Tension servo control method and system applicable to multiple scenes

Abstract

The invention discloses a tension servo control method and system suitable for multiple scenes, and belongs to the technical field of tension servo control. Comprising the following steps: respectively installing a tension sensor and an encoder at specified positions based on structural characteristics of an execution mechanism, simultaneously acquiring a pressure signal # imgabs0 # of the tension sensor and a pulse signal generated by the encoder at a specified frequency, and converting the pressure signal # imgabs1 # into a digital signal to obtain a current tension value # imgabs2 #; based on the pulse signal, rotating speed conversion is carried out to obtain the current rotating speed # imgabs3 # of the tension roller, the current rotating speed # imgabs4 # is combined, a rolling diameter calculation formula is utilized to obtain the current rolling diameter # imgabs5 #, PID parameters are dynamically adjusted by adopting the current rolling diameter # imgabs6 #, and a self-adaptive fuzzy algorithm is constructed; and the current tension value # imgabs7 # and the current rotating speed # imgabs8 # serve as input, and a control variable # imgabs9 # is obtained through calculation. The tension control system is different from a tension control system based on a PLC in the prior art, signal identification and data output are directly carried out through the encoder, the PLC scanning period is omitted, and the control efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of tension servo control, and in particular relates to a tension servo control method and system applicable to multiple scenarios. Background Art

[0002] In today's industrial automation field, especially in many industrial production processes involving material processing, transmission and winding, tension control plays a vital role. The stability of tension control is directly related to product quality, production efficiency, and the safety and reliability of the production process. For example, in industries such as printing, papermaking, textiles, film production, metal strip processing, and cable manufacturing, precise tension control can ensure that products avoid quality problems such as material stretching, breaking, wrinkling, and uneven winding during the production process, and also help improve the operating efficiency and service life of production equipment.

[0003] Traditional tension control systems widely use PLC (Programmable Logic Controller) PID (Proportional-Integral-Derivative) control algorithm is used to adjust the tension. In this control mode, PLC As the core controller, it is responsible for receiving feedback signals from the tension sensor and then adjusting the tension according to the preset PID The control algorithm calculates the corresponding control instructions and sends them to the actuators (such as motors, brakes, clutches, tension adjustment mechanisms, etc.) to achieve tension adjustment.

[0004] However, PLC Its own working mechanism has certain limitations, the most prominent of which is its scanning cycle. PLC The scanning cycle is PLC The time required for a complete input sampling, program execution, and output refresh operation of the entire program. In the case of relatively slow industrial production speed, this PLC The tension control method can meet the basic needs of tension control to a certain extent. However, with the development of industry and technological progress, more and more production scenarios require higher production speeds, such as high-speed printing machines, high-speed film winding machines, high-speed metal strip rolling mills, etc. Their production speeds have been greatly improved, which puts forward higher requirements on the timeliness and stability of tension control. Summary of the invention

[0005] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a tension servo control method and system applicable to multiple scenarios.

[0006] The present invention adopts the following technical solution: a tension servo control method applicable to multiple scenarios, comprising the following steps: Select the corresponding actuator according to industrial needs, and pre-set the mechanism operation parameters and target tension value based on the actuator and initial value of coil diameter ; Based on the structural characteristics of the actuator, the tension sensor and encoder are installed at the specified positions respectively, and the following steps are performed during operation: Simultaneously collect the pressure signal of the tension sensor at a specified frequency and the pulse signal generated by the encoder, the pressure signal Convert into digital signal to get the current tension value ,in t is the time node for collecting pulse signals; The pulse signal is converted into a speed to obtain the current speed of the tension roller in the actuator. , use the coil diameter calculation formula to get the current coil diameter ; Using the current roll diameter Dynamic PID Parameter adjustment, and build an adaptive fuzzy algorithm; the current tension value and current speed The control variables are calculated as input , according to the control variable Acting on the actuator to achieve high-precision control of tension.

[0007] In a further embodiment, the actuator comprises at least: an actuator based on torque adjustment and an actuator based on angle adjustment; The tension servo control method further comprises the following steps: According to the type of regulation of the actuator, select the appropriate control variable conversion mode; the conversion mode includes at least: a speed conversion mode and an angle conversion mode.

[0008] In a further embodiment, the pressure signal Convert into digital signal to get the current tension value The conversion steps are as follows: Create a pressure signal data set. Each time a pressure signal is collected, it is updated to the pressure signal data set according to the time series, expressed as: , corresponding to the digital signal data set ; The digital processing model is established using the time series analysis method and expressed using the following formula: ; In the formula, Indicates the time node is t The predicted value of the digital signal when The time node is t -1 digital signal measurement value, is the ARIMA function; Introducing sensor correction factors , based on the digital processing model, the corrected current digital signal is obtained It is expressed as: , where The time node is t- A digital signal of 1; Use the following conversion formula to get the current tension value : ; In the formula, , and These are calibration factors.

[0009] In a further embodiment, the current speed The calculation process is as follows: Introducing temperature compensation coefficient : , T is the real-time temperature during transportation, is the reference temperature, is the temperature compensation coefficient; Then, use the following formula to calculate the current speed : ; In the formula, Indicates the time interval is The number of pulses collected, is the encoder error coefficient, N The number of pulses generated per revolution.

[0010] In a further embodiment, the coil diameter calculation formula is expressed as follows: ; in, and are the coil diameters at time nodes t and t-1 respectively, is the material thickness, and They are the positions of the reel / reel at time nodes t and t-1 respectively.

[0011] In a further embodiment, the construction process of the adaptive fuzzy algorithm is as follows: The tension error is calculated using the following formula: : ;in, is the curl diameter function, ; Based on the current roll diameter , use the following formula to PID Parameters are adjusted dynamically: ; In the formula, , , It is basic PID parameter, , and About Function of The calculation formula of the adaptive fuzzy algorithm is as follows: ; In the formula, is the control variable, It is the tension error dead zone.

[0012] In a further embodiment, the conversion formula of the speed conversion mode is as follows: ; In the formula, is the speed variable, is the torque coefficient, is the moment of inertia, is the damping coefficient.

[0013] In a further embodiment, the conversion formula of the angle conversion mode is as follows: ;in, is the angle variable, i is the transmission ratio, They are the maximum rotation angle and the minimum rotation angle of the transmission mechanism respectively.

[0014] In a further embodiment, the function , and Set to the same or different as required.

[0015] A tension servo control system applicable to multiple scenarios, used to implement the tension servo control method as described above, comprising: The actuator is configured according to industrial needs; the actuator includes at least: an actuator based on torque adjustment and an actuator based on angle adjustment; The encoder and tension sensor are installed at the designated position of the actuator; The first module is configured to simultaneously collect the pressure signal of the tension sensor at a specified frequency and the pulse signal generated by the encoder, the pressure signal Convert into digital signal to get the current tension value ,in t is the time node for collecting pulse signals; The second module is configured to convert the pulse signal into a speed to obtain the current speed of the tension roller in the actuator. , use the coil diameter calculation formula to get the current coil diameter ; The third module is configured to utilize the current roll diameter Dynamic PID Parameter adjustment, and build an adaptive fuzzy algorithm; the current tension value and current speed The control variables are calculated as input , according to the control variable Acting on the actuator to achieve high-precision control of tension.

[0016] Beneficial effects of the present invention: The present invention is different from the prior art based on PLC The tension control system directly recognizes signals and outputs data through the encoder, eliminating the need for PLC The scanning cycle improves control efficiency. At the same time, actuators based on torque regulation or angle regulation can be selected according to different industrial needs, which is suitable for a variety of industrial scenarios and improves the versatility and flexibility of the system. For example, in some occasions where high torque control accuracy is required, actuators based on torque regulation can be selected; and in some scenarios where angle control is more sensitive, actuators based on angle regulation can be selected.

[0017] In the data processing process, by simultaneously collecting the pressure signal of the tension sensor and the pulse signal of the encoder at a specified frequency, the tension and speed information of the system can be obtained in real time. The pressure signal is modeled and corrected using time series analysis, which effectively improves the accuracy of tension value measurement and reduces the impact of sensor errors on control accuracy.

[0018] The PID parameters are adjusted dynamically using the current roll diameter, so that the controller can better adapt to the characteristic changes of the system under different roll diameters. Combining the tension error and dead zone settings, an adaptive fuzzy algorithm is constructed, which not only ensures the rapid response of the system when the error is large, but also avoids frequent adjustments when the error is small, thereby achieving high-precision control of the tension. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a tension servo control method applicable to multiple scenarios in Example 1. DETAILED DESCRIPTION

[0020] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0021] Example 1 Due to the influence of the scanning cycle of PLC, it is difficult to meet the requirements of fast-speed places. In order to meet the requirements of fast applications, this embodiment discloses a tension servo control method applicable to multiple scenarios, including the following steps: like Figure 1 As shown, the corresponding actuator is selected according to industrial needs, and the mechanism operation parameters and target tension value are pre-set based on the actuator. and initial value of coil diameter ; Based on the structural characteristics of the actuator, the tension sensor and encoder are installed at the specified positions respectively, and the following steps are performed during operation: Simultaneously collect the pressure signal of the tension sensor at a specified frequency and the pulse signal generated by the encoder, the pressure signal Convert into digital signal to get the current tension value ,in t is the time node for collecting pulse signals; The pulse signal is converted into a speed to obtain the current speed of the tension roller in the actuator. , use the coil diameter calculation formula to get the current coil diameter ; Using the current roll diameter Dynamic PID Parameter adjustment, and build an adaptive fuzzy algorithm; the current tension value and current speed The control variables are calculated as input , according to the control variable Acting on the actuator to achieve high-precision control of tension.

[0022] In this embodiment, taking the textile industry as an example, the yarn winding machine adopts an actuator based on torque regulation. This is because the yarn needs to maintain a constant tension during the winding process to prevent the yarn from being too loose or too tight, which affects the quality of the yarn and the winding effect. The torque regulation can accurately control the rotational force of the winding shaft to ensure uniform tension of the yarn. Correspondingly, the parameters of the conveying equipment need to consider the type and speed of the yarn or fabric. For the transportation of fine yarn, the conveying speed may be faster and needs to be set to tens to hundreds of meters per minute; for heavy fabrics, the conveying speed will be relatively slow, possibly only a few meters per minute. At the same time, the parameters of the actuator such as the guide roller spacing and guide roller diameter also need to be adjusted according to the thickness of the yarn or fabric.

[0023] In other embodiments, during high-speed wire transmission, the wire needs to be accurately guided to different processing equipment or processing units, and the actuator based on angle adjustment can be a guide wheel or guide arm with a power source. For example, in a multi-station wire processing production line, a guide arm is used to adjust the conveying angle so that the wire can be guided to the corresponding processing station according to different processing procedures, ensuring that the transmission path of the wire is accurate. Correspondingly, the parameters of the conveying equipment need to consider the angle range, speed, torque, etc.

[0024] In summary, the actuators include at least: an actuator based on torque adjustment and an actuator based on angle adjustment. Correspondingly, the tension servo control method further includes the following steps: according to the adjustment type of the actuator, selecting a suitable control variable conversion mode; the conversion mode includes at least: a speed conversion mode and an angle conversion mode.

[0025] In this embodiment, the pressure signal The main purpose of not filtering is to ensure the authenticity of the signal. In other words, not filtering can ensure that the received pressure signal It is the most original signal, without any information lost due to filtering operations. In some cases, even short pressure fluctuations may contain important information. For example, in high-speed wire processing, a short pressure spike may mean an instantaneous tension change in the wire, which may be caused by the unevenness of the wire, slight vibration of the equipment, or other transient phenomena. If the signal is filtered, this information may be smoothed out, thereby masking important information that may affect the quality of the final product.

[0026] Therefore, this embodiment will be the pressure signal Direct conversion, but in actual industrial environments, factors such as ambient temperature, humidity, vibration, etc. will change over time, and these factors will affect the performance of the tension sensor.

[0027] Therefore, the pressure signal disclosed in this embodiment The transformation method introduces the factor of aging, and the specific steps are as follows: Create a pressure signal data set. Each time a pressure signal is collected, it is updated to the pressure signal data set according to the time series, expressed as: , corresponding to the digital signal data set ; The tension sensor is modeled using time series analysis and expressed using the following formula: ; In the formula, Represents the predicted value of the digital signal at time node t, is the digital signal measurement value at time node t-1, The ARIMA function is the autoregressive moving average model. Introducing sensor correction factors , the corrected current digital signal based on the digital processing model is expressed as: .

[0028] Finally, the current tension value is obtained using the following conversion formula: : ; In the formula, , and These are calibration factors.

[0029] By adopting the above technical solution and modeling the tension sensor through time series analysis, the digital signal prediction value of the current time node can be predicted based on the historical digital signal measurement value. When the tension change has a certain regularity, the prediction can serve as an important reference for subsequent signal processing.

[0030] At the same time, the sensor correction factor is introduced After obtaining the corrected digital signal, the current measurement value is corrected according to the difference between the predicted value and the digital signal measurement value at the previous moment. The measurement error caused by the performance fluctuation of the tension sensor itself, environmental interference and other factors is effectively reduced, and the accuracy of the measurement result is improved. For example, in some tension control systems that run continuously for a long time, such as papermaking or metal strip processing, the tension sensor may be affected by factors such as temperature, humidity, and mechanical vibration. Through this correction, the measurement signal can be dynamically adjusted, so that the measurement result is closer to the real tension signal, thereby improving the measurement accuracy of the final tension value.

[0031] In this embodiment, the current speed The calculation process is as follows: Introducing temperature compensation coefficient : , T is the real-time temperature during transportation, is the reference temperature, is the temperature compensation coefficient; Then, use the following formula to calculate the current speed : ; In the formula, Indicates the time interval is The number of pulses collected, is the encoder error coefficient, N The number of pulses generated per revolution.

[0032] Using the above technical features, the time interval is comprehensively considered. The number of pulses collected within and the number of pulses generated per revolution N , accurately converting the pulse signal generated by the encoder into speed information. By measuring and calculating the number of pulses, the problem of inaccurate or impractical speed information directly obtained from the sensor is solved, especially in some complex industrial environments, where direct speed measurement may be affected by equipment structure, space limitations or costs.

[0033] Since the encoder may have errors during the manufacturing and installation process, the encoder error coefficient is used to quantify and compensate for them, so that the calculated speed is closer to the actual speed, avoiding speed measurement deviation caused by encoder error, thereby improving the accuracy of speed calculation.

[0034] In the industrial production process, temperature changes will affect the performance of the encoder, and thus affect the speed measurement. The temperature compensation coefficient solves the problem of inaccurate speed measurement caused by temperature changes. For example, in the metal strip processing in a high temperature environment or the cable manufacturing process in a low temperature environment, the temperature change will affect the electrical characteristics of the encoder. Temperature compensation can correct this effect and ensure the speed measurement accuracy at different temperatures.

[0035] In a further embodiment, the coil diameter calculation formula is expressed as follows: ; in, and are the coil diameters at time nodes t and t-1 respectively, is the material thickness, and They are the positions of the reel / reel at time nodes t and t-1 respectively.

[0036] In many tension control industrial applications, the physical characteristics of the system vary with the roll diameter. For example, during the winding process, as the roll diameter increases or decreases, the system's inertia, friction, elasticity and other characteristics will change significantly, making it difficult to achieve stable and accurate tension control with fixed PID parameters.

[0037] Therefore, this embodiment is suitable for direct control and multiple scenarios, and the construction process of the adaptive fuzzy algorithm is as follows: Calculate tension error : ;in, is the curl diameter function, ; According to the current roll diameter Use the following formula to PID Parameters are adjusted dynamically: ; In the formula, , , It is basic PID parameter, , and About function.

[0038] The calculation formula of the adaptive fuzzy algorithm is as follows: ; In the formula, is the control variable, is the tension error dead zone, , is the basic error dead zone, is the coefficient.

[0039] Compared with traditional PLC control technology, the steady-state error may be difficult to eliminate due to unreasonable setting of the integral term. It helps to eliminate steady-state errors. After the system has been running for a period of time, as long as the tension error If the integral term persists, it will continue to accumulate, generating enough control to adjust the tension to near the target value, thus improving the control accuracy of the system. At the same time, due to the dynamic adjustment of the PID parameters, the effect of the integral term will be adjusted according to the different winding diameters, thus avoiding the problem of integral saturation or poor effect caused by changes in winding diameter.

[0040] In addition, when approaching the target tension, traditional PLC control may frequently adjust due to small tension errors, causing system instability and energy waste. Therefore, the tension error dead zone is introduced. This problem can be avoided when When the control variable , adjustment will only be made when the tension error exceeds the dead zone, which is of great significance for some systems with restrictions on adjustment frequency or systems that need energy saving.

[0041] Finally, for different systems and different winding processes, adjust , and The specific function of makes the algorithm adapt to different working conditions and system characteristics, improving the adaptability and versatility of the system. , and Set to be the same or different according to the requirements. For example, select one or a combination of linear function, inverse proportional function, polynomial function, exponential function, logarithmic function. Whether it is a large or small winding diameter, fast winding speed or slow winding speed, the algorithm can adjust the control strategy according to the actual situation to achieve better control performance.

[0042] Taking into account the different adjustment parameters of the actuator, the output of specific variables is made based on the structural characteristics of the actuator. For example, when the actuator is an actuator based on torque regulation, the conversion formula of the speed conversion mode is as follows: ; In the formula, is the speed variable, is the torque coefficient, is the moment of inertia, is the damping coefficient.

[0043] Alternatively, when the actuator is an actuator based on angle adjustment, the conversion formula of the angle conversion mode is as follows: ;in, is the angle variable, i is the transmission ratio, They are the maximum rotation angle and the minimum rotation angle of the transmission mechanism respectively.

[0044] Example 2 In order to implement the tension servo control method applicable to multiple scenarios described in Example 1, this embodiment discloses a tension servo control system applicable to multiple scenarios, including: The actuator is configured according to industrial needs; the actuator includes at least: an actuator based on torque adjustment and an actuator based on angle adjustment; The encoder and tension sensor are installed at the designated position of the actuator; The first module is configured to simultaneously collect the pressure signal of the tension sensor at a specified frequency and the pulse signal generated by the encoder, the pressure signal Convert into digital signal to get the current tension value ,in t is the time node for collecting pulse signals; The second module is configured to convert the pulse signal into a speed to obtain the current speed of the tension roller in the actuator. , use the coil diameter calculation formula to get the current coil diameter ; The third module is configured to utilize the current roll diameter Dynamic PID Parameter adjustment, and build an adaptive fuzzy algorithm; the current tension value and current speed The control variables are calculated as input , according to the control variable Acting on the actuator to achieve high-precision control of tension.

[0045] In a further embodiment, for an actuator based on torque regulation, taking a servo motor as an example, an encoder is installed at the shaft end of the motor to measure the rotation angle, speed and position information of the motor shaft. Combined with the application scenario of a printing press, a tension sensor is installed on the unwinding roller or the winding roller (depending on the specific needs). During the printing process, the paper or film material needs to maintain a certain tension to ensure the printing quality.

[0046] In another embodiment, for an actuator based on angle adjustment, a guide arm is taken as an example. An encoder is installed on the rotating shaft of the guide arm and is coaxially connected to the rotating shaft to directly measure the rotation angle of the guide arm. For another example, the guide arm is driven by a motor, and the encoder can also be installed on the motor shaft to calculate the rotation angle of the guide arm through the transmission ratio. Correspondingly, a tension sensor is installed in the front and rear positions where the material contacts the guide arm, such as near a guide wheel or roller near the guide arm, to monitor the tension changes of the material when passing through the guide arm.

Claims

1. A tension servo control method applicable to multiple scenarios, characterized in that: The following steps are involved: Select the corresponding actuator according to industrial needs, and pre-set the mechanism operation parameters and target tension value based on the actuator and initial value of coil diameter ; Based on the structural characteristics of the actuator, the tension sensor and encoder are installed at the specified positions respectively, and the following steps are performed during operation: Simultaneously collect the pressure signal of the tension sensor at a specified frequency and the pulse signal generated by the encoder, the pressure signal Convert into digital signal to get the current tension value ,in t is the time node for collecting pulse signals; The pulse signal is converted into a speed to obtain the current speed of the tension roller in the actuator. , use the coil diameter calculation formula to get the current coil diameter ; Using the current roll diameter Dynamic PID Parameter adjustment, and build an adaptive fuzzy algorithm; the current tension value and current speed The control variables are calculated as input , according to the control variable Acting on the actuator to achieve high-precision control of tension.

2. A tension servo control method applicable to multiple scenarios according to claim 1, characterized in that: The actuator at least includes: an actuator based on torque adjustment and an actuator based on angle adjustment; The tension servo control method further comprises the following steps: According to the type of regulation of the actuator, select the appropriate control variable conversion mode; the conversion mode includes at least: a speed conversion mode and an angle conversion mode.

3. The tension servo control method applicable to multiple scenarios according to claim 1 is characterized in that: The pressure signal Convert into digital signal to get the current tension value The conversion steps are as follows: Create a pressure signal data set. Each time a pressure signal is collected, it is updated to the pressure signal data set according to the time series, expressed as: , corresponding to the digital signal data set ; The digital processing model is established using the time series analysis method and expressed using the following formula: ; In the formula, Indicates the time node is t The predicted value of the digital signal when The time node is t -1 digital signal measurement value, is the ARIMA function; Introducing sensor correction factors , based on the digital processing model, the corrected current digital signal is obtained It is expressed as: ； Use the following conversion formula to get the current tension value : ; In the formula, , and These are calibration factors.

4. The tension servo control method applicable to multiple scenarios according to claim 1 is characterized in that: The current speed The calculation process is as follows: Introducing temperature compensation coefficient : , T is the real-time temperature during transportation, is the reference temperature, is the temperature compensation coefficient; Then, use the following formula to calculate the current speed : ; In the formula, Indicates the time interval is The number of pulses collected, is the encoder error coefficient, N is the number of pulses generated per revolution.

5. The tension servo control method applicable to multiple scenarios according to claim 1, characterized in that: The coil diameter calculation formula is expressed as follows: ； in, and are the coil diameters at time nodes t and t-1 respectively, is the material thickness, and They are the positions of the reel / reel at time nodes t and t-1 respectively.

6. The tension servo control method applicable to multiple scenarios according to claim 1, characterized in that: The construction process of the adaptive fuzzy algorithm is as follows: The tension error is calculated using the following formula: : ;in, is the curl diameter function, ; Based on the current roll diameter , use the following formula to PID Parameters are adjusted dynamically: ； In the formula, , , It is basic PID parameter, , and About Function of The calculation formula of the adaptive fuzzy algorithm is as follows: ； In the formula, is the control variable, It is the tension error dead zone.

7. The tension servo control method applicable to multiple scenarios according to claim 2, characterized in that: The conversion formula of the speed conversion mode is as follows: ； In the formula, is the speed variable, is the torque coefficient, is the moment of inertia, is the damping coefficient.

8. The tension servo control method applicable to multiple scenarios according to claim 2, characterized in that: The conversion formula of the angle conversion mode is as follows: ;in, is the angle variable, i is the transmission ratio, They are the maximum rotation angle and the minimum rotation angle of the transmission mechanism respectively.

9. The tension servo control method applicable to multiple scenarios according to claim 6, characterized in that: The function , and Set to the same or different as required.

10. A tension servo control system applicable to multiple scenarios, used to implement the tension servo control method according to any one of claims 1 to 9, characterized in that: include: Actuators, configured according to industrial needs; The actuator at least includes: an actuator based on torque adjustment and an actuator based on angle adjustment; The encoder and tension sensor are installed at the designated position of the actuator; The first module is configured to simultaneously collect the pressure signal of the tension sensor at a specified frequency and the pulse signal generated by the encoder, the pressure signal Convert into digital signal to get the current tension value ,in t is the time node for collecting pulse signals; The second module is configured to convert the pulse signal into a speed to obtain the current speed of the tension roller in the actuator. , use the coil diameter calculation formula to get the current coil diameter ; The third module is configured to utilize the current roll diameter Dynamic PID Parameter adjustment, and build an adaptive fuzzy algorithm; the current tension value and current speed The control variables are calculated as input , according to the control variable Acting on the actuator to achieve high-precision control of tension.

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