Linear servo motor tension structure and control method thereof

Abstract

The invention provides a linear servo motor tension structure and a control method thereof, which are applied to the technical field of winding machines, real-time and accurate detection of the displacement of a sliding block guide wheel is realized by utilizing a high-precision magnetic suspension sliding rail and a magnetic railing ruler, and a tension control program operated by a PLC (Programmable Logic Controller) is used in combination with the motor torque information of a linear servo motor to control the tension of the linear servo motor. The rotating speed of the linear servo motor and the rotating speed of the rolling servo motor can be dynamically calculated and adjusted. According to the scheme, the problems that the tension precision is low, the speed control is insufficient, the coiled material is uneven or bent and the like due to the fact that the tension of the rotating motor cannot meet the field and preset parameters or manual experience adjustment is insufficient are effectively solved. The high-precision constant-tension winding device for the packing belt has the advantages that high-precision constant-tension winding of the packing belt under various working conditions can be guaranteed, production efficiency and product quality are improved remarkably, dependence on artificial experience is avoided, and intelligence and automation of tension control are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of winding machines, in particular to a linear servo motor tension structure and a control method thereof. BACKGROUND

[0002] In modern industrial production, especially in scenarios that require precise winding of the strip, such as the production and packaging of packing tapes, how to ensure that the tension of the strip is always stable during high-speed operation is the key to ensuring product quality and production efficiency. In order to achieve this goal, a precise linear servo motor tension winding mechanism is usually used. The core components of this mechanism include a linear servo motor, a guide rail module, and a slider guide wheel, which work together to ensure that the strip is wound smoothly and neatly.

[0003] The stable output of the strip tension mainly depends on the torque control mode of the linear servo motor. When the system sets a target tension value, the torque sensor inside the linear servo motor will monitor the actual output torque in real time and compare it with the target value. Through a proportional-integral-derivative (PID) regulator, the system can dynamically adjust the output of the motor to maintain the stability of the torque. However, in actual production, especially in scenarios such as packing tape winding that require high speed and material adaptability, the traditional control method, although it achieves rapid changeover through torque parameter presetting, still faces challenges. When the production line needs to frequently switch between different materials of packing tapes and requires high tension stability at extreme high speed, relying solely on preset parameters or manual experience for fine-tuning often fails to achieve optimal results. This not only limits the further improvement of production efficiency, but also may lead to inaccurate tension control when facing new materials or complex working conditions, resulting in problems such as strip wrinkles or breakage. Therefore, how to break away from the dependence on manual experience and achieve fully intelligent and automatic adjustment of tension control parameters to adapt to various materials and extreme high-speed winding requirements has become a technical problem that needs to be solved.

[0004] In view of the above problems, the prior art needs to be improved. SUMMARY

[0005] In view of the above problems of the prior art, the present application provides a linear servo motor tension structure and a control method thereof, aiming to solve the problem that the traditional control method is difficult to maintain high tension stability under frequent switching between different materials and extreme high speed during the winding of packing tapes, and the strong dependence on manual experience.

[0006] In a first aspect, a linear servo motor tension structure is provided, which is arranged on a winding machine and used to adjust the tension of a packing tape during winding to enable constant tension winding of the packing tape. The linear servo motor tension structure at least comprises: The linear servo motor at least comprises a stator, a mover and a linear motion module; the stator comprises a high-precision magnetic suspension slide rail, and a high-precision magnetic scale is arranged on the high-precision magnetic suspension slide rail; the mover comprises a magnetic slider, the magnetic slider is movably installed on the high-precision magnetic suspension slide rail and reciprocally runs along the high-precision magnetic suspension slide rail; the linear motion module at least comprises a driver, and the driver drives the magnetic slider to run on the high-precision magnetic suspension slide rail; A slider guide wheel is arranged on the magnetic slider, and the packing belt runs through the slider guide wheel along with the magnetic slider, so that the constant tension control is maintained. A tension control electric control module at least comprises a PLC controller, the PLC controller runs a tension control program, the tension control program calculates the torque of the linear servo motor and the rotating speed of the winding servo motor according to the slider displacement information of the slider guide wheel detected by the high-precision magnetic scale and the motor torque information of the linear servo motor, so as to control the tension balance of unwinding and winding.

[0007] By the technical scheme, the linear servo motor tension structure integrated with the high-precision magnetic suspension slide rail, the magnetic scale and the PLC controller can realize real-time and accurate detection of the slider displacement and the motor torque, and dynamically adjust the operation parameters of the winding machine according to the detection results, so as to realize the constant tension winding of the packing belt, effectively solve the problem of unstable tension control of the traditional method in the high-speed and multi-material switching scene, and significantly improve the production efficiency and product quality.

[0008] In a second aspect, a control method of a linear servo motor tension structure is applied to the linear servo motor tension structure, and the control method comprises the following steps: S1: obtaining operation data of the linear servo motor tension structure, the operation data at least comprising motor torque information and slider displacement information; S2: calculating a tension fluctuation amplitude and a tension response speed based on the motor torque information, calculating displacement stability of the slider guide wheel based on the slider displacement information, and identifying a small vibration frequency of the strip based on the motor torque information or the slider displacement information; S3: evaluating tension control system performance and strip dynamic characteristics based on the tension fluctuation amplitude, the tension response speed, the displacement stability and the small vibration frequency of the strip, and obtaining an evaluation result; S4: calculating torque control parameters of the linear servo motor and rotating speed correction parameters of the winding servo motor by using a PID algorithm according to the evaluation result; S5: controlling the linear servo motor to run according to the torque control parameters, and controlling the winding servo motor to run according to the rotating speed correction parameters.

[0009] This technical solution enables intelligent control of the tension structure of a linear servo motor. By acquiring real-time data and conducting multi-dimensional performance evaluation, control parameters can be dynamically adjusted, effectively improving the accuracy and stability of tension control and eliminating reliance on manual experience.

[0010] Furthermore, step S2 includes: S21: Based on the motor torque information, obtain the strip tension data and calculate the standard deviation of the strip tension data as an indicator of the tension fluctuation amplitude; S22: Record the time required from the issuance of the tension control command to the time when the strip tension data reflected by the motor torque information reaches the preset percentage of the new target value, as an indicator of the tension response speed; S23: Based on the slider displacement information, obtain the slider guide wheel displacement and calculate the root mean square error of the slider guide wheel displacement as an indicator of displacement stability. S24: Perform spectrum analysis on the motor torque information or the slider displacement information to identify the frequency components with concentrated energy and obtain the micro vibration frequency of the strip.

[0011] This technical solution provides a specific method for quantitatively evaluating tension fluctuations, response speed, displacement stability, and strip vibration frequency, providing accurate data support for subsequent system performance evaluation and parameter adjustment.

[0012] Furthermore, step S3 includes: S31: Define multiple operating states, including startup state, stable state, transition state and abnormal state; S32: Set an evaluation threshold for the operating state; S33: Based on the tension fluctuation amplitude, the tension response speed, the displacement stability, and the micro-vibration frequency of the strip, determine the current operating status of the winding machine according to the evaluation threshold; S34: Assess the system performance level of the winding machine under its current operating condition; S35: The operating status and the system performance level are used as the evaluation results.

[0013] This technical solution enables intelligent identification of the winding machine's operating status and quantitative evaluation of system performance, providing a basis for decision-making in subsequent adaptive parameter adjustments and improving the intelligence level of the control system.

[0014] Furthermore, step S33 includes: S331: If the tension fluctuation exceeds its corresponding preset abnormal threshold, the winding machine is determined to be in an abnormal state; otherwise, it is not in an abnormal state. S332: If not in an abnormal state, obtain the winding speed of the winding machine. If the winding speed is lower than the preset start-up completion speed and the tension response speed is higher than the preset response threshold, it is determined to be in the start state; otherwise, it is not in the start state. S333: If not in the start-up state, determine whether any of the following indicators exceeds the corresponding preset stability threshold: tension fluctuation amplitude, displacement stability, and strip micro-vibration frequency. If it exceeds the corresponding preset stability threshold but does not reach the corresponding preset abnormal threshold, determine that the winding machine is currently in a transition state; if it does not exceed the corresponding preset stability threshold, determine that the winding machine is currently in a stable state.

[0015] Furthermore, step S34 includes: S341: When the system is in a non-abnormal state, a set of ideal performance reference thresholds is preset for the current operating state of the winding machine; S342: Calculate the tension fluctuation amplitude, the tension response speed, the displacement stability, and the deviation of the micro-vibration frequency of the strip from the ideal performance reference threshold; S343: Determine the system performance level based on the degree of deviation.

[0016] Furthermore, step S4 includes: S41: Based on the operating status and the system performance level, determine the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor from the preset parameter mapping table; S42: The proportional gain, the integral gain, the differential gain, and the torque feedforward are used together as the torque control parameters of the linear servo motor, and the speed feedforward is used as the speed correction parameter of the winding servo motor.

[0017] Furthermore, step S41 includes: S411: During the operation of the winding machine, the operating status and the system performance level are continuously acquired; S412: Determine whether the system performance level is lower than the preset optimization target; S413: If the system performance level is lower than the optimization target, then the parameter set corresponding to the current operating state in the parameter mapping table is adjusted according to the degree of deviation between the system performance level and the optimization target; S414: Update the adjusted parameter set to the parameter mapping table, and determine the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor from the updated parameter mapping table.

[0018] Furthermore, step S413 includes: S4131: Record the operating status, system performance level, degree of deviation, and historical parameter adjustment results to build a historical adjustment database; S4132: Based on the current operating status and the system performance level, retrieve similar historical data from the historical adjustment database; S4133: Based on the current degree of deviation and the retrieved similar historical data, adjust the parameter set corresponding to the current running state in the parameter mapping table.

[0019] Furthermore, step S414 includes: S4141: Using the operating status and the system performance level as indexes, search in the updated parameter mapping table to obtain the parameter value; S4142: Interpolate the parameter values ​​to obtain the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor.

[0020] Beneficial Effects: This application proposes a linear servo motor tension structure and its control method, which effectively solves the problems of unstable tension control and strong reliance on manual experience during the winding process of packing tape in existing technologies by organically combining a linear servo motor, a slider guide wheel, and a tension control electrical control module. Specifically, this structure utilizes a high-precision magnetic levitation slide rail and a magnetic scale to achieve real-time and accurate detection of the slider guide wheel displacement. Combined with the motor torque information of the linear servo motor, the tension control program running through the PLC controller can dynamically calculate and adjust the speeds of the linear servo motor and the winding servo motor. This closed-loop control mechanism ensures that the packing tape maintains constant tension throughout the winding process, even under complex working conditions such as high-speed operation or frequent switching of different packing tape materials. Compared with traditional control methods that rely on preset parameters or manual experience, the technical solution of this application significantly improves the accuracy, response speed, and adaptability of tension control, thereby effectively avoiding problems such as tape wrinkling and breakage, improving product quality and production efficiency, and realizing intelligent and automated tension control. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the installation of a linear servo motor tension structure proposed in this application.

[0022] Figure 2 This is a three-dimensional view of the tension structure of a linear servo motor proposed in this application.

[0023] Figure 3This is a flowchart illustrating a control method for a linear servo motor tension structure proposed in this application.

[0024] Labeling Explanation: 1. Winding machine; 2. Linear servo motor tension structure; 21. Linear servo motor; 22. Stator; 23. Mover; 11. Vertical mounting plate; 221. High-precision magnetic levitation slide rail; 24. Slider guide wheel; 232. Magnetic slider; 25. Cable drag chain. Detailed Implementation

[0025] 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 a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and marked in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0026] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] Please refer to Figure 1 , Figure 2 A linear servo motor tension structure 2, mounted on the winding machine 1, is used to adjust the tension of the packing strap during the winding process, ensuring constant tension winding of the packing strap, and includes at least: The linear servo motor 21 includes at least a stator 22, a mover 23, and a linear motion module. The stator 22 includes a high-precision magnetic levitation slide rail 221, on which a high-precision magnetic scale is mounted. The mover 23 includes a magnetic slider 232, which is movably mounted on the high-precision magnetic levitation slide rail 221 and reciprocates along it. The linear motion module includes at least a driver that drives the magnetic slider 232 to run on the high-precision magnetic levitation slide rail 221. The slider guide wheel 24 is set on the magnetic slider 232. The packing strap moves with the magnetic slider 232 through the slider guide wheel 24, thereby maintaining constant tension control. Tension control electrical control module: includes at least a PLC controller. The PLC controller runs a tension control program. The tension control program calculates the torque of the linear servo motor 21 and the speed of the winding servo motor based on the slider displacement information of the slider guide wheel 24 detected by the high-precision magnetic scale and the motor torque information of the linear servo motor 21, thereby controlling the tension balance between unwinding and winding.

[0028] The linear servo motor tension structure 2 proposed in this application aims to provide a solution for achieving constant tension winding of packing tape. The linear servo motor 21 is an actuator capable of converting electrical energy into linear motion, characterized by high precision, high response speed, and high torque output, and is used in this application to provide the power required for tension adjustment.

[0029] The stator 22 is the stationary part of the linear servo motor 21.

[0030] The mover 23 is the movable part of the linear servo motor 21, which moves on the high-precision magnetic levitation slide rail 221.

[0031] The high-precision magnetic levitation slide rail 221 is a guide rail system that uses magnetic force to achieve contactless levitation and movement. It has the advantages of low friction, high precision and long service life.

[0032] A high-precision magnetic grating ruler is a sensor that uses changes in magnetic field to measure displacement and can provide accurate displacement information.

[0033] The linear motion module is an auxiliary mechanism for realizing the linear motion of the magnetic slider 232. It includes at least a driver that converts input electrical energy into current, driving the magnetic slider 232 to generate a magnetic field. This causes the magnetic slider 232 to interact with the magnetic field of the high-precision magnetic levitation rail 221, directly generating linear thrust. The linear motion module also includes cables and a cable chain 25 to protect the cables. The cables include at least a power line connected to the magnetic slider 232 and a reading head line for the high-precision magnetic scale.

[0034] The slider guide wheel 24 is a component that is in direct contact with the packing strap, and its displacement change directly reflects the tension state of the packing strap.

[0035] The tension control electronic control module is the core control unit of the entire system. The PLC controller is an industrial automation control device that is responsible for running the tension control program. This program processes various sensor data to achieve coordinated control of the linear servo motor 21 and the winding servo motor, ultimately achieving constant tension winding.

[0036] Specifically, the linear servo motor 21 is the power core of the entire tension adjustment system. This linear servo motor 21 includes at least a stator 22, a mover 23, and a linear motion module. The stator 22 can be implemented in various ways. For example, the stator 22 can be composed of one or more permanent magnet arrays, which are precisely fixed to a base to form a high-precision magnetic levitation slide rail 221. The high-precision magnetic levitation slide rail 221 is fixed to the vertical mounting plate 11 of the winding machine 1, and its main function is to provide a precise linear motion trajectory for the slider guide wheel 24. The positioning accuracy of the high-precision magnetic levitation slide rail 221 is within an error range of ±0.01mm.

[0037] The high-precision magnetic levitation slide rail 221 is equipped with a high-precision magnetic scale (accuracy between ±1µm and ±5µm). The high-precision magnetic scale can be implemented by embedding a magnetic coding strip on the side or inside of the slide rail, and using a reading head to detect changes in the magnetic field to obtain accurate displacement information.

[0038] The mover 23 includes at least a magnetic slider 232. The magnetic slider 232 can be implemented as a slider with a permanent magnet, which generates thrust by interacting with the magnetic field on the stator 22.

[0039] The linear motion module includes at least a driver and a cable carrier 25. The cable carrier 25 can be implemented as a flexible chain that houses the cable and bends or extends with the movement of the magnetic slider 232. The driver drives the magnetic slider 232 to run on a high-precision magnetic levitation rail 221. The driver can be a servo driver that receives commands from the control system and precisely controls the current input to the magnetic slider 232, thereby achieving precise control of the position and speed of the magnetic slider 232.

[0040] The slider guide wheel 24 is mounted on the magnetic slider 232. The strapping tape moves with the magnetic slider 232 via the slider guide wheel 24, thereby maintaining constant tension control. The slider guide wheel 24 can be implemented as a low-friction roller, and its bearing design ensures smooth rotation even at high speeds, reducing wear on the strapping tape.

[0041] The tension control electrical control module includes at least a PLC controller. The PLC controller can be an industrial-grade programmable logic controller (PLC) running a tension control program. Based on the slider displacement information of the slider guide wheel 24 detected by a high-precision magnetic scale and the motor torque information of the linear servo motor 21, the tension control program calculates the rotational speeds of the linear servo motor 21 and the winding servo motor, thereby controlling the tension balance between unwinding and winding. Specifically, the tension control program first calculates a series of performance indicators such as tension fluctuation, response speed, and displacement stability based on the real-time acquired motor torque and slider displacement information. Then, based on the evaluation results of these indicators, the program uses a PID algorithm to calculate two sets of key parameters: one is the torque control parameters for the linear servo motor 21 (such as PID gain and torque feedforward), and the other is the speed correction parameters for the winding servo motor (such as speed feedforward). In application, the linear servo motor 21 adjusts its thrust at high frequency and with precision based on its torque parameters to directly maintain a constant tension in the packing strap (force control); simultaneously, the winding servo motor adjusts its speed based on its speed correction parameters (mainly based on the system balance state reflected by the slider displacement information) to match the overall winding speed of the material (speed control). It is this coordinated control of "force" and "speed" that ultimately achieves tension balance between unwinding and winding.

[0042] The tension control program can be implemented as a PID algorithm-based control program that dynamically adjusts the output of the linear servo motor 21 and the winding servo motor by real-time monitoring of the slider displacement and motor torque to maintain constant tension of the packing tape.

[0043] Compared to traditional tension control schemes, this application significantly improves the accuracy and response speed of displacement detection by introducing a high-precision magnetic levitation slide rail 221 and a high-precision magnetic scale. The use of the high-precision magnetic levitation slide rail 221 eliminates mechanical friction, making the movement of the magnetic slider 232 smoother and more precise, thus enabling it to more sensitively reflect minute tension changes in the packing strap. The high-precision magnetic scale provides centimeter-level or even millimeter-level displacement feedback, providing more accurate real-time data for the tension control program.

[0044] Furthermore, the tension control program running on the PLC controller in the tension control module can intelligently calculate and adjust based on the slider displacement information detected by the high-precision magnetic scale and the motor torque information of the linear servo motor 21. This dynamic control mechanism based on real-time data feedback enables the system to break free from reliance on human experience and achieve automated and intelligent adjustment of tension control parameters. Regardless of changes in the material of the strapping or the maximum winding speed, the system can ensure that the strapping remains under constant tension by accurately calculating and coordinating the rotational speeds of the linear servo motor 21 and the winding servo motor.

[0045] Please refer to Figure 3 A control method for a linear servo motor tension structure 2, applied to the aforementioned linear servo motor tension structure 2, includes the following steps: S1: Obtain the operating data of the linear servo motor tension structure 2. The operating data includes at least the motor torque information and the slider displacement information. S2: Calculate the tension fluctuation amplitude and tension response speed based on motor torque information, calculate the displacement stability of slider guide wheel 24 based on slider displacement information, and identify the small vibration frequency of the strip based on motor torque information or slider displacement information. S3: Based on the tension fluctuation amplitude, tension response speed, displacement stability, and the micro-vibration frequency of the strip, evaluate the performance of the tension control system and the dynamic characteristics of the strip, and obtain the evaluation results; S4: Based on the evaluation results, the torque control parameters of the linear servo motor 21 and the speed correction parameters of the winding servo motor are calculated using the PID algorithm. S5: Controls the linear servo motor 21 to run according to the torque control parameters, and controls the winding servo motor to run according to the speed correction parameters.

[0046] Specifically, the above control method aims to ensure that the packing tape maintains constant tension during the winding process through real-time monitoring and dynamic adjustment.

[0047] Step S1 involves acquiring the operating data of the linear servo motor tension structure 2. The operating data is a real-time reflection of the system's operating status and includes at least the motor torque information of the linear servo motor 21 and the slider displacement information of the slider guide wheel 24. The motor torque information is directly related to the tension on the packing strap, while the slider displacement information reflects the dynamic response and stability of the tension adjustment mechanism.

[0048] Furthermore, in step S2, key performance indicators are calculated based on the acquired operational data. Specifically, the tension fluctuation amplitude and tension response speed are calculated based on the motor torque information, which respectively quantify the degree of tension fluctuation near the target value and the system's response speed to changes in tension commands. The displacement stability of the slider guide wheel 24 is calculated based on the slider displacement information, which measures the smoothness of the slider guide wheel 24 during linear motion. In addition, by performing spectral analysis on the motor torque information or slider displacement information, the minute vibration frequencies that may occur in the strip during winding can be identified, which is crucial for diagnosing and suppressing resonance phenomena.

[0049] Therefore, in step S3, based on the tension fluctuation amplitude, tension response speed, displacement stability, and micro-vibration frequency of the strip obtained from the above calculations, the overall performance of the tension control system and the dynamic characteristics of the packing strap are comprehensively evaluated, resulting in a comprehensive evaluation result. This evaluation result provides a decision-making basis for subsequent adjustment of control parameters.

[0050] In this application, the dynamic characteristics of the strip are a crucial factor affecting the stability of the tension control system. In step S2, the method quantifies the motor torque or slider displacement information into a technical indicator called the micro-vibration frequency of the strip through spectral analysis. Therefore, the evaluation of the strip's dynamic characteristics in step S3 does not output a single evaluation parameter. Instead, the micro-vibration frequency of the strip obtained in S2, along with indicators such as tension fluctuation amplitude, tension response speed, and displacement stability, are used as inputs for the evaluation in S3.

[0051] Furthermore, as defined in steps S31 to S35, the evaluation result defined in this application is a combined result, specifically including two parts: "operating status" and "system performance level".

[0052] The strip micro-vibration frequency, a dynamic characteristic indicator, is used in the S3 evaluation process for the following two aspects: First, to determine the operating status: As described in step S333, the system determines whether the strip micro-vibration frequency indicator exceeds a preset stability threshold. If this indicator (or other indicators such as tension fluctuation or displacement stability) exceeds the stability threshold but does not reach the abnormal threshold, the system determines that it is currently in a "transitional state". Second, to evaluate the system performance level: As described in step S34, after determining the operating status, the system evaluates the system performance level in that state. This evaluation is based on the degree of deviation of all key indicators, including the strip micro-vibration frequency, from the ideal performance reference curve.

[0053] In a preferred embodiment, in step S4, based on the evaluation results obtained in step S3, the torque control parameters of the linear servo motor 21 and the speed correction parameters of the winding servo motor are calculated using a PID (Proportional-Integral-Derivative) algorithm. The PID algorithm is a feedback control algorithm widely used in industrial control, capable of adjusting the control output based on the proportional, integral, and derivative terms of the system error to achieve precise control. The torque control parameters are used to directly adjust the output torque of the linear servo motor 21, thereby precisely controlling the tension of the packing tape. Specifically, the torque control parameters mainly include proportional gain (P), integral gain (I), derivative gain (D), and torque feedforward. They work together to adjust the output torque of the linear servo motor, as detailed below: The system continuously compares the target tension value with the actual tension reflected by the motor torque information. When an error exists between the two, the PID controller calculates a corrective torque based on the pre-set proportional gain, integral gain, and derivative gain parameters. These parameters determine the strength and speed of the controller's response to the current error (P), cumulative error (I), and error change rate (D).

[0054] To improve the system's response speed and anti-interference capability, the system also uses torque feedforward. This is a predictive parameter that applies a compensating torque in advance, based on a known system model or experience, before a disturbance (such as a change in winding speed or startup) occurs. For example, an initial torque feedforward is applied at startup to overcome inertia and friction, or the output torque is pre-adjusted based on changes in winding diameter.

[0055] Finally, the PLC controller combines the corrected torque calculated by the PID controller with the torque feedforward to generate a final torque control command. This command is sent to the driver of the linear servo motor, which then precisely controls the motor's current and magnetic field to produce a precise output torque that perfectly matches the command, thus maintaining constant tension in the packing strap.

[0056] The speed correction parameter is used to fine-tune the speed of the winding servo motor to work in conjunction with the linear servo motor 21 to maintain constant tension winding. Specifically, the PLC controller monitors the slider displacement information detected by the high-precision magnetic scale in real time. This displacement information directly reflects whether the speeds of the unwinding and winding stages are matched.

[0057] If the winding servo motor rotates slower than the material feed rate, the strapping will tend to loosen, and the slider guide roller (mover) will shift to one side. Conversely, if the rotation speed is faster than the feed rate, the strapping will become too tight, and the slider guide roller will shift to the other side.

[0058] The tension control program in the PLC processes this slider displacement information. Using speed correction parameters (such as speed feedforward) as a reference, it calculates a precise speed adjustment command based on the degree and direction of the slider displacement deviation. This command is sent to the driver of the take-up servo motor, fine-tuning its speed (either increasing or decreasing).

[0059] In this way, the system can ensure that the speed of the winding motor and the tension system adjusted by the linear servo motor are perfectly coordinated, so that the slider guide wheel is always kept in a dynamically balanced center position, thereby achieving long-term constant tension winding.

[0060] Finally, in step S5, based on the torque control parameters and speed correction parameters calculated in step S4, the linear servo motor 21 and the winding servo motor are precisely controlled to run according to the preset tension target, thereby achieving constant tension winding of the packing tape.

[0061] The solution proposed in this application effectively solves the problem that the traditional linear servo motor tension structure 2 is difficult to maintain precise constant tension under dynamic working conditions by constructing a closed-loop feedback control system of "displacement detection-signal feedback-speed adjustment". Specifically, in some preferred embodiments, it is assumed that a PET strapping with a width of 50mm needs to be wound with constant tension on a certain winding machine 1.

[0062] First, in step S1, a high-precision torque sensor mounted on the linear servo motor 21 collects motor torque information in real time, and a high-precision magnetic scale mounted on the high-precision magnetic levitation slide rail 221 acquires slider displacement information of the slider guide wheel 24 in real time. These data are acquired by the control system at a frequency of once per millisecond.

[0063] Next, in step S2, the control system processes the acquired data. For example, it calculates the standard deviation of the motor torque over the past second to obtain the tension fluctuation amplitude; it measures the tension response speed by recording the time required for the actual tension to reach 90% of the new set value after the tension set value is changed; it evaluates the displacement stability by calculating the root mean square error of the displacement of the magnetic slider 232 over a period of time; and it performs a fast Fourier transform (FFT) on the motor torque information to identify possible minute vibration frequencies of the packing strap, such as periodic vibrations of 20 Hz.

[0064] Subsequently, in step S3, the control system evaluates the performance level of the current tension control system and the dynamic characteristics of the packing strap based on the calculated tension fluctuation amplitude, tension response speed, displacement stability, and micro-vibration frequency of the strapping, combined with preset performance thresholds. For example, if the evaluation shows: If the system performance level indicators are poor (e.g., tension fluctuation amplitude exceeds 0.5N, tension response speed is slower than 200ms, and displacement stability root mean square error is greater than 0.1mm); and the dynamic characteristics of the strip are assessed by spectrum analysis as "having obvious 20Hz vibration", then the assessment results may indicate that the system is in a "transitional state" or "stable state".

[0065] Based on this evaluation result, in step S4, the control system uses a PID algorithm to dynamically adjust the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward of the linear servo motor 21 and the speed feedforward of the winding servo motor, according to the current system state and target performance requirements. For example, if the system response speed is slow, the proportional gain and integral gain may be appropriately increased; if vibration exists, the derivative gain may be adjusted or a notch filter may be introduced.

[0066] Finally, in step S5, these calculated and adjusted torque control parameters and speed correction parameters are sent in real time to the drivers of the linear servo motor 21 and the winding servo motor. This precisely controls the operation of the linear servo motor 21, ensuring that its output torque accurately counteracts tension fluctuations and works in conjunction with the winding servo motor to ensure that the strapping maintains a preset constant tension, such as 100N, throughout the entire winding process. Through this dynamic and adaptive control method, tension stability can be effectively maintained even when the winding speed changes or the strapping material is uneven.

[0067] Furthermore, step S2 includes: S21: Based on the motor torque information, obtain the strip tension data and calculate the standard deviation of the strip tension data as an indicator of the tension fluctuation range; S22: Record the time required from the issuance of the tension control command to the time when the strip tension data reflected by the motor torque information reaches the preset percentage of the new target value, as an indicator of tension response speed; S23: Based on the slider displacement information, obtain the displacement of slider guide wheel 24, and calculate the root mean square error of slider guide wheel 24 displacement as an indicator of displacement stability. S24: Perform spectrum analysis on the motor torque information or slider displacement information to identify the frequency components with concentrated energy and obtain the micro vibration frequency of the strip.

[0068] In step S21, the motor torque information can be understood as the real-time torque data generated by the linear servo motor 21 during operation, which can be directly obtained through the motor controller. The strip tension data can be calculated based on the motor torque information. The specific calculation formula is: Strip tension = Motor torque / Slider guide wheel radius. The slider guide wheel radius is typically designed to be 20-50mm. In practical applications, the specific radius of the slider guide wheel 24 needs to be matched according to the width of the packing strap. For example, when the guide wheel radius is 30mm, if the motor outputs a torque of 0.6 N·m, it can be converted into a strip tension of 20 N. Calculating the standard deviation of the strip tension data aims to quantify the dispersion of the tension data around its average value. A larger standard deviation indicates more severe tension fluctuations, thus providing an objective and quantitative indicator of the tension fluctuation amplitude.

[0069] In step S22, the tension control command refers to the target tension value set manually in the system. The new target value is preset as a percentage, for example, 90% or 95%, to provide a practically acceptable stability range before the tension reaches full stability, thus more accurately reflecting the system's response speed. Recording the time required from the issuance of the command to the tension data first entering and remaining within this preset percentage range directly measures the tension control system's responsiveness to changes in the tension setpoint.

[0070] In step S23, the slider displacement information is typically acquired in real time by a high-precision magnetic scale built into the linear servo motor 21. The displacement of the slider guide wheel 24 can be directly extracted from the slider displacement information or obtained through filtering. The root mean square error of the slider guide wheel 24 displacement is calculated to evaluate the stability of the slider guide wheel 24 during linear motion. The root mean square error can effectively reflect the degree of displacement jitter or deviation, thus serving as a quantitative indicator of displacement stability.

[0071] In step S24, spectral analysis is performed on the motor torque information or slider displacement information, for example, using signal processing techniques such as Fast Fourier Transform (FFT). The purpose is to convert the time-domain signal into a frequency-domain signal, thereby identifying the frequency components with concentrated energy in the signal. These frequency components typically correspond to the minute vibration frequencies that may exist during the winding process of the packing tape, such as vibrations caused by mechanical resonance, imbalance, or the natural frequencies of the control system. Identifying these frequencies helps in diagnosing and locating the vibration source.

[0072] Through the above technical solutions, the calculation process for tension fluctuation amplitude, tension response speed, displacement stability, and the frequency of minute vibrations in the strip is standardized and quantified, significantly improving the accuracy and reliability of these key performance indicators. This enables the system to more accurately grasp the tension state and dynamic behavior of the strip during the winding process, providing a more solid data foundation for subsequent PID algorithm parameter calculations. This helps to achieve more refined and stable constant tension winding control, effectively avoiding control deviations or system instability caused by inaccurate assessments.

[0073] Furthermore, step S3 includes: S31: Define multiple operating states, including startup state, stable state, transition state, and abnormal state; S32: Set evaluation thresholds for operating status; S33: Based on the tension fluctuation amplitude, tension response speed, displacement stability, and the micro-vibration frequency of the strip, determine the current operating status of the winding machine 1 according to the evaluation threshold; S34: Evaluate the system performance level of the winding machine 1 under its current operating state; S35: Use operating status and system performance level as evaluation results.

[0074] Specifically, in step S31, multiple operating states of the winding machine 1 are defined, including a start-up state, a stable state, a transitional state, and an abnormal state. These states are designed to comprehensively cover various working conditions that the winding machine 1 may encounter in actual operation, so as to adopt different evaluation strategies and control measures for different working conditions. For example, the start-up state usually refers to the stage from which the winding machine 1 goes from a standstill to reaching the preset operating speed; the stable state refers to the stage in which the winding machine 1 operates stably at the preset speed for a long time; the transitional state may refer to the dynamic adjustment stage when the winding speed or tension value changes; and the abnormal state refers to the situation where the system malfunctions or its performance deviates significantly from expectations.

[0075] In step S32, corresponding evaluation thresholds are set for each operating state defined above. These evaluation thresholds are determined based on historical operating data, theoretical models, or actual test results, and are used to quantitatively determine whether the system is in a specific state and whether the system performance meets the requirements in that state. Preferably, statistical analysis based on historical operating data is used to calculate the average and standard deviation of each performance index, and then the average plus or minus two or three times the standard deviation is used as the threshold. For tension fluctuation amplitude, a maximum allowable standard deviation can be set, for example, 0.5N. For tension response speed, a maximum allowable time can be set, for example, 200ms. For the displacement stability of the slider guide wheel 24, a maximum allowable root mean square error can be set, for example, 0.1mm. For the small vibration frequency of the strip, an energy concentration threshold can be set, for example, when the energy proportion in a specific frequency range exceeds 15%, it is considered that there is significant vibration. These thresholds can be stored in the memory of the control system or managed through a configuration file so that they can be dynamically loaded and updated during system operation.

[0076] In step S33, the tension fluctuation amplitude, tension response speed, displacement stability, and micro-vibration frequency of the strip calculated in step S2 are compared with preset evaluation thresholds to determine the current operating state of the winding machine 1. This determination process is dynamic and can reflect the changes in the operating conditions of the winding machine 1 in real time.

[0077] In step S34, after determining the current operating state of the winding machine 1, the system performance level under this operating state is evaluated. This evaluation can be based on the degree of deviation of various indicators under the current state from the ideal performance indicators, or by comparing them with the preset performance standards under this state.

[0078] Step S35 outputs the determined operating status and evaluated system performance level as the final evaluation result, providing an accurate and comprehensive basis for the subsequent calculation of torque control parameters and speed correction parameters.

[0079] In some preferred embodiments, it is assumed that the winding machine 1 first enters the start-up state during operation. At this time, the system monitors the tension fluctuation amplitude, tension response speed, displacement stability of the slider guide wheel 24, and the micro-vibration frequency of the strip. For example, in the initial stage of start-up, the tension response speed may be high, and the tension fluctuation amplitude may also be large, but as long as these indicators are within the preset evaluation threshold range of the start-up state, the system judges it as a normal start-up process. Once the winding speed reaches the preset value and the various tension indicators tend to stabilize, the system will judge that it has entered a stable state based on the evaluation threshold. In the stable state, the requirements for indicators such as tension fluctuation amplitude and displacement stability will be more stringent, and any fluctuation exceeding the stability threshold may be identified as a transitional state or an abnormal state. For example, if the micro-vibration frequency of the strip suddenly increases and exceeds the stability threshold, but does not reach the abnormal threshold, the system will judge it as a transitional state and evaluate its performance level in order to adjust the control parameters in a timely manner. If the tension fluctuation amplitude suddenly exceeds the abnormal threshold significantly, the system will immediately judge it as an abnormal state and trigger the corresponding alarm or protection mechanism. Through this state-based and threshold-based evaluation mechanism, the system can accurately grasp the operating status of the winding machine 1 in real time and provide precise input for subsequent adaptive control.

[0080] Furthermore, step S33 includes: S331: If the tension fluctuation amplitude exceeds its corresponding preset abnormal threshold, the winding machine 1 is determined to be in an abnormal state; otherwise, it is not in an abnormal state. S332: If not in an abnormal state, obtain the winding speed of winding machine 1. If the winding speed is lower than the preset start-up completion speed and the tension response speed is higher than the preset response threshold, it is determined to be in the start-up state; otherwise, it is not in the start-up state. S333: If not in the start-up state, determine whether any of the following indicators exceeds the corresponding preset stability threshold: tension fluctuation amplitude, displacement stability, and strip micro-vibration frequency. If it exceeds the corresponding preset stability threshold but does not reach the corresponding preset abnormal threshold, determine that the winding machine 1 is currently in the transition state; if it does not exceed the corresponding preset stability threshold, determine that the winding machine 1 is currently in the stable state.

[0081] Specifically, the aforementioned preset anomaly threshold, start-up completion speed, preset response threshold, and preset stability threshold can all be preset based on actual application scenarios and experience. For example, the preset anomaly threshold can be set to trigger when the tension fluctuation amplitude exceeds a certain percentage of the normal operating range, indicating a potential fault or serious deviation. The preset start-up completion speed can be defined as a certain percentage of the winding machine 1 reaching its rated operating speed, such as 80% or 90%. The preset response threshold can be set as the upper limit of the tension response speed; exceeding this value indicates that the system response is too slow. The preset stability threshold is used to define the system's performance within the normal fluctuation range. For example, when any of the following indicators—tension fluctuation amplitude, displacement stability, or the frequency of minor vibrations in the strip—exceeds this threshold but does not reach its corresponding preset anomaly threshold, it indicates that the system may be in a non-ideal but controllable transitional state.

[0082] This application's solution addresses the potential ambiguity in traditional state determination methods by introducing a hierarchical and prioritized judgment logic. First, the system prioritizes determining whether the winding machine 1 is in an abnormal state. This is because abnormal states typically require immediate attention and handling, and this determination, based on the key indicator of tension fluctuation amplitude, can quickly identify serious deviations in system operation. Second, after ruling out abnormal states, the system determines whether it is in a startup state. This determination combines winding speed and tension response speed, accurately capturing the transition characteristics of the winding machine 1 from a standstill to normal operation. Finally, in a non-abnormal and non-starting state, the system further distinguishes between transitional and stable states. By checking whether the tension fluctuation amplitude, displacement stability, and the frequency of minor strip vibrations exceed their respective preset stability thresholds, it can finely identify subtle changes in system performance. This progressively advancing judgment mechanism ensures accurate and unambiguous classification of the winding machine 1's operating state at any given time.

[0083] Through the above technical solution, the operating status of the winding machine 1 can be identified more accurately and reliably. This refined status judgment avoids misjudgment or delayed response caused by ambiguous status, allowing subsequent control parameter adjustments to be more targeted. Specifically, when the system is in an abnormal state, an emergency stop or alarm can be triggered; when in the start-up state, a specific start-up control strategy can be adopted. For example, when the winding machine 1 starts from a stationary state, the control system first identifies that it is currently in the start-up state. At this time, the control system will activate a preset start-up control strategy. At the moment the motor starts, the linear servo motor 21 driver will apply a preset initial torque feedforward amount to quickly overcome the system inertia and friction, preventing the strapping from becoming loose in the early stage of start-up. This torque feedforward amount can be estimated based on parameters such as the width, thickness, and roll diameter of the strapping. Specifically, when the system starts or accelerates, it must overcome the inertia of the entire motion system (including the strapping and the winding roll). The width and thickness of the strapping (combined with the material density) determine the mass per unit length of the strapping material. The greater the mass, the greater the force (tension) required for acceleration. The roll diameter determines the moment of inertia of the winding spool. A large-diameter spool that is nearly fully wound has a much greater moment of inertia than a small-diameter spool that is nearly hollow.

[0084] When estimating the torque feedforward, the estimation model calculates the total inertia of the current system in real time based on these parameters, and estimates an acceleration torque as part of the feedforward.

[0085] In constant tension winding, the motor needs to apply torque, while tension is the force acting on the surface of the reel. The relationship between the two is: Torque = Tension × Reel radius.

[0086] As the winding diameter increases during the winding process, the torque output by the motor must also increase proportionally to maintain constant tension. The prediction model continuously monitors the winding diameter and calculates the basic torque required to maintain that tension at the current winding diameter based on the target tension value. This torque is also part of the feedforward.

[0087] Therefore, the tension control program in the PLC integrates the above model and pre-estimates a "torque feedforward" based on the input parameters such as the width, thickness, material density of the packing strap, and the real-time monitored roll diameter. This torque feedforward is directly applied to the linear servo motor so that the motor's output torque quickly approaches (or even reaches) the actual required value before the PID feedback controller begins to correct errors, thereby minimizing the risk of slack or tension shock in the packing strap during initial startup.

[0088] Furthermore, during startup, the tension value does not immediately reach the set value, but rather increases gradually using a smooth ramp function. For example, within the first 2 seconds after startup, the tension value increases linearly from 0N to the target tension value (e.g., 100N) to avoid sudden tension changes impacting the packing tape. During the startup phase, the proportional gain (Kp) and integral gain (Ki) of the PID controller may be set to relatively high values ​​to improve the system's response speed and eliminate steady-state errors in the initial startup phase. For example, Kp may be set to 0.8, Ki to 0.15, while the derivative gain (Kd) may be kept low or temporarily disabled to avoid oversensitivity to noise during startup. The speed correction parameters of the take-up servo motor are also adjusted in coordination with the torque control parameters of the linear servo motor 21. This coordinated adjustment means that in the startup state, the parameters of the linear motor are set to force control priority, actively establishing tension; while the parameters of the take-up motor are set to speed control follow, passively adjusting the speed based on the slider displacement results generated by the linear motor's operation. One is responsible for applying force, and the other is responsible for matching speed. The two work closely together through the link of slider displacement information to complete a smooth start-up process.

[0089] In the initial stage of startup, the winding servo motor may start at a low initial speed and gradually accelerate according to the displacement feedback of the linear servo motor 21 to ensure that the tension of the packing tape is within a controllable range.

[0090] When in a transitional state, flexible adjustments can be made to avoid entering anomalies. For example, if the tension fluctuation slightly exceeds the stable threshold but does not reach the abnormal threshold, the system can initiate a flexible adjustment strategy. This strategy may include: first, reducing the proportional gain of the PID controller by 5% to reduce the system's response to tension errors and prevent excessive oscillations; second, increasing the integral gain by 2% to slowly eliminate steady-state errors and ensure that the tension eventually returns to the target value; simultaneously, the speed correction parameters of the winding servo motor can be fine-tuned. For example, if the tension is too high, the winding speed can be slightly reduced by 0.1 m / min to alleviate the tension. These adjustments are gradual, and indicators such as tension fluctuation amplitude and displacement stability are continuously monitored during the adjustment process. If the indicators continue to deteriorate and approach the abnormal threshold, higher-level intervention measures will be triggered.

[0091] When in a stable state, optimal control parameters can be maintained. This significantly improves the overall performance, stability, and reliability of the tension control system, effectively reducing the risk of excessive tension fluctuations, delayed response, or minor vibrations during the winding process, thus ensuring the constant tension winding quality of the strapping.

[0092] Traditional tension control systems often rely solely on preset thresholds for qualitative judgment when assessing the system performance level of the winding machine 1 under its current operating state. However, this qualitative assessment method struggles to accurately quantify the quality of system performance, especially under non-abnormal conditions. It fails to meticulously reflect the gap between system performance and the ideal state, potentially leading to an insufficient understanding of system performance and affecting the precise adjustment of subsequent torque control parameters and speed correction parameters. Therefore, further, step S34 includes: S341: When the system is in a non-abnormal state, a set of ideal performance reference thresholds is preset for the current operating state of the winding machine 1; S342: Calculate the tension fluctuation amplitude, tension response speed, displacement stability, and the degree of deviation of the strip's micro-vibration frequency from the ideal performance reference threshold; S343: Determine the system performance level based on the degree of deviation.

[0093] Specifically, when the system is in a non-abnormal state, it means that the winding machine 1 is not judged to be in an abnormal state, i.e., the tension fluctuation amplitude does not exceed the preset abnormal threshold. For the current operating state of the winding machine 1, such as the start-up state, stable state, or transition state, a set of ideal performance reference thresholds needs to be preset. The ideal performance reference thresholds can be understood as the trend of the optimal or expected values ​​of key performance indicators such as tension fluctuation amplitude, tension response speed, displacement stability, and strip micro-vibration frequency changing with time or winding speed under a specific operating state. These curves can be obtained through historical data analysis. For example, after the winding machine 1 has undergone multiple adjustments and reached a good operating state, data such as tension fluctuation amplitude, tension response speed, displacement stability, and strip micro-vibration frequency under that state can be collected and stored. By performing statistical analysis on these historical data, such as calculating the average value and standard deviation, and combining it with time series analysis, ideal performance reference thresholds representing the "stable state" or "transition state" can be constructed. The purpose is to provide a benchmark for system performance evaluation.

[0094] The deviation refers to the difference between the actual measured tension fluctuation amplitude, tension response speed, displacement stability, and micro-vibration frequency of the strip and the ideal performance reference threshold under the corresponding operating conditions. The deviation can be calculated using various mathematical methods, such as mean square error, absolute error, and percentage deviation, to quantify the gap between actual and ideal performance. For example, under stable operating conditions, the ideal tension fluctuation amplitude is 0.5N. If the actual measured tension fluctuation amplitude is 0.8N, the deviation can be calculated using the absolute error method: Deviation = |0.8N - 0.5N| = 0.3N. Alternatively, the percentage deviation method can be used: Deviation = ((0.8N - 0.5N) / 0.5N) * 100% = 60%. For multiple indicators, the deviation of each indicator can be calculated, and then a comprehensive deviation can be obtained through weighted averaging or maximum deviation. For example, if the tension fluctuation amplitude deviates by 60%, the tension response speed deviates by 50%, the displacement stability deviates by 50%, and the micro-vibration frequency of the strip deviates by 40%, a comprehensive system performance deviation score can be calculated based on these deviations and the preset weights.

[0095] In practical applications, system performance levels are determined based on the degree of deviation. The smaller the deviation, the higher the system performance level, and vice versa. System performance levels can be divided into different grades, such as "excellent," "good," "average," and "poor," or represented by a continuous numerical value.

[0096] In some preferred embodiments, it is assumed that the winding machine 1 is currently in a stable state, and an ideal performance reference threshold for this stable state has been preset. The ideal performance reference threshold can be defined as follows: tension fluctuation amplitude should be less than 0.5N, tension response speed should be less than 0.2 seconds, displacement stability (root mean square error) should be less than 0.1mm, and the strip micro-vibration frequency should be below 5Hz with energy concentration below 10%. In actual operation, the system acquires the current operating data and calculates the tension fluctuation amplitude to be 0.8N, the tension response speed to be 0.3 seconds, the displacement stability to be 0.15mm, the strip micro-vibration frequency to be 7Hz, and the energy concentration to be 15%. Next, the degree of deviation is calculated. For example, the percentage deviation of each indicator from the ideal value can be calculated: tension fluctuation amplitude deviation is 60%, tension response speed deviation is 50%, displacement stability deviation is 50%, and strip micro-vibration frequency deviation is 40% (assuming the energy concentration also deviates proportionally). Based on these degrees of deviation, the system performance level can be determined. For example, a comprehensive deviation index can be set, or each indicator can be rated separately based on its degree of deviation. If the overall deviation exceeds a certain threshold, the system performance level is judged as "average" or "poor"; if the deviation is small, it is judged as "good" or "excellent". In this example, since all indicators have significant deviations, the system performance level may be determined as "average", indicating that the system has some room for optimization. Through this quantitative evaluation, it is possible to clearly identify which performance indicators need to be adjusted and optimized first, thereby guiding subsequent parameter adjustment strategies.

[0097] Furthermore, step S4 includes: S41: Based on the operating status and system performance level, determine the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor 21 from the preset parameter mapping table. S42: The proportional gain, integral gain, derivative gain, and torque feedforward are used together as the torque control parameters of the linear servo motor 21, and the speed feedforward is used as the speed correction parameter of the winding servo motor.

[0098] Specifically, the aforementioned operating status and system performance level refer to the comprehensive results obtained after evaluating the tension fluctuation amplitude, tension response speed, displacement stability, and the frequency of minor vibrations in the strip, used to represent the current working condition and control effect of the coiler 1. The preset parameter mapping table can be understood as a data structure storing multiple sets of control parameters, where each set of parameters corresponds to a specific operating status and system performance level. This mapping table can be a two-dimensional array, a hash table, or a database. Its index can be a combination of operating status and system performance level, while the corresponding values ​​are the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor 21.

[0099] The proportional gain, integral gain, and derivative gain of the PID controller are core parameters in the classic PID control algorithm, used to adjust the controller's response speed, eliminate steady-state error, and suppress overshoot, respectively. The torque feedforward and speed feedforward of the linear servo motor 21 are important components of feedforward control. They are used to apply compensation control quantities in advance, based on known system models or experience, before disturbances occur in the system, thereby improving the system's response speed and anti-interference capability. For example, the torque feedforward can pre-adjust the output torque of the linear servo motor 21 according to changes in winding speed and winding diameter, while the speed feedforward can pre-adjust the speed of the winding servo motor according to changes in winding speed.

[0100] The solution proposed in this application solves the problem of insufficient adaptability of traditional fixed parameters or simple calculation methods under complex working conditions by introducing a preset parameter mapping table and dynamically selecting or determining control parameters based on the operating status and system performance level obtained from real-time evaluation.

[0101] Furthermore, step S41 includes: S411: During the operation of winding machine 1, continuously acquire the operating status and system performance level; S412: Determine whether the system performance level is lower than the preset optimization target; S413: If the system performance level is lower than the optimization target, the parameter set corresponding to the current running state in the parameter mapping table shall be adjusted according to the degree of deviation between the system performance level and the optimization target. S414: Update the adjusted parameter set to the parameter mapping table, and determine the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor 21 from the updated parameter mapping table.

[0102] Specifically, in step S411, the operating state and system performance level are continuously obtained based on the evaluation results of step S3 above. This means that the system monitors the operation of the winding machine 1 in real time, including the start-up state, stable state, transition state, and abnormal state, and evaluates its performance level. In step S412, the preset optimization target can be a specific performance indicator, such as tension fluctuation amplitude being less than a certain threshold, tension response speed being faster than a certain time, and displacement stability root mean square error being less than a certain value. When the system performance level is lower than this optimization target, it indicates that the current control parameters may no longer be the optimal choice and need to be adjusted. In step S413, the parameter mapping table is a lookup table that stores the PID parameters (proportional gain, integral gain, derivative gain) and feedforward quantities (torque feedforward quantity, speed feedforward quantity) corresponding to different operating states and system performance levels. When the system performance level is lower than the optimization target, the adjustment amount of the parameter set under the current operating state is calculated based on the degree of deviation between the performance level and the optimization target, such as the magnitude and duration of the deviation. This adjustment can be incremental or based on a certain optimization algorithm (such as gradient descent, genetic algorithm, etc.). In step S414, the adjusted parameter set is written to or overwritten in the parameter mapping table, thereby realizing the dynamic updating of the parameter mapping table. Subsequently, the system will re-search and determine the parameters used to control the linear servo motor 21 and the take-up servo motor from this updated parameter mapping table, based on the current operating status and system performance level.

[0103] As a specific implementation, assuming the winding machine 1 is in a stable operating state, its tension fluctuation amplitude is consistently higher than the preset optimization target. For example, the target fluctuation amplitude is ±0.5N, but the actual fluctuation amplitude is ±0.8N. The system continuously obtains information in step S411 that it is currently in a "stable state" and the "system performance level" is lower than the optimization target. In step S412, it is determined that the performance is indeed lower than the optimization target. Subsequently, in step S413, the system fine-tunes the PID proportional gain, integral gain, derivative gain, torque feedforward, and speed feedforward corresponding to the "stable state" in the parameter mapping table based on the 0.3N deviation. For example, the proportional gain may be slightly increased to improve the response speed, while the integral gain is adjusted to eliminate steady-state error. These adjusted parameter sets are updated in the parameter mapping table in step S414. In the next control cycle, the system will obtain new parameters from this updated parameter mapping table to control the linear servo motor 21, thereby potentially reducing the tension fluctuation amplitude to within the optimization target range. This process can continue, allowing the parameter mapping table to learn and optimize over time and as operating conditions change, ensuring that the tension control system is always in a high-performance operating state.

[0104] Furthermore, step S413 includes: S4131: Record the operating status, system performance level, degree of deviation, and historical parameter adjustment results to build a historical adjustment database; S4132: Based on the current operating status and system performance level, retrieve similar historical data from the historical adjustment database; S4133: Based on the current degree of deviation and the retrieved similar historical data, adjust the parameter set corresponding to the current running state in the parameter mapping table.

[0105] Specifically, in step S4131, during the operation of the winding machine 1, the system continuously records key operating parameters, including the current operating status (e.g., startup, stable, transitional, or abnormal state), the real-time assessed system performance level, the deviation between the system performance level and the optimization target, and the specific adjustment results obtained after each parameter adjustment. This data is stored in a structured manner to construct a historical adjustment database. This database can be implemented as a relational database, a non-relational database, or a file system, with the aim of accumulating rich historical experience data to provide a basis for subsequent intelligent adjustments.

[0106] In step S4132, when parameter adjustments are required, the system uses the current operating status of the winding machine 1 and the real-time assessed system performance level as query criteria to search the existing historical adjustment database. The goal of the search is to find the historical data record most similar to the current operating condition. Similarity judgment can be based on various algorithms, such as Euclidean distance or cosine similarity, to ensure that the retrieved historical data accurately reflects the system behavior and adjustment effects similar to the current situation.

[0107] In practical applications, in step S4133, after retrieving similar historical data, the system comprehensively analyzes the current deviation level with the deviation levels and corresponding adjustment results recorded in these similar historical data. For example, weighted averaging, machine learning prediction, or expert system rules can be used to combine historical experience with the current situation, thereby generating a more accurate and effective parameter adjustment strategy. Specifically, if a weighted averaging method is used, the system can assign different weights based on factors such as the significance of the adjustment effect in the historical data and the relevance of the adjustment time (where relevance refers to how recently the historical adjustment data was recorded. A high relevance data point means it occurred in the very recent past (e.g., a few minutes or hours ago); while a low relevance data point may have been recorded a few days or months ago). Then, these historical adjustment results are weighted and averaged to obtain a preliminary parameter adjustment suggestion.

[0108] Specifically, this weighted averaging process is an intelligent decision-making mechanism designed to comprehensively utilize historical experience while prioritizing the most effective and relevant experiences. Its working principle is as follows: First, when parameter adjustments are required, the system will retrieve a set of historical data with similar operating conditions from the historical adjustment database based on the current operating status and performance level.

[0109] The system calculates a comprehensive weight value for each retrieved historical data point. This weight value is dynamically generated based on at least two factors, such as: A historical adjustment that brought about a significant performance improvement (such as a 50% reduction in tension fluctuations) will receive a higher weight than an adjustment that only brought minor improvements.

[0110] Compared to last month's adjusted data, yesterday's adjustments will receive a higher weight.

[0111] The system then performs a weighted average calculation. It multiplies the parameter adjustment result (e.g., "proportional gain increased by 5%) in each historical data point by its corresponding weight value. Then, it sums all these weighted adjustments and divides by the sum of all weight values.

[0112] The final result of this calculation is a preliminary parameter adjustment suggestion. This suggested value (e.g., "increase the proportional gain by 4.8%) will be more inclined towards historical adjustment schemes that have proven effective in recent times, thus avoiding being misled by outdated or invalid historical data.

[0113] If machine learning is used for prediction, a regression model can be pre-trained. The inputs are the operating status, system performance level, and degree of deviation; the outputs are the adjustments to the PID parameters and feedforward. When adjustments are needed, the current operating data is input into the model, and the model will predict the specific parameter adjustments. For example, the model might predict that under the current operating conditions, the proportional gain should increase by 5.5%, and the integral gain should decrease by 2.1%.

[0114] If an expert system rule-based approach is used, a series of rules can be preset, such as "If the system is in a transitional state and the tension fluctuation amplitude deviates by more than 20%, then increase the proportional gain by 5% and decrease the integral gain." The system matches the corresponding rules based on the current operating conditions and executes the parameter adjustment operations defined in the rules.

[0115] This approach aims to avoid blind adjustments, instead optimizing the parameter set corresponding to the current operating state in the parameter mapping table based on past successes and lessons learned. The parameter set typically includes the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor 21.

[0116] Furthermore, step S414 includes: S4141: Using the running status and system performance level as indexes, look up the parameter value in the updated parameter mapping table; S4142: Interpolate the parameter values ​​to obtain the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor 21.

[0117] Specifically, in step S4141, the operating status and system performance level are used as indexes for the parameter mapping table. The parameter mapping table can be constructed as a multi-dimensional lookup table, where one dimension corresponds to different operating states (e.g., startup, stable, transitional, abnormal states), and another dimension or multiple dimensions correspond to different ranges or specific values ​​of the system performance level. By inputting the current operating status and system performance level into this mapping table, one or more preset parameter sets closest to the current operating condition can be quickly located, thus obtaining preliminary parameter values.

[0118] In step S4142, interpolation calculations are performed on the obtained parameter values. Interpolation calculation is a mathematical method used to estimate the values ​​of unknown data points between known data points. For example, when the system performance level is between two adjacent preset performance levels in the parameter mapping table, linear interpolation, polynomial interpolation, or spline interpolation can be used to calculate the more accurate proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor 21, based on the parameter values ​​corresponding to these two preset performance levels. The purpose is to achieve continuous and refined adjustment of control parameters based on the discrete parameter mapping table, so as to better adapt to the continuously changing operating conditions in actual operation.

[0119] This application's solution solves the problem of parameter inaccuracy that may arise from traditional discrete parameter lookup by introducing a lookup mechanism indexed by operating status and system performance level, combined with interpolation calculation. The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A tension structure for a linear servo motor, characterized in that, A linear servo motor tensioning structure is installed on the winding machine to adjust the tension of the strapping during the winding process, ensuring constant tension during winding. This structure includes at least the following: A linear servo motor includes at least a stator, a mover, and a linear motion module; the stator includes a high-precision magnetic levitation slide rail, on which a high-precision magnetic scale is configured; the mover includes a magnetic slider, which is movably mounted on the high-precision magnetic levitation slide rail and reciprocates along the high-precision magnetic levitation slide rail; the linear motion module includes at least a driver, which drives the magnetic slider to run on the high-precision magnetic levitation slide rail. A slider guide wheel is mounted on the magnetic slider. The packing strap moves with the magnetic slider through the slider guide wheel, thereby maintaining constant tension control. Tension control electrical control module: including at least a PLC controller, the PLC controller running a tension control program, the tension control program calculating the torque of the linear servo motor and the speed of the winding servo motor based on the slider displacement information of the slider guide wheel detected by the high-precision magnetic scale and the motor torque information of the linear servo motor, thereby controlling the tension balance of unwinding and winding.

2. A control method for a tension structure of a linear servo motor, characterized in that, The control method, applied to the linear servo motor tension structure as described in claim 1, includes the following steps: S1: Obtain the operating data of the linear servo motor tension structure, the operating data including at least motor torque information and slider displacement information; S2: Calculate the tension fluctuation amplitude and tension response speed based on the motor torque information; calculate the displacement stability of the slider guide wheel based on the slider displacement information; and identify the micro vibration frequency of the strip based on the motor torque information or the slider displacement information. S3: Based on the tension fluctuation amplitude, the tension response speed, the displacement stability, and the micro-vibration frequency of the strip, evaluate the performance of the tension control system and the dynamic characteristics of the strip, and obtain the evaluation results; S4: Based on the evaluation results, the torque control parameters of the linear servo motor and the speed correction parameters of the winding servo motor are calculated using the PID algorithm; S5: Control the linear servo motor to run according to the torque control parameters, and control the winding servo motor to run according to the speed correction parameters.

3. The control method for a linear servo motor tension structure according to claim 2, characterized in that, Step S2 includes: S21: Based on the motor torque information, obtain the strip tension data and calculate the standard deviation of the strip tension data as an indicator of the tension fluctuation amplitude; S22: Record the time required from the issuance of the tension control command to the time when the strip tension data reflected by the motor torque information reaches the preset percentage of the new target value, as an indicator of the tension response speed; S23: Based on the slider displacement information, obtain the slider guide wheel displacement and calculate the root mean square error of the slider guide wheel displacement as an indicator of displacement stability. S24: Perform spectrum analysis on the motor torque information or the slider displacement information to identify the frequency components with concentrated energy and obtain the micro vibration frequency of the strip.

4. The control method for a linear servo motor tension structure according to claim 2, characterized in that, Step S3 includes: S31: Define multiple operating states, including startup state, stable state, transition state and abnormal state; S32: Set an evaluation threshold for the operating state; S33: Based on the tension fluctuation amplitude, the tension response speed, the displacement stability, and the micro-vibration frequency of the strip, determine the current operating status of the winding machine according to the evaluation threshold; S34: Assess the system performance level of the winding machine under its current operating condition; S35: The operating status and the system performance level are used as the evaluation results.

5. The control method for a linear servo motor tension structure according to claim 4, characterized in that, Step S33 includes: S331: If the tension fluctuation exceeds its corresponding preset abnormal threshold, the winding machine is determined to be in an abnormal state; otherwise, it is not in an abnormal state. S332: If not in an abnormal state, obtain the winding speed of the winding machine. If the winding speed is lower than the preset start-up completion speed and the tension response speed is higher than the preset response threshold, it is determined to be in the start state; otherwise, it is not in the start state. S333: If not in the start state, determine whether any of the following indicators exceeds the corresponding preset stability threshold: tension fluctuation amplitude, displacement stability, and strip micro-vibration frequency. If it exceeds the corresponding preset stability threshold but does not reach the corresponding preset abnormal threshold, determine that the winding machine is currently in a transition state; if it does not exceed the corresponding preset stability threshold, determine that the winding machine is currently in a stable state.

6. The control method for a linear servo motor tension structure according to claim 5, characterized in that, Step S34 includes: S341: When the system is in a non-abnormal state, a set of ideal performance reference thresholds is preset for the current operating state of the winding machine; S342: Calculate the tension fluctuation amplitude, the tension response speed, the displacement stability, and the deviation of the micro-vibration frequency of the strip from the ideal performance reference threshold; S343: Determine the system performance level based on the degree of deviation.

7. The control method for a linear servo motor tension structure according to claim 4, characterized in that, Step S4 includes: S41: Based on the operating status and the system performance level, determine the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor, from the preset parameter mapping table. S42: The proportional gain, the integral gain, the differential gain, and the torque feedforward are used together as the torque control parameters of the linear servo motor, and the speed feedforward is used as the speed correction parameter of the winding servo motor.

8. The control method for a linear servo motor tension structure according to claim 7, characterized in that, Step S41 includes: S411: During the operation of the winding machine, the operating status and the system performance level are continuously acquired; S412: Determine whether the system performance level is lower than the preset optimization target; S413: If the system performance level is lower than the optimization target, then the parameter set corresponding to the current operating state in the parameter mapping table is adjusted according to the degree of deviation between the system performance level and the optimization target; S414: Update the adjusted parameter set to the parameter mapping table, and determine the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor from the updated parameter mapping table.

9. The control method for a linear servo motor tension structure according to claim 8, characterized in that, Step S413 includes: S4131: Record the operating status, system performance level, degree of deviation, and historical parameter adjustment results to build a historical adjustment database; S4132: Based on the current operating status and the system performance level, retrieve similar historical data from the historical adjustment database; S4133: Based on the current degree of deviation and the retrieved similar historical data, adjust the parameter set corresponding to the current running state in the parameter mapping table.

10. The control method for a linear servo motor tension structure according to claim 8, characterized in that, Step S414 includes: S4141: Using the operating status and the system performance level as indexes, search in the updated parameter mapping table to obtain the parameter value; S4142: Interpolate the parameter values ​​to obtain the proportional gain, integral gain, and derivative gain of the PID controller, as well as the torque feedforward and speed feedforward of the linear servo motor.

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