Control method, system, device and medium for roller welder

Abstract

The application provides a control method, system, device and medium of a roll welding machine, comprising: obtaining a material type and a material thickness of a first material to be welded by the roll welding machine currently, and a set reference speed of a motor of a welding roller group in the roll welding machine; determining a target proportional coefficient, a target integral coefficient and a target differential coefficient corresponding to a current working condition according to the material type and the material thickness; determining a tension deviation between a current actual tension value and a set tension value of the first material; performing operation on the tension deviation by using the target proportional coefficient, the target integral coefficient and the target differential coefficient to determine a PID speed compensation amount; determining a PID target parameter of a unwinding motor of the first material based on the PID speed compensation amount and the set reference speed; and performing PID control on a rotating speed of the unwinding motor of the first material according to the PID target parameter. The application can improve the accuracy of material tension control, and further improve the consistency of product quality.

Description

Technical Field

[0001] This application relates to the field of roller welding machine technology, specifically to a control method, system, equipment, and medium for a roller welding machine. Background Technology

[0002] Roll welding machines are key equipment in composite material processing, especially in fields such as new energy batteries and new materials, for achieving interlayer bonding of materials. During the roll welding process, precise and stable control of material tension is crucial to ensure welding quality and yield.

[0003] However, in actual production, the tension control of materials is often not precise enough, causing the materials to stretch and deform or wrinkle, affecting the consistency of product quality. Summary of the Invention

[0004] The embodiments of this application provide a control method, system, equipment, and medium for a roll welding machine, aiming to achieve more precise material tension control and thereby improve the consistency of product quality.

[0005] In a first aspect, embodiments of this application provide a control method for a roller welding machine, the control method comprising:

[0006] The material type and thickness of the first material to be welded by the roller welding machine are obtained, as well as the set reference speed of the welding roller group motor in the roller welding machine.

[0007] Based on the material type and material thickness, determine the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition;

[0008] Determine the tension deviation between the current actual tension value and the set tension value of the first material;

[0009] The tension deviation is calculated using the target proportional coefficient, the target integral coefficient, and the target derivative coefficient to determine the PID speed compensation amount;

[0010] Based on the PID speed compensation amount and the set reference speed, the PID target parameters of the unwinding motor of the first material are determined;

[0011] The rotational speed of the unwinding motor for the first material is controlled by PID according to the PID target parameters.

[0012] In the above embodiments, by pre-determining PID control parameters based on material type and thickness, adaptive tension control under different working conditions can be achieved. Without the need for tedious parameter adjustments after material replacement, the material tension can be quickly and stably controlled near the set value, effectively avoiding tensile deformation or wrinkling of composite materials caused by tension fluctuations, and improving the automation level and product yield of roll welding production.

[0013] In one embodiment, determining the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition based on the material type and material thickness includes:

[0014] Determine the basic proportional coefficient, basic integral coefficient, and basic differential coefficient corresponding to the material type;

[0015] Based on the material thickness, determine the thickness gain value;

[0016] The target proportional coefficient, the target integral coefficient, and the target differential coefficient are determined based on the thickness gain value, the basic proportional coefficient, the basic integral coefficient, and the basic differential coefficient.

[0017] In the above embodiments, by decoupling the determination of PID parameters into two steps, namely "determination of basic parameters" and "thickness gain adjustment", the adaptability and control accuracy of the control system to changes in material specifications can be improved, ensuring high stability and high quality of the roll welding process under the multi-variety, small-batch production mode.

[0018] In one embodiment, determining the thickness gain value based on the material thickness includes:

[0019] Obtain the preset material standard reference thickness;

[0020] Calculate the thickness ratio between the material thickness and the material standard reference thickness;

[0021] The thickness ratio is input into a preset nonlinear gain curve model, and the thickness gain value corresponding to the thickness ratio is output. The nonlinear gain curve model defines the gain gradient corresponding to different thickness ratio ranges.

[0022] In the above embodiments, by introducing a nonlinear gain curve model based on thickness ratio, the adjustment of PID parameters is deeply integrated with the physical laws of material thickness variation, thereby realizing the accurate calculation of thickness gain value and making the target PID parameters more accurately match the dynamic characteristics of materials of arbitrary thickness.

[0023] In one embodiment, after performing PID control on the speed of the unwinding motor of the first material according to the PID target parameters, the method further includes:

[0024] The tension deviations within multiple consecutive control cycles are determined to generate a tension deviation sequence;

[0025] Based on the tension deviation sequence, the current control performance index is determined, which includes tension overshoot, oscillation period, or integral value of steady-state error.

[0026] If the control performance index is greater than the preset index threshold, then with the goal of minimizing the control performance index, the correction amount of the basic proportional coefficient, the basic integral coefficient, and the basic derivative coefficient is determined using a preset parameter optimization model.

[0027] Using the correction amount, adjust the values ​​of the current basic proportional coefficient, basic integral coefficient, and basic differential coefficient;

[0028] Return to the step of determining the target proportional coefficient, the target integral coefficient, and the target differential coefficient based on the thickness gain value, the basic proportional coefficient, the basic integral coefficient, and the basic differential coefficient.

[0029] In the above embodiments, by adding online performance evaluation and parameter self-tuning closed loop, the optimal basic PID parameters can be found, which can adapt to different material specifications and improve the long-term operation of the roller welding machine.

[0030] In one embodiment, the step of calculating the tension deviation using the target proportional coefficient, the target integral coefficient, and the target derivative coefficient to determine the PID speed compensation amount includes:

[0031] The product of the target proportionality coefficient and the tension deviation is determined to obtain the proportional term component;

[0032] Obtain the cumulative value of tension deviation within the historical control cycle, and determine the product of the target integral coefficient and the cumulative value of tension deviation to obtain the integral term component;

[0033] Obtain the historical tension deviation from the previous control cycle, determine the difference between the tension deviation and the historical tension deviation, and determine the product of the target differential coefficient and the difference to obtain the differential term component;

[0034] The proportional term component, the integral term component, and the derivative term component are summed to obtain the PID speed compensation amount.

[0035] In the above embodiments, by determining the proportional term component, integral term component, and derivative term component, and summing them, the PID speed compensation amount is obtained, so as to realize PID control of the unwinding motor speed.

[0036] In one embodiment, after summing the proportional term component, the integral term component, and the derivative term component to obtain the PID speed compensation amount, the method further includes:

[0037] Obtain the real-time acceleration of the motor of the welding roller group;

[0038] Based on the real-time acceleration, determine the corresponding compensation saturation threshold;

[0039] If the PID speed compensation amount is greater than the compensation amount saturation threshold, the tension deviation cumulative value is corrected based on the difference between the PID speed compensation amount and the compensation amount saturation threshold.

[0040] Return to the step of determining the product of the target integral coefficient and the cumulative value of the tension deviation to obtain the integral term component.

[0041] In the above embodiments, by dynamically linking the PID output saturation threshold with the real-time acceleration of the welding roller motor, the control output is preemptively limited to ensure that it is always within the physical tolerance range of the system. This can improve the stability and dynamic response quality of the system under severe operating conditions such as start-up, stop, acceleration and deceleration, and effectively prevent serious overshoot and long-term oscillation caused by integral saturation.

[0042] In one embodiment, determining the PID target parameters of the unwinding motor for the first material based on the PID speed compensation amount and the set reference speed includes:

[0043] Obtain the preset tensile strength of the first material;

[0044] Based on the set reference speed and the preset stretching rate, calculate the feedforward synchronous linear velocity of the first material under the current working conditions;

[0045] The PID speed compensation is superimposed on the feedforward synchronous linear speed to obtain the total target unwinding linear speed.

[0046] Based on the total unwinding target linear velocity, the PID target parameters of the unwinding motor for the first material are generated.

[0047] In the above embodiments, the known speed difference is actively compensated by the feedforward control of the stretching ratio to provide a fast reference response, and the PID feedback control eliminates residual errors and unknown disturbances to ensure the final accuracy. Thus, it can predictably adapt to process requirements, correct operating deviations in real time, and achieve high-precision control of the first material tension.

[0048] Secondly, embodiments of this application provide a control system for a roller welding machine, the control system being used to execute the control method for the roller welding machine as described in any of the preceding claims.

[0049] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the control method of the roll welding machine as described in any of the preceding claims.

[0050] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program configured to be executed by a processor to implement the control method for a roll welding machine as described in any of the preceding claims.

[0051] The beneficial effects of the embodiments of this application are as follows:

[0052] In the embodiments of this application, based on the material type and thickness of the first material to be welded, the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition are determined. Then, combined with the tension deviation between the current actual tension value and the set tension value of the first material, the PID speed compensation amount is determined. Based on the PID speed compensation amount and the set reference speed, the PID target parameters of the unwinding motor of the first material are determined, so that the rotational speed of the unwinding motor of the first material can take into account the material differences of the first material, thereby improving the accuracy of material tension control and the consistency of product quality. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0054] Figure 1 This is a schematic flowchart of an embodiment of the control method for a roller welding machine provided in this application. Detailed Implementation

[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. In addition, in the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0056] Firstly, embodiments of this application provide a control method for a roll welding machine, wherein the executing entity is the control system of the roll welding machine (hereinafter referred to as the "system"). Specifically, refer to... Figure 1 The control methods for the roll welding machine may include:

[0057] S101. Obtain the material type and thickness of the first material to be welded in the roller welding machine, as well as the set reference speed of the welding roller group motor in the roller welding machine;

[0058] In the embodiments of this application, the first material refers to a strip or roll of material that is unwound and fed into a welding roller assembly for welding. In some embodiments of this application, the first material may be a metal foil (such as copper foil or aluminum foil, commonly used in the manufacture of new energy battery electrodes), or a non-metallic material such as a polymer composite film or non-woven fabric.

[0059] Material type refers to the classification of the physicochemical properties of the primary material (such as main chemical components: copper, aluminum, polypropylene, etc., or composite structure). Different material types have different elastic moduli, yield strengths, and surface friction coefficients, which are key physical parameters affecting the dynamic response of tension control.

[0060] Material thickness refers to the dimension of the first material perpendicular to its length and width. Variations in material thickness directly affect the total inertia and stiffness of the roll material, thereby influencing the system's response characteristics.

[0061] The welding roller motor is the power source that drives the rotation of the core pair of rollers (two or more) at the welding station. Its rotation speed determines the core processing speed of the material on the production line.

[0062] The baseline speed is the baseline linear speed (usually in meters per minute, m / min) set by the operator or the upper-level manufacturing execution system (MES) for the entire welding process. It serves as the reference for all subsequent speed synchronization and adjustment calculations.

[0063] In some embodiments of this application, the above parameters are obtained in the following ways: first, through a human-machine interface (HMI) for manual input by the operator; second, through sensors (such as barcode scanners or radio frequency identification (RFID) readers) configured at the unwinding station, information tags on the material core or packaging are automatically scanned, and information such as material type and material thickness is parsed and transmitted to the system's programmable logic controller (PLC) to realize automatic loading of production formula, reduce manual intervention, and improve production efficiency and accuracy.

[0064] S102. Based on the material type and material thickness, determine the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition;

[0065] In the embodiments of this application, the current working condition refers to a specific production scenario defined by the material type and thickness of the first material. The target proportional coefficient (Kp), target integral coefficient (Ki), and target derivative coefficient (Kd) are three core tuning parameters of the PID (Proportional Integral Derivative) control algorithm, which together determine the controller's response speed, stability, and ability to eliminate steady-state errors in response to tension deviations.

[0066] In some embodiments of this application, the target proportional coefficient, target integral coefficient, and target differential coefficient can be determined based on a preset parameter database. Specifically, the system internally stores a multidimensional lookup table, indexed by material type and material thickness, which directly maps to a set of Kp, Ki, and Kd values ​​pre-optimized through experiments or simulations (e.g., "0.05mm thick copper foil" corresponds to (Kp1, Ki1, Kd1), and "0.1mm thick aluminum foil" corresponds to (Kp2, Ki2, Kd2)). This scheme is simple to implement and has a fast response.

[0067] S103. Determine the tension deviation between the current actual tension value and the set tension value of the first material;

[0068] In the embodiments of this application, the current actual tension value is a physical quantity detected in real time by a tension sensor on the material conveyor path (the sensor can be a potentiometer / angle sensor on the floating roller mechanism, or a piezoelectric / strain gauge force sensor under the fixed support roller bearing seat). The set tension value is the ideal tension required by the process (set by the operator on the human-machine interface, usually in Newtons, N). The tension deviation is the algebraic difference between the current actual tension value and the set tension value (E(t) = actual tension value - set tension value), which is the error signal input to the PID calculation stage, driving the controller to adjust.

[0069] S104. Calculate the tension deviation using the target proportional coefficient, target integral coefficient, and target derivative coefficient to determine the PID speed compensation amount.

[0070] In the embodiments of this application, the PID speed compensation amount is an increment or decrement of the unwinding motor speed calculated by the controller based on the current tension deviation.

[0071] The operation follows the discretized PID control equations:

[0072] ΔV(t)=Kp×E(t)+Ki×ΣE(t)+Kd×[E(t)-E(t-1)]

[0073] Where ΔV(t) is the PID speed compensation amount at the current moment, E(t) is the tension deviation at the current moment, ΣE(t) is the sum of historical deviations (integral term), and [E(t)-E(t-1)] is the difference between the current deviation and the deviation at the previous moment (differential term).

[0074] S105. Based on the PID speed compensation amount and the set reference speed, determine the PID target parameters of the unwinding motor of the first material;

[0075] In the embodiments of this application, the PID target parameter refers to the "target speed command" provided to the unwinding motor driver.

[0076] In some embodiments of this application, the target speed command consists of two parts: one is the set reference speed as a feedforward quantity (to ensure that the unwinding speed and welding speed are roughly synchronized); the other is the PID speed compensation quantity as a feedback correction quantity (to accurately compensate for tension fluctuations caused by changes in roll diameter, material disturbances, etc.), and the calculation formula is: target speed = set reference speed + PID speed compensation quantity.

[0077] In some embodiments of this application, a winding diameter compensation feedforward is also introduced: the unwinding winding diameter is calculated in real time using the encoder pulse count. Based on the principle of "linear velocity = angular velocity × radius", a feedforward velocity component calculated from the winding diameter change is superimposed on the set reference speed. The optimized calculation formula is: Target speed = Set reference speed (linear velocity) / Current winding diameter (angular velocity) + Winding diameter change feedforward compensation + PID speed compensation. This "feedforward + feedback" composite control strategy can eliminate predictable disturbances such as winding diameter changes in advance through the feedforward stage, leaving only random and unpredictable disturbances for the PID feedback stage to handle, significantly reducing the burden on the PID controller and making tension control faster and more stable.

[0078] S106. According to the PID target parameters, perform PID control on the speed of the unwinding motor of the first material.

[0079] In the embodiments of this application, the "target speed command" calculated in the previous step is sent as a command to the unwinding servo motor driver through a high-speed communication bus. The servo driver contains a high-response frequency speed loop and current loop proportional-integral-derivative controller, which compares the target speed with the actual rotational speed fed back by the motor encoder at high frequency, adjusts the current output to the motor in real time, and precisely drives the unwinding motor to rotate at the target speed, thus completing the entire tension closed-loop control.

[0080] As can be seen, the embodiments of this application achieve adaptive tension control under different working conditions by pre-determining PID control parameters based on material type and material thickness. Without the need for tedious parameter adjustments after material replacement, the material tension can be quickly and stably controlled near the set value, effectively avoiding the problem of tensile deformation or wrinkling of composite materials caused by tension fluctuations, and improving the automation level and product yield of roll welding production.

[0081] In some embodiments of this application, the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition are determined based on the material type and material thickness, including:

[0082] S201. Determine the basic proportional coefficient, basic integral coefficient, and basic differential coefficient corresponding to the material type;

[0083] In the embodiments of this application, this step decomposes the determination process of proportional-integral-derivative parameters. First, a set of benchmark parameters is set based on the inherent physical properties of the material. The basic proportional coefficient, basic integral coefficient, and basic derivative coefficient are a set of nominal PID tuning parameters for a specific material type (without considering the effect of thickness). They reflect the basic dynamic response characteristics of this type of material (such as copper and aluminum) at standard thickness. For example, copper and aluminum have different elastic moduli and densities, and their response behavior differs when subjected to the same tensile disturbance, requiring different basic PID parameters to be configured.

[0084] In some embodiments of this application, the basic coefficients are implemented through a "material-basic PID parameter" mapping table: the material type is used as the index key, and (basic Kp, basic Ki, basic Kd) is used as the value. When the system obtains that the material type is "copper foil", it directly retrieves the corresponding basic parameter group from the table.

[0085] S202. Determine the thickness gain value based on the material thickness;

[0086] In the embodiments of this application, the thickness gain value is an adjustment factor used to correct the basic PID parameters, representing the degree of influence on the dynamic characteristics of the control system when the actual material thickness deviates from the standard thickness. The thicker the material, the greater the inertia and rigidity, and the PID parameters need to be adjusted through the thickness gain value to maintain optimal control performance.

[0087] S203. Determine the target proportional coefficient, target integral coefficient, and target differential coefficient based on the thickness gain value, the basic proportional coefficient, the basic integral coefficient, and the basic differential coefficient.

[0088] In the embodiments of this application, the basic parameters are combined with the influence of thickness to generate the controller's operating parameters. For example, the target coefficients can be synthesized through linear weighting: the thickness gain value is used as a multiplication factor and applied to the three basic coefficients respectively, as shown in the following formula:

[0089] Target scaling factor = Base scaling factor × Thickness gain value

[0090] Target integral coefficient = base integral coefficient × thickness gain value

[0091] Target differential coefficient = basic differential coefficient × thickness gain value

[0092] As can be seen, by decoupling the determination of PID parameters into two steps, namely "determination of basic parameters" and "thickness gain adjustment", the embodiments of this application can improve the adaptability and control accuracy of the control system to changes in material specifications, and ensure the high stability and high quality of the roll welding process under the multi-variety, small-batch production mode.

[0093] In some embodiments of this application, the thickness gain value is determined based on the material thickness, including:

[0094] S301. Obtain the preset material standard reference thickness;

[0095] In the embodiments of this application, the material standard reference thickness is a reference thickness value used when defining the basic PID parameters for a specific material type, and is associated with the material type (different materials have different commonly used / representative thicknesses). For example, the material standard reference thickness for copper foil can be preset to 0.08 mm, and for aluminum foil it can be preset to 0.1 mm. This value is stored in the system, and when the system retrieves the basic PID parameters corresponding to the material type, it will simultaneously obtain the material standard reference thickness for that material.

[0096] S302. Calculate the thickness ratio between the material thickness and the material standard reference thickness;

[0097] In the embodiments of this application, the thickness ratio is obtained by dividing the actual material thickness of the first material to be welded by its corresponding material standard reference thickness. The calculation formula is: Thickness ratio = Material thickness / Material standard reference thickness. For example, if the current copper foil thickness is 0.1 mm and the copper foil material standard reference thickness is 0.08 mm, then the thickness ratio is 1.25.

[0098] S303. Input the thickness ratio into the preset nonlinear gain curve model and output the thickness gain value corresponding to the thickness ratio. The nonlinear gain curve model defines the gain gradient corresponding to different thickness ratio ranges.

[0099] In the embodiments of this application, the nonlinear gain curve model is a mathematical model preset in the controller, which describes the nonlinear relationship between the thickness gain value and the thickness ratio. Since the influence of material thickness on the system's inertia and stiffness is not nonlinear, this model can more accurately match the actual dynamic characteristics; the gain gradient refers to the slope of a point on the gain curve (the rate at which the thickness gain value changes with the thickness ratio), and the model embodies "nonlinearity" by defining the gain gradient in different thickness ratio ranges.

[0100] In some embodiments of this application, the nonlinear gain curve model is a piecewise linear function model: the controller presets multiple thickness ratio inflection points and gain gradients for each interval, for example:

[0101] Thickness ratio ∈ [0.5, 0.9]: Gain gradient = 0.3 (gain adjustment is moderate when the material is thinner than the standard);

[0102] Thickness ratio ∈ (0.9, 1.1]: Gain gradient = 1.0 (near standard thickness, gain and ratio are approximately linearly related).

[0103] Thickness ratio ∈ (1.1, 1.5]: Gain gradient = 1.8 (When the material is thicker than the standard, the influence of system inertia increases, requiring a larger gain adjustment).

[0104] Thickness ratio > 1.5: Gain gradient = 2.5 (to cope with significant dynamic property changes in extremely thick materials).

[0105] After determining the range to which the thickness ratio belongs, the final thickness gain value is obtained by interpolation based on the range reference point and gain gradient.

[0106] As can be seen, the embodiments of this application introduce a nonlinear gain curve model based on thickness ratio, which deeply integrates the adjustment of PID parameters with the physical laws of material thickness variation, and realizes the accurate calculation of thickness gain value, so that the target PID parameters can more accurately match the dynamic characteristics of materials of arbitrary thickness.

[0107] In some embodiments of this application, after performing PID control on the rotational speed of the unwinding motor of the first material according to the PID target parameters, the method further includes:

[0108] S401. Determine the tension deviation within multiple consecutive control cycles to generate a tension deviation sequence;

[0109] In the embodiments of this application, the control cycle refers to the time (usually milliseconds, on the order of ms) for the system to execute one complete cycle of "reading sensor - calculating - outputting control quantity"; the tension deviation sequence is a time series that records the tension deviation values ​​of each cycle within multiple consecutive control cycles. For example, when the control cycle is 10ms, a sequence E(t1), E(t2), ..., E(t100) containing 100 tension deviation values ​​can be generated within 1 second.

[0110] S402. Based on the tension deviation sequence, determine the current control performance indicators, including tension overshoot, oscillation period, or integral value of steady-state error.

[0111] In the embodiments of this application, the control performance index is a quantitative parameter describing the dynamic response and steady-state characteristics of the control system. Among them, tension overshoot refers to the maximum percentage by which the peak value exceeds the set value when the tension response changes abruptly (reflecting system stability); oscillation period refers to the duration of the period during which the tension fluctuates around the set value before reaching stability (reflecting system response speed and damping characteristics); the integral value of steady-state error usually refers to the integral of time-weighted absolute error (ITAE), calculated by the formula ∫t|E(t)|dt (comprehensively considering the magnitude and duration of the error to fully evaluate dynamic and steady-state performance).

[0112] S403. If the control performance index is greater than the preset index threshold, then with the goal of minimizing the control performance index, the correction amount of the basic proportional coefficient, basic integral coefficient and basic derivative coefficient is determined using the preset parameter optimization model.

[0113] In the embodiments of this application, the index threshold refers to the maximum value of the pre-set acceptable control performance index. If it exceeds the threshold, it indicates that the current control effect is not good and parameter optimization needs to be initiated. The parameter optimization model is an intelligent algorithm model that calculates the PID parameter adjustment amount in reverse based on the control performance index. The correction amount is the increment / decrement of the basic PID parameters (i.e., ΔKp, ΔKi, ΔKd) required to make the control performance optimal.

[0114] In some embodiments of this application, to improve the accuracy and efficiency of self-tuning, the parameter optimization model employs an iterative optimization algorithm based on gradient descent: the control performance index (such as ITAE) is regarded as the objective function J(Kp, Ki, Kd) of the basic PID parameters (Kp, Ki, Kd). By calculating the gradient (partial derivative) of the objective function with respect to each parameter, the parameters are iteratively adjusted in small steps in the opposite direction of the gradient, gradually finding the optimal parameter combination that minimizes J (the gradient can be approximated by observing the changes in the performance index after small perturbations of the parameters). This method is rigorous and can automatically converge to the optimal parameters, improving the intelligence level of self-tuning.

[0115] S404. Use the correction amount to adjust the values ​​of the current basic proportional coefficient, basic integral coefficient, and basic differential coefficient.

[0116] In the embodiments of this application, the basic PID parameters are updated using the following adjustment formula:

[0117] New base ratio coefficient = Current base ratio coefficient + Kp correction amount;

[0118] New basic integral coefficient = Current basic integral coefficient + Ki correction amount;

[0119] New basic differential coefficients = current basic differential coefficients + Kd correction amount.

[0120] S405. Return to the execution of the steps to determine the target proportional coefficient, target integral coefficient, and target differential coefficient based on the thickness gain value, the basic proportional coefficient, the basic integral coefficient, and the basic differential coefficient.

[0121] In the embodiments of this application, after the basic PID parameters are optimized, the system does not directly use the new parameters, but instead returns to the step of "determining the target PID parameters based on the thickness gain value and the basic parameters" (i.e., S203) to recalculate the target parameters adapted to the current operating conditions. This structure achieves dual closed-loop coordination of "outer loop self-tuning (optimizing basic parameters to adapt to slow time-varying characteristics such as equipment aging and environmental changes) + inner loop operating condition self-adaptation (rapidly adjusting the target parameters based on the thickness)" to ensure control accuracy and stability.

[0122] As can be seen, the embodiments of this application, by adding online performance evaluation and parameter self-tuning closed loop, find the optimal basic PID parameters, which can be adapted to different material specifications and improve the long-term operation of the roll welding machine.

[0123] In some embodiments of this application, the tension deviation is calculated using a target proportional coefficient, a target integral coefficient, and a target derivative coefficient to determine the PID speed compensation amount, including:

[0124] S501. Determine the product of the target proportionality coefficient and the tension deviation to obtain the proportional term component;

[0125] In the embodiments of this application, the proportional component is the part of the PID speed compensation that is proportional to the current tension deviation. Its core function is to provide the main control force to pull the tension back to the set value.

[0126] S502. Obtain the cumulative value of tension deviation within the historical control cycle, and determine the product of the target integral coefficient and the cumulative value of tension deviation to obtain the integral term component;

[0127] In the embodiments of this application, the cumulative tension deviation value within the historical control cycle is the sum of the tension deviations of each historical control cycle continuously accumulated in a certain register of the system; the integral term component is the part of the PID speed compensation quantity that is proportional to the cumulative deviation value. As long as an error exists, the integral term will continue to increase, generating a stronger control effect until the error is eliminated.

[0128] S503. Obtain the historical tension deviation of the previous control cycle, determine the difference between the tension deviation and the historical tension deviation, and determine the product of the target differential coefficient and the difference to obtain the differential term component.

[0129] In the embodiments of this application, historical tension deviation specifically refers to the tension deviation value of the previous control cycle; the derivative component is the part of the PID speed compensation quantity that is proportional to the rate of change of tension deviation. When the deviation increases rapidly, the derivative component generates a reverse force to suppress further expansion of the deviation.

[0130] S504. Summing the proportional, integral, and derivative components yields the PID speed compensation.

[0131] In the embodiments of this application, the three independent action components of the PID controller are combined into a unified control output to obtain the PID speed compensation amount.

[0132] In some embodiments of this application, an improved PID controller structure is used instead of simple summation. In this structure, the inputs to the proportional and derivative terms are the changes in the current actual tension value, rather than the tension deviation. The PID speed compensation calculation formula is optimized as follows:

[0133] PID speed compensation = Integral term (based on tension deviation) - [Proportional term (based on actual tension value) + Derivative term (based on actual tension value)]

[0134] in:

[0135] Proportional component (based on actual tension value) = Target proportional coefficient × (Current actual tension value - Previous cycle actual tension value)

[0136] Differential component (based on actual tension value) = Target differential coefficient × [(Current actual tension value - Previous cycle actual tension value) - (Previous cycle actual tension value - Previous cycle actual tension value)]

[0137] The improved PID controller structure decouples the "setpoint response (handled by the integral term)" from the "disturbance response (handled by the proportional / derivative term)". In tension control scenarios (mainly for disturbance suppression), it can quickly and effectively suppress tension fluctuations, and there is no proportional / derivative "overshoot" when adjusting the setpoint, resulting in a smoother control process.

[0138] As can be seen, the embodiments of this application determine the proportional term component, integral term component, and differential term component, and sum them to obtain the PID speed compensation amount, so as to realize PID control of the unwinding motor speed.

[0139] In some embodiments of this application, after summing the proportional, integral, and derivative components to obtain the PID speed compensation amount, the method further includes:

[0140] S601. Obtain the real-time acceleration of the welding roller assembly motor;

[0141] In the embodiments of this application, the real-time acceleration of the welding roller motor refers to the rate of change of angular velocity of the welding roller motor in the current control cycle (usually calculated from the speed signal fed back by the motor encoder, rather than being directly measured by an independent sensor).

[0142] S602. Based on real-time acceleration, determine the corresponding compensation saturation threshold;

[0143] In the embodiments of this application, the compensation saturation threshold is a dynamic upper limit that limits the maximum instantaneous output of the PID speed compensation. Unlike the fixed threshold, it is adaptively adjusted with the real-time acceleration of the welding roller motor. The significance is that when the system accelerates or decelerates at high speed, its ability to withstand additional speed compensation is limited. Excessive compensation may cause material slippage, severe tension fluctuations, or equipment damage.

[0144] In some embodiments of this application, a saturation threshold for the compensation amount is determined by a preset nonlinear mapping function: real-time acceleration is taken as input, and the corresponding threshold is output. For example, when the real-time acceleration is zero / close to zero (the system is moving at a constant speed), the threshold takes a larger default value, allowing the PID controller a larger adjustment range; when the absolute value of the real-time acceleration increases, the threshold decreases nonlinearly.

[0145] Furthermore, the preset nonlinear mapping function can be designed to be asymmetric: the threshold decrease curve is gentle during positive acceleration (acceleration state) and steeper during negative acceleration (deceleration state). This is because the system inertia during deceleration easily leads to material relaxation, requiring stricter limits on the PID speed compensation. This asymmetric dynamic threshold based on physical characteristics can accurately match the system's tolerance under different dynamic operating conditions, achieving precise and safe protection.

[0146] S603. If the PID speed compensation amount is greater than the compensation amount saturation threshold, the cumulative value of tension deviation shall be corrected according to the difference between the PID speed compensation amount and the compensation amount saturation threshold.

[0147] In the embodiments of this application, when the PID speed compensation amount is detected to exceed the dynamic saturation threshold determined by the current acceleration, it is determined that the integral term has entered a saturation / quasi-saturation state, and the integral term needs to be "rolled back" to prevent unlimited accumulation. Correcting the accumulated tension deviation value means subtracting the difference from the current accumulated value to suppress integral accumulation.

[0148] S604. Return to the step of determining the product of the target integral coefficient and the cumulative value of the tension deviation to obtain the integral term component.

[0149] In the embodiments of this application, after correcting the accumulated value of tension deviation, the system immediately returns to the step of "determining the product of the target integral coefficient and the accumulated value of tension deviation to obtain the integral term component" (i.e., S502). This means that in the next control cycle, the system will use the smaller accumulated value after "back-off" to calculate the new integral term component, ensuring that the anti-saturation measures take effect without delay, keeping the accumulated value of integral within a reasonable range allowed by the system in real time, and avoiding the deep development of integral saturation.

[0150] As can be seen, the embodiments of this application dynamically correlate the PID output saturation threshold with the real-time acceleration of the welding roller motor, predictively limiting the control output to ensure that it is always within the physical tolerance range of the system. This can improve the stability and dynamic response quality of the system under severe operating conditions such as start-up, stop, acceleration and deceleration, and effectively prevent serious overshoot and long-term oscillation caused by integral saturation.

[0151] In some embodiments of this application, determining the PID target parameters of the unwinding motor for the first material based on the PID speed compensation amount and a set reference speed may include:

[0152] S701, Obtain the preset tensile strength of the first material;

[0153] In some embodiments of this application, the preset elongation rate is a percentage value preset and stored in the system based on the physical properties of the first material (such as elastic modulus) and process requirements (such as target tension), which characterizes the elongation ratio of the material length relative to its natural length under the action of target tension (for example, the preset elongation rate of a copper foil under a tension of 20N is 0.05%).

[0154] In some embodiments of this application, the calculation of the preset tensile rate is not only based on the elastic mechanical tensile rate, but may also incorporate the thermal expansion compensation rate determined based on welding process parameters. The preset tensile rate is defined herein as the comprehensive deformation rate, the value of which is equal to the algebraic sum of the elastic mechanical tensile rate and the thermal expansion compensation rate.

[0155] The elastic mechanical tensile ratio is a deformation component calculated based on the material's mechanical properties. Specifically, the current set tension value is read, and this value is calculated according to the stored material properties: Elastic mechanical tensile ratio = Set tension / (Elastic modulus × Cross-sectional area). This component reflects the elastic elongation of the material under tensile force at room temperature.

[0156] The thermal expansion compensation rate is the deformation component calculated based on the welding heat input. Since Joule heating during roll welding causes a rapid increase in local material temperature and thermal expansion, the welding current and voltage values ​​of the welding power source can be collected in real time and combined with the current set reference speed to estimate the heat energy received per unit length of material. Subsequently, using a pre-stored temperature rise model, such as temperature rise = (welding current × welding voltage × thermal efficiency coefficient) / (set reference speed × material heat capacity × linear density), the average temperature rise of the first material in the welding area is calculated. Finally, the thermal expansion compensation rate is calculated: Thermal expansion compensation rate = linear thermal expansion coefficient × average temperature rise.

[0157] In some embodiments of this application, the calculation of the preset tensile rate may also incorporate a thermal accumulation correction factor. The thermal accumulation correction factor is used to compensate for the phenomenon that the temperature of the welding wheel and surrounding mechanical structure gradually increases with increasing continuous welding time, causing a drift in the baseline of the preheating temperature of the first material. The thermal accumulation correction factor is a variable that increases slowly over time. Specifically, the background temperature rise of the system is estimated using the total welding time and cumulative welding energy of the first material as inputs. Thermal accumulation correction factor = background temperature rise × system comprehensive thermal expansion coefficient, where the system comprehensive thermal expansion coefficient is an empirical value reflecting the rate of change of the effective path length due to the overall temperature rise of the equipment and the additional thermal expansion caused by the preheating effect on the first material.

[0158] It can be seen that in scenarios of long-term continuous production (e.g., more than 30 minutes), the thermal accumulation correction factor can effectively compensate for the chronic tension drift caused by the overall temperature rise of the equipment. By superimposing the elastic mechanical tensile rate, thermal expansion compensation rate, and thermal accumulation correction factor, the preset tensile rate value can be dynamically refreshed within each control cycle (e.g., 1ms), ensuring that it always accurately reflects the material's true deformation tendency under the current complex physical field.

[0159] S702. Based on the set reference speed and preset tensile rate, calculate the feedforward synchronous linear velocity of the first material under the current working conditions.

[0160] In the embodiments of this application, the feedforward synchronous linear speed is the preset baseline linear speed (feedforward control quantity, intended to actively compensate for deviations before they occur) of the unwinding motor in order to maintain synchronization with the main drive (welding roller group) and actively establish the target tension. The calculation formula is: feedforward synchronous linear speed = set reference speed × (1 - preset stretching ratio). Its control logic is: in order to stretch the material to the preset stretching ratio when it reaches the welding roller group, the unwinding side feed speed needs to be slightly slower than the welding roller group linear speed. This speed difference is just used to generate elastic deformation of the material.

[0161] In the scheme incorporating thermal expansion compensation, the thermal expansion compensation rate, as a negative compensation term, has significant physical implications: Metal materials elongate when heated. If the original unwinding speed is maintained, this additional thermal elongation will cause the actual tension to be less than the target value (i.e., tension relaxation). By subtracting the thermal expansion compensation rate when calculating the feedforward synchronous linear speed, the unwinding motor is effectively commanded to further reduce its feed speed. This additional reduction in speed precisely offsets the increased length of the material due to thermal expansion, thus ensuring that the material can still be "tightened" to the expected tension level in the high-temperature welding zone.

[0162] S703. The PID speed compensation is superimposed on the feedforward synchronous linear speed to obtain the total target linear speed of unwinding.

[0163] In the embodiments of this application, the total unwinding target linear velocity is the final speed command combining active compensation (feedforward) and passive correction (feedback). The calculation formula is: Total unwinding target linear velocity = Feedforward synchronous linear velocity + PID speed compensation. The feedforward part handles known control requirements (synchronization, stretching), while the feedback part (PID) only needs to handle residual disturbances and model uncertainties, greatly reducing the PID burden and enabling fine adjustment.

[0164] S704. Based on the total unwinding target linear speed, generate the PID target parameters for the unwinding motor of the first material.

[0165] In the embodiments of this application, the conversion from linear velocity to rotational speed needs to take into account the real-time radius of the unwinding drum. This can be achieved by continuously tracking the real-time radius R of the unwinding drum using a drum diameter calculation module (e.g., via the linear velocity / angular velocity method or the material thickness accumulation method). The target rotational speed is calculated using the following formula:

[0166] Target rotational speed = (total target linear velocity of unwinding / (2 × π × real-time radius)) × reduction ratio

[0167] The reduction ratio is the mechanical transmission ratio between the motor and the drum. The calculated target speed will be sent to the unwinding motor servo driver as the set value for the next control cycle.

[0168] As can be seen, the embodiments of this application actively compensate for the known speed difference through feedforward control of the stretching ratio, providing a fast reference response. PID feedback control eliminates residual errors and unknown disturbances, ensuring final accuracy. Thus, it can predictably adapt to process requirements, correct operating deviations in real time, and achieve high-precision control of the first material tension.

[0169] In some embodiments of this application, a method for calculating the thermal accumulation correction factor in the above embodiments is provided, specifically including the following steps:

[0170] S801, Calculate the dynamic heat dissipation coefficient for the current cycle;

[0171] In embodiments of this application, this step aims to quantify the differences in the ability of the cooling medium to remove heat at different rotational speeds. The dynamic heat dissipation coefficient characterizes the intensity of convective heat transfer between the internal cooling water and the inner wall of the welding wheel during its rotation.

[0172] The rotational angular velocity of the welding wheel is collected in real time and denoted as ω(k). The turbulence intensity h of the cooling water flowing in the internal channel of the welding wheel is calculated based on a preset fluid dynamics model. dyn (k). The calculation formula is:

[0173] h dyn (k)=h static +β×(ω(k)) γ

[0174] Among them, h static β is the natural convection heat transfer coefficient under static conditions, which refers to the basic cooling capacity of the cooling water when the welding wheel is not rotating; β is the flow channel structure gain factor, which is determined by the spiral structure, cross-sectional area and surface roughness of the cooling water tank inside the welding wheel, and is used to calibrate the flow velocity gain sensitivity under a specific mechanical design; γ is the flow velocity correlation index (ranging from 0.8 to 0.9), which reflects the nonlinear power law relationship between the cooling water flow velocity and the heat transfer efficiency.

[0175] The physical significance of this step lies in establishing a dynamic relationship between rotational speed and heat dissipation: the faster the welding wheel rotates, the higher the relative speed of the cooling water with respect to the flow channel, the greater the fluid shear force, which leads to intensified turbulence and thus improves the efficiency of heat removal.

[0176] S802, Iteratively update the equivalent heat accumulation temperature using the energy residual equation;

[0177] In the embodiments of this application, this step is based on the law of conservation of energy, and the temperature change of the welding wheel body is deduced by calculating the difference between heat input and heat output.

[0178] The equivalent heat accumulation temperature does not refer to the extremely high temperature at the instantaneous contact point on the surface of the welding wheel, but rather to the average background temperature of the entire metal substrate of the welding wheel and the connecting shaft system under thermal equilibrium.

[0179] Update the equivalent heat accumulation temperature T using the discretized energy residual equation eq (k). The calculation formula is:

[0180] T eq (k)=T eq (k-1)+(Δt / (M×Cp))×[η×I(k) 2 ×R(k)-h dyn (k)×A×(T eq (k-1)-T water )]

[0181] Among them, T eq (k) represents the equivalent heat accumulation temperature of the welding wheel at the current moment; T eq (k-1) is the estimated temperature value of the previous control cycle; Δt is the control cycle duration; M×Cp is the total heat capacity of the welding wheel, reflecting the inertia of system temperature changes; η is the heat split ratio, representing the proportion of heat absorbed by the welding wheel and causing a temperature rise in the total Joule heat generated during welding (the remaining heat is carried away or dissipated by the first material); I(k) and R(k) are the welding current collected in real time and the calculated contact resistance, respectively; A is the effective heat dissipation area; T water This refers to the inlet temperature of the cooling water.

[0182] This equation accurately simulates the dynamic equilibrium process of heat being "charged and released" in the welding wheel. As T... eq As the temperature rises, the subtrahend term (heat dissipation power) in the equation will gradually increase until it equals the minuend term (heat generation power), at which point T... eq It no longer rises, thus reproducing the heat capacity saturation characteristics of the physical system at the mathematical model level.

[0183] S803. Determine the thermal accumulation correction factor based on the thermal expansion mapping of material-equipment coupling.

[0184] In embodiments of this application, this step maps changes in the temperature dimension to corrections in the geometric dimension.

[0185] The heat accumulation correction factor is a dimensionless coefficient calculated using the heat-mechanical transfer function, used to correct for a preset elongation rate. The calculation formula is:

[0186] Heat accumulation correction factor = α wheel ×(T eq (k)-T amb )×λ coupling

[0187] Where, α wheel T is the coefficient of linear expansion of the welding wheel material (e.g., chromium-zirconium-copper alloy); amb The ambient reference temperature; λ coupling This is the contact arc length correction factor.

[0188] Because the welding wheel expands in diameter due to heat, the contact arc length between the welding wheel and the first material will increase slightly under constant downward pressure. This change in contact area alters the micro-friction driving characteristics, thus affecting the actual linear velocity transmission efficiency. Therefore, through λ... coupling The simple linear thermal expansion of the material is transformed into a comprehensive influence on the synchronous driving process of the roller welding.

[0189] As can be seen, the embodiments of this application propose a heat accumulation observation scheme based on dynamic cooling efficiency. This scheme incorporates the nonlinear turbulent influence of welding wheel rotation speed on water cooling efficiency into the model, constructing a closed-loop estimation system that includes Joule heat injection, variable-coefficient convective heat dissipation, and heat capacity saturation characteristics. This allows for accurate reconstruction of the thermal balance state of the welding wheel and shaft system without the need for easily damaged contact temperature sensors. Furthermore, by calculating and compensating for this heat accumulation factor in real time, the scheme effectively solves the problem of synchronization accuracy fluctuations caused by drastic changes in thermal boundary conditions under complex operating conditions such as variable speed, variable overload, and long-term operation of the roller welding machine.

[0190] Secondly, embodiments of this application provide a control system for a roll welding machine, which is used to execute the control method for the roll welding machine as described in any of the above embodiments.

[0191] Thirdly, embodiments of this application provide an electronic device that integrates the control system of any of the roll welding machines provided in the embodiments of this application. The electronic device includes a processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the control method for the roll welding machine as described in any of the above embodiments.

[0192] Fourthly, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc. The computer-readable storage medium stores a computer program configured to be executed by a processor to implement the control method for the roll welding machine as described in any of the preceding claims.

[0193] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A control method for a roll welding machine, characterized in that, The control method for the roller welding machine includes: The material type and thickness of the first material to be welded by the roller welding machine are obtained, as well as the set reference speed of the welding roller group motor in the roller welding machine. Based on the material type and material thickness, determine the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition; Determine the tension deviation between the current actual tension value and the set tension value of the first material; The tension deviation is calculated using the target proportional coefficient, the target integral coefficient, and the target derivative coefficient to determine the PID speed compensation amount; Based on the PID speed compensation amount and the set reference speed, the PID target parameters of the unwinding motor of the first material are determined; The rotational speed of the unwinding motor for the first material is controlled by PID according to the PID target parameters.

2. The control method for the roll welding machine as described in claim 1, characterized in that, The step of determining the target proportional coefficient, target integral coefficient, and target differential coefficient corresponding to the current working condition based on the material type and material thickness includes: Determine the basic proportional coefficient, basic integral coefficient, and basic differential coefficient corresponding to the material type; Based on the material thickness, determine the thickness gain value; The target proportional coefficient, the target integral coefficient, and the target differential coefficient are determined based on the thickness gain value, the basic proportional coefficient, the basic integral coefficient, and the basic differential coefficient.

3. The control method for the roll welding machine as described in claim 2, characterized in that, Determining the thickness gain value based on the material thickness includes: Obtain the preset material standard reference thickness; Calculate the thickness ratio between the material thickness and the material standard reference thickness; The thickness ratio is input into a preset nonlinear gain curve model, and the thickness gain value corresponding to the thickness ratio is output. The nonlinear gain curve model defines the gain gradient corresponding to different thickness ratio ranges.

4. The control method for the roller welding machine as described in claim 2, characterized in that, After performing PID control on the speed of the unwinding motor of the first material according to the PID target parameters, the method further includes: The tension deviations within multiple consecutive control cycles are determined to generate a tension deviation sequence; Based on the tension deviation sequence, the current control performance index is determined, which includes any one of the following three: integral value of steady-state error, tension overshoot, and oscillation period; If the control performance index is greater than the preset index threshold, then with the goal of minimizing the control performance index, the correction amount of the basic proportional coefficient, the basic integral coefficient, and the basic derivative coefficient is determined using a preset parameter optimization model. Using the correction amount, adjust the values ​​of the current basic proportional coefficient, basic integral coefficient, and basic differential coefficient; Return to the step of determining the target proportional coefficient, the target integral coefficient, and the target differential coefficient based on the thickness gain value, the basic proportional coefficient, the basic integral coefficient, and the basic differential coefficient.

5. The control method for the roll welding machine as described in claim 1, characterized in that, The step of calculating the tension deviation using the target proportional coefficient, the target integral coefficient, and the target derivative coefficient to determine the PID speed compensation amount includes: The product of the target proportionality coefficient and the tension deviation is determined to obtain the proportional term component; Obtain the cumulative value of tension deviation within the historical control cycle, and determine the product of the target integral coefficient and the cumulative value of tension deviation to obtain the integral term component; Obtain the historical tension deviation from the previous control cycle, determine the difference between the tension deviation and the historical tension deviation, and determine the product of the target differential coefficient and the difference to obtain the differential term component; The proportional term component, the integral term component, and the derivative term component are summed to obtain the PID speed compensation amount.

6. The control method for the roll welding machine as described in claim 5, characterized in that, After summing the proportional term component, the integral term component, and the derivative term component to obtain the PID speed compensation amount, the method further includes: Obtain the real-time acceleration of the motor of the welding roller group; Based on the real-time acceleration, determine the corresponding compensation saturation threshold; If the PID speed compensation amount is greater than the compensation amount saturation threshold, the tension deviation cumulative value is corrected based on the difference between the PID speed compensation amount and the compensation amount saturation threshold. Return to the step of determining the product of the target integral coefficient and the cumulative value of the tension deviation to obtain the integral term component.

7. The control method for the roll welding machine as described in claim 1, characterized in that, The step of determining the PID target parameters of the unwinding motor for the first material based on the PID speed compensation amount and the set reference speed includes: Obtain the preset tensile strength of the first material; Based on the set reference speed and the preset stretching rate, calculate the feedforward synchronous linear velocity of the first material under the current working conditions; The PID speed compensation is superimposed on the feedforward synchronous linear speed to obtain the total target unwinding linear speed. Based on the total unwinding target linear velocity, the PID target parameters of the unwinding motor for the first material are generated.

8. A control system for a roll welding machine, characterized in that, The control system of the roller welding machine is used to execute the control method of the roller welding machine according to any one of claims 1 to 7.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the control method of the roll welding machine according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program configured to be executed by a processor to implement the control method of the roll welding machine according to any one of claims 1 to 7.

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