial point.

[0084] For example, a trial point can be obtained by taking a step along the direction that causes the function value to decrease (the negative gradient direction), with the step size determined by the initial step size. Initial step size = g 2 / H dd ,in, g 2 =g T 2 +g t 2 It is the square of the gradient magnitude.

[0085] S424, if the decrease in the second evaluation function value of the trial point relative to the current iteration point does not meet the preset decrease condition, then the step size is reduced by a preset ratio and the trial is repeated until the preset decrease condition is met, and the current iteration point is updated with the step size that meets the preset decrease condition.

[0086] For example, the preset descent condition can be an Armijo condition. If the decrease in the second evaluation function value of the trial point relative to the current iteration point does not meet the preset descent condition, the step size is reduced by a preset ratio (e.g., 50%), and the calculation is repeated with the reduced step size until the preset descent condition is met. If the preset descent condition is met, the trial point is accepted as the current iteration point.

[0087] S425, calculate the convergence criterion for the current iteration point.

[0088] For example, the convergence criterion can be the change in parameters. The change in parameters can be obtained by calculating the Euclidean distance between the control parameter vectors between two adjacent iterations.

[0089] S426 If the convergence judgment index is less than the preset convergence tolerance, or the step size is less than the preset minimum step size, or the number of iterations reaches the preset maximum number of iterations, then the second optimization value is obtained based on the current iteration point.

[0090] For example, optimization can be terminated and the current iteration point is output as the second optimization value as long as any of the following conditions are met: the convergence criterion is less than the preset convergence tolerance, the step size is less than the preset minimum step size, or the number of iterations reaches the preset maximum number of iterations.

[0091] Through steps S421 to S426, the gradient and curvature are calculated to ensure the search proceeds along the steepest descent direction, significantly reducing the number of iterations. A backtracking search is employed, dynamically adjusting the step size to guarantee sufficient function value descent in each iteration while avoiding excessively small step sizes. A convergence criterion is provided, facilitating timely termination near the optimum and conserving computational resources. The introduced step size condition prevents premature termination due to numerical errors.

[0092] Optionally, please refer to Figure 2 S320, determine the type of yielding action based on the first optimized value and the initial stiffness value, including: S321, when the initial stiffness value is greater than or equal to the first optimization value, the type of retreat action is determined to be deep retreat action.

[0093] For example, the initial stiffness value can be compared with the first optimized value, and if it is determined that the initial stiffness value is greater than or equal to the first optimized value, the type of retreat action is determined to be a deep retreat action.

[0094] S322, when the initial stiffness value is less than the first optimization value, the type of yielding action is determined to be shallow yielding action.

[0095] For example, the initial stiffness value can be compared with the first optimized value, and if it is determined that the initial stiffness value is less than the first optimized value, the type of retreat action is determined to be a shallow retreat action.

[0096] Through the above steps S321 to S322, the system stiffness is measured and quantified in real time and objectively compared with the statistically optimized threshold, which helps to eliminate the interference of human factors and improve the automation level of the production line.

[0097] Optionally, please refer to Figure 4 S420, under the condition of overload, before optimizing the control parameters to be optimized based on the first optimized value and the functional relationship to obtain the second optimized value, includes: S4201, obtains real-time drawing tension.

[0098] For example, real-time drawing tension is the axial tensile force borne by the copper wire during the drawing process, which can be continuously measured by a force sensor installed on a tension swing arm or force measuring roller, such as... Figure 6 As shown.

[0099] S4202 compares the real-time drawing tension with the preset drawing tension to obtain the tension deviation.

[0100] For example, the preset drawing tension can be set according to the diameter of the copper wire. For instance, for a copper wire with a diameter of 0.3 mm, the preset drawing tension is typically 40~60 N. The tension deviation is obtained by calculating the difference between the real-time drawing tension and the preset tension.

[0101] S4203, by differentiating the tension deviation over time, obtains the rate of change of the deviation.

[0102] For example, the rate of change of deviation can be obtained using the backward difference formula. (t i )=[e(t i )−e(t i−1 )] / Δt, where e(t) i ) represents the current racket tension deviation, e(t) i−1 ) represents the tension deviation of the previous beat (i.e., Δt seconds ago).

[0103] S4204 determines the maximum value of the tension deviation within a sliding time window as the tension peak value for the current period.

[0104] For example, the length of the sliding time window can be preset, and the maximum value of the tension deviation can be found by traversing the current sliding time window to obtain the tension peak value.

[0105] S4205, if the absolute value of the deviation change rate exceeds the warning threshold and the tension peak exceeds the tension limit threshold, then overload is determined.

[0106] For example, the tension limit threshold e can be set according to the breaking tensile force of the copper wire. lim To maintain a safety margin, for example, if the tension deviation corresponding to the copper wire breaking force is 35N (copper wire breaking force 85N minus the preset tension 50N), then take e. lim =30N (85%). Warning threshold for the rate of change of deviation. th The value can be 500~1000 N / s, such as th =800 N / s. Overload is determined when the absolute value of the deviation change rate exceeds the warning threshold and the peak tension exceeds the tension limit threshold.

[0107] Through the steps S4201 to S4205 described above, impact overload and slow over-limit are effectively distinguished. By calculating the rate of change of deviation, an early warning can be issued when the tension has not yet reached its limit but the rate of increase is extremely rapid, thus buying time for the yielding action. Using the maximum value within the sliding window instead of the instantaneous value helps prevent misjudgments caused by single-point noise or glitch.

[0108] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0109] Corresponding to the copper wire drawing device stretching control method described in the above embodiments, this application also provides a copper wire drawing device stretching control device, the various modules of which can realize the various steps of the copper wire drawing device stretching control method. Figure 7 The diagram shows a structural block diagram of the stretching control device of the copper wire drawing apparatus provided in the embodiment of this application. For ease of explanation, only the parts related to the embodiment of this application are shown.

[0110] Reference Figure 7 The device includes: The acquisition module is used to acquire the tension damping response information corresponding to the acceleration perturbation signal applied to the wire drawing machine during the start-up phase; An initial stiffness value module is used to obtain an initial stiffness value based on the tension damping response information; The yielding action type module is used to determine the yielding action type based on the initial stiffness value; wherein, the yielding action type refers to a deep yielding action or a shallow yielding action; The yielding action parameter module is used to determine yielding action parameters based on the yielding action type, and to control the wire drawing machine based on the yielding action parameters; wherein, the yielding action parameters include a torque limit value and a duration.

[0111] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0112] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0113] This application also provides a copper wire drawing device. Figure 8 This is a schematic diagram of the structure of a copper wire drawing device provided in one embodiment of this application. Figure 8 As shown, the control device in the copper wire drawing device 8 of this embodiment includes: at least one processor 80 ( Figure 8 Only one is shown in the image), at least one memory 81 ( Figure 8 (Only one is shown in the image) and a computer program 82 stored in the at least one memory 81 and executable on the at least one processor 80. When the processor 80 executes the computer program 82, it causes the copper wire drawing device 8 to perform the steps in any of the above embodiments of the copper wire drawing device stretching control method, or causes the copper wire drawing device 8 to perform the functions of each module / unit in the above embodiments of the device.

[0114] For example, the computer program 82 can be divided into one or more modules / units, which are stored in the memory 81 and executed by the processor 80 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 82 in the copper wire drawing device 8.

[0115] The copper wire drawing device 8 may include a drawing machine and a control device. The control device is used to control the drawing machine and may be an embedded control system, an industrial computer, a programmable logic controller, a distributed control system, a desktop computer, a laptop, a handheld computer, or a cloud server, etc. The copper wire drawing device may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art will understand that... Figure 8 This is merely an example of the copper wire drawing device 8 and does not constitute a limitation on the copper wire drawing device 8. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0116] The processor 80 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0117] In some embodiments, the memory 81 can be an internal storage unit of the copper wire drawing device 8, such as a hard disk or memory of the copper wire drawing device 8. In other embodiments, the memory 81 can be an external storage device of the copper wire drawing device 8, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the copper wire drawing device 8. Further, the memory 81 can include both internal storage units and external storage devices of the copper wire drawing device 8. The memory 81 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 81 can also be used to temporarily store data that has been output or will be output.

[0118] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0119] This application provides a computer program product that, when run on a copper wire drawing device, enables the copper wire drawing device to perform the steps described in any of the above method embodiments.

[0120] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate form. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the copper wire drawing device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0121] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0123] In the embodiments provided in this application, it should be understood that the disclosed copper wire drawing apparatus and method can be implemented in other ways. For example, the copper wire drawing apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0124] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0125] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for controlling the stretching of a copper wire drawing device, characterized in that, The method is applied to a copper wire drawing device, which includes a drawing machine and a control device; the method includes: Obtain the tension damping response information corresponding to the acceleration perturbation signal applied during the startup phase of the wire drawing machine; The initial stiffness value is obtained based on the tension damping response information; The type of yielding action is determined based on the initial stiffness value; wherein, the type of yielding action refers to a deep yielding action or a shallow yielding action; The yielding action parameters are determined based on the yielding action type, and the wire drawing machine is controlled based on the yielding action parameters; wherein, the yielding action parameters include a torque limit value and a duration.

2. The stretching control method for the copper wire drawing device as described in claim 1, characterized in that, The method further includes: The corresponding operating parameters are obtained by simulation based on different combinations of control parameter values; wherein, the control parameters include stiffness threshold, first torque limit value and first duration corresponding to deep yielding, and second torque limit value and second duration corresponding to shallow yielding; and the operating parameters include tension response sequence, wire breakage rate and tangle rate. The functional relationship between the operating parameters and the control parameters is determined based on the combination of parameter values ​​in each group and the corresponding operating parameters.

3. The stretching control method for the copper wire drawing device as described in claim 2, characterized in that, Determining the type of yielding action based on the initial stiffness value includes: Before the formal wire drawing begins, the stiffness threshold used to distinguish between deep and shallow yielding is optimized based on the first value range and the functional relationship to obtain a first optimized value; wherein, the first optimized value is used to determine whether to select a deep yielding action or a shallow yielding action when overloaded; The type of yielding action is determined based on the first optimized value and the initial stiffness value.

4. The stretching control method for the copper wire drawing device as described in claim 3, characterized in that, The first optimized value is obtained by optimizing the stiffness threshold used to distinguish between deep and shallow yielding based on the first value range and the functional relationship, including: Initial sampling points are generated by sampling within the first value range; The first evaluation function value is obtained based on the initial sampling points and the functional relationship; wherein, the first evaluation function value is a weighted combination of the wire breakage rate and the tangled wire rate in the operating parameters; Based on each of the first evaluation function values, the current optimal sampling point is determined; wherein, the current optimal sampling point refers to the sampling point with the smallest first evaluation function value; Random sampling is performed within a local search neighborhood centered on the current best sampling point to generate candidate sampling points; The candidate sampling points are evaluated to obtain the corresponding first evaluation function value, and the current optimal sampling point is updated. The first optimized value is determined based on the current optimal sampling point.

5. The stretching control method for the copper wire drawing device as described in claim 4, characterized in that, The method further includes: If the first evaluation function value of the candidate sampling point is greater than or equal to the first evaluation function value of the current optimal sampling point, then the radius of the local search neighborhood is reduced.

6. The stretching control method for the copper wire drawing device as described in claim 3, characterized in that, The step of determining the yielding action parameters based on the yielding action type and controlling the wire drawing machine based on the yielding action parameters includes: The control parameters to be optimized are determined based on the type of yielding action. When an overload is determined, the control parameters to be optimized are optimized based on the first optimized value and the functional relationship to obtain a second optimized value; wherein, the second optimized value is used to determine the specific torque limit value and duration of the selected yielding action; The yielding action parameters are obtained based on the first optimized value and the second optimized value.

7. The stretching control method for the copper wire drawing device as described in claim 6, characterized in that, The step of optimizing the control parameter to be optimized based on the first optimized value and the functional relationship to obtain a second optimized value includes: Substitute the set of parameters corresponding to the current iteration point into the functional relationship to calculate the corresponding second evaluation function value; At the current iteration point, calculate the gradient direction and curvature information of the second evaluation function value relative to the control parameter to be optimized; Based on the gradient direction and the curvature information, a trial point is obtained by starting from the current iteration point with an initial step size; If the decrease in the value of the second evaluation function relative to the current iteration point does not meet the preset decrease condition, the step size is reduced by a preset ratio and the test is repeated until the preset decrease condition is met, and the current iteration point is updated with the step size that meets the preset decrease condition. Calculate the convergence criterion for the current iteration point; If the convergence criterion is less than the preset convergence tolerance, or the step size is less than the preset minimum step size, or the number of iterations reaches the preset maximum number of iterations, then the second optimized value is obtained based on the current iteration point.

8. The tension control method for the copper wire drawing device as described in claim 3, characterized in that, Determining the type of yielding action based on the first optimized value and the initial stiffness value includes: When the initial stiffness value is greater than or equal to the first optimized value, the type of yielding action is determined to be a deep yielding action; When the initial stiffness value is less than the first optimized value, the type of yielding action is determined to be a shallow yielding action.

9. The stretching control method for the copper wire drawing device as described in claim 6, characterized in that, Before optimizing the control parameter to be optimized based on the first optimized value and the functional relationship when an overload is determined, to obtain the second optimized value, the following steps are included: Obtain real-time drawing tension; The real-time drawing tension is compared with the preset drawing tension to obtain the tension deviation; The rate of change of the tension deviation is obtained by differentiating the deviation over time. Within a sliding time window, the maximum value of the tension deviation is determined as the tension peak value for the current time period; If the absolute value of the deviation change rate exceeds the warning threshold and the tension peak exceeds the tension limit threshold, then an overload is determined.

10. A copper wire drawing device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

Images