A spinning machine spindle speed control method and system

Abstract

The application relates to the technical field of spinning frame rotating speed control, in particular to a spinning frame spindle rotating speed control method and system, which comprises the following steps: collecting the rotating speed and spinning tension of the spinning frame spindle at each moment; determining the tension abnormal significant value of each cycle period; obtaining the deviation significant value of the spindle rotating speed in each cycle period; obtaining the rotating speed state difference value of the spindle in each cycle period; analyzing the correlation degree of the tension abnormal significant value and the rotating speed state difference value of all cycle periods during the operation of the spinning frame; determining the abnormal influence degree of the spindle rotating speed during the operation of the spinning frame; and obtaining the optimal control parameter of the PID controller by using an optimization algorithm, wherein the abnormal influence degree is taken as the weight, the performance index of the PID controller is combined, the fitness function of the optimization algorithm is constructed, and the spindle rotating speed during the next operation of the spinning frame is controlled. Therefore, the stability of the spinning frame spindle rotating speed control is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of spinning frame rotating speed control, in particular to a spinning frame spindle rotating speed control method and system. BACKGROUND

[0002] As the last key process of yarn forming, the production and quality of spun yarn greatly affect the efficiency of a textile mill. During the winding process, the spindle brushless DC motor speed fluctuation is large, which can cause large differences in yarn twist, high unevenness rate, yarn breakage and other problems. Therefore, the spindle speed control is very important to the quality of the yarn.

[0003] The spindle speed should be relatively stable during operation. However, in actual processing, due to the influence of abnormal fluctuations in spun yarn tension and changes in motor parameters, the spindle speed can fluctuate greatly, thereby reducing the quality of spun yarn production. The conventional method usually uses a classic PID controller to adjust the spindle speed, but does not fully consider the disturbance of abnormal fluctuations in tension and spindle speed fluctuations, which makes the setting of the PID controller control parameters have the problems of insufficient adaptability and low precision, so it is difficult to accurately control the spindle within the target speed, and the spindle speed control precision is insufficient, which reduces the quality of spun yarn production. SUMMARY

[0004] To solve the above technical problems, the purpose of the present application is to provide a spinning frame spindle speed control method and system, and the technical solution adopted is as follows:

[0005] In a first aspect, the present application provides a spinning frame spindle speed control method, which comprises the following steps:

[0006] Collecting the speed of the spinning frame spindle at each moment and the spun yarn tension;

[0007] Analyzing the trend of all spun yarn tensions in each cycle period and the symmetry of the spun yarn tension distribution, and determining the tension abnormality significant value of each cycle period in combination with the correlation of the spun yarn tension of each cycle period and its adjacent cycle period;

[0008] Determining the deviation significant value of the spindle speed in each cycle period by the fluctuation degree of the spindle speed in each cycle period and the deviation degree of the spindle speed from the target speed;

[0009] Based on the consistency degree of the deviation significant value of all spindle speeds of the spinning frame in each cycle period, obtaining the speed state difference value of the spindle in each cycle period; analyzing the correlation degree of the tension abnormality significant value and the speed state difference value of all cycle periods during the operation of the spinning frame, and determining the abnormal influence degree of the spindle speed during the operation of the spinning frame;

[0010] The optimal control parameter of the PID controller is obtained by using an optimization algorithm, wherein a fitness function of the optimization algorithm is constructed by taking the abnormal influence degree as a weight and combining a performance index of the PID controller; and the PID controller controls the spindle speed during the next operation of the spinning frame by using the optimal control parameter.

[0011] In one embodiment, the determination of the tension abnormality significant value of each cycle includes:

[0012] The spinning yarn tension at all times of each cycle is curve-fitted, and the mean value of the absolute value of the difference between the fitted value and the actual value of the spinning yarn tension at all times of each cycle is calculated;

[0013] The skewness of the fitted curve of the spinning yarn tension of each cycle is calculated; the tension abnormality significant value is positively correlated with the mean value and the absolute value of the skewness, and negatively correlated with the correlation.

[0014] In one embodiment, the further determination of the tension abnormality significant value includes:

[0015] The correlation is non-negatively mapped, the product of the mean value and the absolute value of the skewness is calculated, and the tension abnormality significant value is the ratio of the product to the result of the non-negative mapping.

[0016] In one embodiment, the determination of the spindle speed deviation significant value of each cycle includes:

[0017] The fitted curve of the spindle speed at all times of each cycle is obtained, all extreme points on the fitted curve are obtained, the ratio between the difference in amplitude of adjacent extreme points and the corresponding time interval is calculated and recorded as a first ratio, and the mean value of the first ratio of all adjacent extreme points on the fitted curve is taken as the speed fluctuation factor of each cycle;

[0018] The speed deviation coefficient of each cycle is determined by the difference between each extreme point on the fitted curve and the target speed;

[0019] The speed deviation significant value of the spindle speed in each cycle is obtained by combining the speed fluctuation factor and the speed deviation coefficient.

[0020] In one embodiment, the determination of the speed deviation coefficient of each cycle includes:

[0021] The sum value of the absolute value of the difference between all extreme points on the fitted curve and the target speed is calculated, and the speed deviation coefficient is the ratio of the sum value to the target speed.

[0022] In one embodiment, the speed state difference value is the dispersion degree of the speed deviation significant value of all spindles of the spinning frame in each cycle.

[0023] In one embodiment, the abnormality influence degree is a normalized value of a correlation coefficient of the tension abnormality significant value and the speed state difference value of all cycle periods during the spinning frame operation.

[0024] In one embodiment, the expression of the fitness function is:

[0025] ; wherein, J is a fitness function, is an abnormality influence degree of the spindle speed during the spinning frame operation, is an overshoot value in the process of the PID controller controlling the spindle speed, is a rise time in the process of the PID controller controlling the spindle speed, is a steady-state error in the process of the PID controller controlling the spindle speed.

[0026] In one embodiment, the optimization algorithm aims to minimize the fitness function.

[0027] In a second aspect, the embodiments of the present application also provide a spinning frame spindle speed control system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the method of any one of the above when executing the computer program.

[0028] The present application has at least the following beneficial effects:

[0029] The present application can more accurately capture the subtle changes of the tension fluctuation by comprehensively analyzing the trend and symmetry of the spinning tension of each cycle period, and timely find the unevenness or sudden change of the yarn tension, measure the abnormality degree of the spinning tension, and improve the accuracy of the spinning tension abnormality identification. Further, the present application determines the deviation significant value of the spindle speed in each cycle period, reflects the abnormality degree of the spindle speed in each cycle period, enhances the sensitivity to the abnormal change of the spindle speed, and helps to improve the accuracy of the subsequent spindle speed control. The interaction of the tension abnormality significant value and the speed state difference value is comprehensively considered, so that the PID controller can more accurately adjust the speed, and the limitation that the speed adjustment in the traditional method cannot effectively handle the influence of the tension abnormality on the yarn quality is solved. This comprehensive optimization not only improves the accuracy of the speed control, but also avoids the quality fluctuation caused by ignoring the tension abnormality. By constructing the fitness function and using the optimization algorithm, the optimal control parameters of the PID controller are obtained, the problem of unstable spindle speed caused by improper setting of the PID controller parameters is avoided, the accuracy of the PID controller parameter setting is improved, the PID controller can better adapt to the complex operating environment of the spinning frame, and thus the accuracy and stability of the spinning frame speed control are improved. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the accompanying drawings required by the embodiments or the prior art description will be briefly introduced as follows. Obviously, the accompanying drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0031] Figure 1 A step flow chart of a spinning frame spindle speed control method provided by an embodiment of the present application is shown in FIG. 1.

[0032] Figure 2 A flow chart for determining the abnormal influence degree of the spindle speed is shown in FIG. 2. DETAILED DESCRIPTION

[0033] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purposes, the specific embodiments, structures, features and effects of the spinning frame spindle speed control method and system according to the present application are described in detail as follows in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0035] The specific scheme of the spinning frame spindle speed control method and system provided by the present application is described in detail below in combination with the drawings.

[0036] Please refer to Figure 1 which shows a step flow chart of a spinning frame spindle speed control method provided by an embodiment of the present application. The method comprises the following steps:

[0037] S1, collecting the speed of the spinning frame spindle at each moment and the spinning yarn tension.

[0038] In the production process of the textile industry, the speed of the spindle directly affects the production quality of the spinning yarn. In order to monitor the speed data of the spinning frame spindle in real time when it is running, the present embodiment uses a laser speed sensor to collect the speed data of the spindle at each moment. In addition, the speed of the spindle is easily affected by abnormal changes in the tension of the spinning yarn. In order to monitor the tension state of the spinning yarn in real time, the present embodiment uses a tension sensor to collect the tension data of the spinning yarn at each moment. The collection frequency of the speed in the present embodiment is set to 100 Hz, and the time interval for collecting the tension of the spinning yarn is 1 second. The implementer can set the collection frequency of the speed and the tension of the spinning yarn according to the actual situation.

[0039] Thus, the spindle speed data and the spun yarn tension data during the operation of the spinning frame are obtained.

[0040] S2, analyze the trend of all the spun yarn tension in each cycle period and the symmetry of the spun yarn tension distribution, determine the tension abnormal significant value of each cycle period in combination with the correlation of the spun yarn tension between each cycle period and its adjacent cycle period.

[0041] When the spinning frame is running, the spindle speed is easily affected by many factors, for example, the spindle surface and bearing wear, abnormal change of the spun yarn tension and sudden disturbance of the motor. Without changing the equipment hardware, the spindle is generally controlled to run within the target speed by using control algorithm to reduce the interference of the above factors. In this embodiment, the spindle speed control is optimized by analyzing the characteristics of the influence on the spindle speed, thereby improving the stability of the spinning frame operation.

[0042] Firstly, the spun yarn winding is completed by the mutual cooperation of the rotating motion of the spindle and the up-and-down reciprocating motion of the ring plate. The winding layer is formed when the ring plate moves upward, at which time the yarn loop is tight and the winding speed is fast. The binding layer is formed when the ring plate moves downward, at which time the yarn loop is sparse and the winding speed is slow. In this embodiment, the time required for one rising and falling process of the ring plate is taken as one cycle period. In the actual processing process, the spun yarn tension will appear the characteristics of periodic fluctuation within a small range due to the reciprocating displacement of the ring plate. When the ring plate rises, the spun yarn tension will increase, and vice versa. In a single cycle period, the tension curve shows a Gaussian distribution trend.

[0043] However, the spun yarn tension may change abnormally due to yarn quality defects or ring plate wear, which is specifically manifested as the decrease of the trend and overall symmetry of the spun yarn tension data change within a single cycle period, and the large difference between the tension curves of adjacent cycle periods. In view of this, this embodiment takes the i-th cycle period as an example, uses the least square fitting algorithm to perform nonlinear fitting on all the spun yarn tension data in the i-th cycle period, and obtains the tension fitting curve. Then, the absolute value of the difference between the spun yarn tension data at each time and its fitting value is calculated, and the mean value of all the absolute value of the difference in the i-th cycle period is denoted as The greater the , the weaker the trend of the spun yarn tension data in the i-th cycle period, and the less the normal distribution characteristics thereof. The least square method is a known technology, and the specific process is not described herein.

[0044] Then, the absolute value of the skewness of the tension fitting curve in the i-th cycle period is calculated, and is denoted as The greater the The greater, the worse symmetry of the fine yarn tension curve. Further, the Spearman correlation coefficient of the tension fitting curve corresponding to the ith cycle period and its adjacent previous cycle period is calculated to measure the correlation of the tension fitting curve corresponding to the ith cycle period and its adjacent previous cycle period. It should be noted that the Spearman correlation coefficient is only one embodiment of the present application, and the implementer can select other existing feasible correlation calculation methods according to actual conditions, and the present embodiment does not limit this.

[0045] The absolute value of the mean of all the difference absolute values in the ith cycle period and the skewness of the tension fitting curve in the ith cycle period are multiplied to obtain a product, and the ratio of the product to the result of the non-negative mapping is taken as the tension anomaly significance value of the ith cycle period . The purpose of the non-negative mapping is to avoid the denominator being 0 and causing the tension anomaly significance value to be unable to be calculated during the calculation process. In the present embodiment, the non-negative mapping is performed by using a sigmoid function to normalize the Spearman correlation coefficient, and the normalized result is taken as the result of the non-negative mapping. The implementer can select other existing feasible non-negative mapping methods.

[0046] Tension anomaly significance value reflects the significant degree of abnormal change characteristics of the fine yarn tension in the ith cycle period and the tension change difference in the local range. The greater the tension anomaly significance value, the more obvious the abnormal condition of the fine yarn tension.

[0047] S3, the deviation significance value of the spindle speed in each cycle period is determined by the fluctuation degree of the spindle speed in each cycle period and the deviation degree of the spindle speed from the target speed.

[0048] Further, under the influence of the abnormal change of the spinning machine tension or the sudden disturbance of the motor, the spindle speed is difficult to maintain stable, and further fluctuates around the speed value. The greater the influence, the more obvious the fluctuation abnormality of the spindle speed. Further, it presents the characteristics of a larger oscillation change rate in a short period of time, and the deviation from the target speed value is more significant. Since the instantaneous change of the speed is obvious, the present embodiment takes the ith cycle period as an example to obtain the continuous fluctuation frequency characteristics. The present embodiment uses a quadratic polynomial fitting algorithm to obtain a fitting curve of all the speed data in the ith cycle period, and obtains all the extreme points in the fitting curve. Further, the ratio of the corresponding amplitude difference between all adjacent two extreme points to the corresponding time interval is calculated, which is denoted as the first ratio. The mean of all the first ratios in the ith cycle period is taken as the speed fluctuation factor of the ith cycle period, which reflects the speed oscillation change speed of the spindle in the ith cycle period, and is denoted as .

[0049] Further, to obtain the deviation degree of the target speed value in the speed oscillation process, all extreme points on the fitting curve of all speed data in the ith cycle are arranged in ascending order of time to obtain a corresponding extreme sequence, and a speed deviation coefficient of the ith cycle is calculated , and the formula is , wherein N represents the total number of data in the extreme sequence corresponding to the ith cycle, represents the kth value in the extreme sequence, represents the target speed value in the ith cycle. The obtained is larger, indicating that the deviation between the spindle speed and the target speed in the cycle is more obvious.

[0050] Further, the speed fluctuation factor and the speed deviation coefficient are combined to obtain a deviation significant value of the spindle speed in the ith cycle , which represents the oscillation change speed and deviation characteristics of the spindle speed in the ith cycle, and the formula is , and the obtained reflects the oscillation change speed and deviation characteristics of the spindle speed in the cycle, and the deviation significant value is larger, indicating that the spindle speed stability in the ith cycle is worse and deviates from the target speed.

[0051] S4, based on the consistency of the deviation significant value of all spindles in the spinning frame in each cycle, a speed state difference value of the spindles in each cycle is obtained; the correlation degree between the tension abnormal significant value and the speed state difference value of all cycles during the operation of the spinning frame is analyzed to determine the abnormal influence degree of the spindle speed during the operation of the spinning frame.

[0052] Nowadays, each spindle in the spinning process has a corresponding driving unit to realize individual control, which can make the spinning frame have high flexibility and better adapt to different process requirements. However, the speeds of different spindles should be consistent during the spinning process, and the worse the consistency of the speed state between the spindles, the greater the influence on the spinning production quality. Although the influence on the speed during the operation is small, the measured data will also have a certain degree of oscillation, which will lead to inaccurate evaluation of the difference characteristics of the speed state of different spindles using the measured speed data. Therefore, the deviation significant value with the oscillation change speed and deviation characteristics is used for analysis in this embodiment, and the more inconsistent the speed state between the spindles, the greater the difference between the corresponding deviation significant values between the spindles. Therefore, the dispersion degree of the corresponding deviation significant values of all spindles in the ith cycle is obtained as the speed state difference value of the spindles in the ith cycle, and the larger the speed state difference value, the more inconsistent the speed state between the spindles in the cycle.

[0053] The dispersion degree can be calculated by variance, standard deviation, coefficient of variation, etc. In this embodiment, the standard deviation is used as the calculation method of the dispersion degree.

[0054] Further, the spinning process usually has a certain length, wherein the ring plate repeatedly performs multiple lifting movements, and in a good processing state, the spindle speed needs to be kept stable for a long time, and there is a certain interaction between the spinning tension and the spindle speed. Therefore, the more similar the spinning tension abnormal characteristics and the spindle speed abnormal characteristics are, the more obvious the instability characteristics of the spindle speed affected by various factors are. In view of this, the correlation degree of the tension abnormal significant value and the speed state difference value of all cycle periods during the operation of the spinning machine is analyzed, wherein the operation of the spinning machine in this embodiment refers to the entire time period corresponding to the start of the spinning machine to the shutdown of the spinning machine. In this embodiment, the normalized value of the Hoeffding's D correlation coefficient between the tension abnormal significant value and the speed state difference value of all cycle periods during the operation of the spinning machine is calculated as the abnormal influence degree of the spindle speed during the operation of the spinning machine, which reflects the similarity between the spinning tension abnormal characteristics and the spindle speed abnormal characteristics, and the greater the abnormal influence degree, the greater the influence on the control of the spindle speed, which is more likely to cause the production quality of the spun yarn to be unstable. The implementer can select other existing feasible correlation coefficient calculation methods, such as Pearson correlation coefficient, etc., which are not limited in this embodiment. The normalized value of the Hoeffding's D correlation coefficient is obtained by using the sigmoid function, and the implementer can select other existing feasible normalization methods. The abnormal influence degree determination flowchart of the spindle speed is shown in Figure 2 .

[0055] S5, obtaining the optimal control parameters of the PID controller by using an optimization algorithm, wherein the abnormal influence degree is used as a weight, and a fitness function of the optimization algorithm is constructed in combination with the performance index of the PID controller; the PID controller controls the spindle speed of the spinning machine during the next operation by using the optimal control parameters.

[0056] In this embodiment, the abnormal change characteristics of the spun yarn tension and the oscillation change speed and deviation characteristics of the spindle speed during the operation of the spinning machine are analyzed in depth, and the influence degree of the interaction between the spun yarn tension and the spindle speed on the control of the spindle speed is further considered. Based on this, the control of the spindle speed is optimized.

[0057] Specifically, the PID controller is used to control the spindle speed in this embodiment, the abnormal influence degree of the spindle speed during the operation of the spinning machine is calculated after the operation of the spinning machine is completed, the fitness function is constructed in combination with the performance index of the PID controller, and the optimal control parameters of the PID controller, i.e. the proportional coefficient , integral coefficient , and differential coefficient .

[0058] First, in the spinning frame spindle speed control experiment, the genetic algorithm is used to optimize the control parameters of the PID controller. The control parameters are adjusted in real time according to the steady-state error feedback of the PID controller, so that the spindle speed always converges to the target precision during the control process. The value range of the PID control parameters is set, wherein, , , , the population of the genetic algorithm is initialized according to the range.

[0059] Secondly, the fitness function is constructed, the expression is: ; in the formula, J is the fitness function, is the abnormal influence degree of the spindle speed during the operation of the spinning frame, is the overshoot of the PID controller during the control of the spindle speed, is the rise time of the PID controller during the control of the spindle speed, is the steady-state error of the PID controller during the control of the spindle speed. The fitness function can evaluate the performance of the PID controller. The optimization process of the genetic algorithm is to minimize the fitness function, wherein the maximum number of iterations is 100.

[0060] In the fitness function, the greater the abnormal influence degree of the spindle speed during the operation of the spinning frame, the greater the influence on the spindle speed, which is easy to lead to unstable production quality of the spun yarn, and a larger rise time weight needs to be set to improve the response speed of the regulation and control; on the contrary, the smaller the abnormal influence degree, the smaller the influence on the current spindle speed, the rise time weight can be reduced, the overshoot weight can be increased, the suppression effect of the overshoot is better, and the control precision is improved.

[0061] Finally, the global optimal control parameters , and are obtained after the optimization of the genetic algorithm, and the PID controller uses the optimal control parameters to start the spindle speed control during the next operation of the spinning frame, realizes the optimization control of the spindle speed, and helps to make up for the defects of insufficient control precision of the spindle speed and improve the production quality of the spun yarn. Genetic algorithm and PID controller are prior known technologies, and the implementer can select other feasible optimization algorithms, which are not limited in the embodiment.

[0062] Based on the same inventive concept as the above method, the application further provides a spinning frame spindle speed control system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor executes the computer program to implement the steps of any one of the above spinning frame spindle speed control methods.

[0063] It should be noted that the above-mentioned sequence of the embodiments of the application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the above describes the specific embodiments of the present application. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0064] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments.

[0065] The above only describes the preferred embodiments of the application, and does not limit the application. Any modification, equivalent replacement, improvement, etc. made within the principles of the application shall be included in the protection scope of the application.

Claims

1. A method for controlling the spindle speed of a spinning frame, characterized in that, The method includes the following steps: Collect the spindle speed and yarn tension of the spinning machine at various times; The trend of all yarn tensions in each cycle and the symmetry of yarn tension distribution are analyzed. Combined with the correlation of yarn tension in each cycle and its adjacent cycles, the significant values ​​of tension anomalies in each cycle are determined. The significant deviation of the spindle speed in each cycle is determined by the degree of fluctuation of the spindle speed in each cycle and the degree of deviation of the spindle speed from the target speed. Based on the consistency of the significant deviation values ​​of the rotational speeds of all spindles in each cycle, the difference value of the spindle rotational speed state in each cycle is obtained; the correlation between the significant value of the tension anomaly and the difference value of the rotational speed state in all cycles during the operation of the spinning machine is analyzed to determine the degree of abnormal influence of the spindle rotational speed during the operation of the spinning machine. The optimal control parameters of the PID controller are obtained using an optimization algorithm, wherein the fitness function of the optimization algorithm is constructed by using the abnormal influence degree as the weight and combining it with the performance index of the PID controller; the PID controller uses the optimal control parameters to control the spindle speed during the next run of the spinning machine. The determination of the significant value of tension anomalies in each cycle includes: Curve fitting is performed on the yarn tension at all times in each cycle, and the mean of the absolute values ​​of the differences between the fitted values ​​and the actual values ​​of the yarn tension at all times in each cycle is calculated. Calculate the skewness of the fitted curve of yarn tension for each cycle; the significant value of the tension anomaly is positively correlated with the mean and the absolute value of the skewness, and negatively correlated with the correlation. The determination of the significant deviation value of the spindle rotation speed within each cycle includes: Obtain the fitting curve of the spindle rotation speed at all times in each cycle, obtain all extreme points on the fitting curve, calculate the ratio between the difference in amplitude of adjacent extreme points and the corresponding time interval, and record it as the first ratio. Use the average of the first ratios of all adjacent extreme points on the fitting curve as the rotation speed fluctuation factor for each cycle. By comparing the extreme points on the fitted curve with the target speed, the speed deviation coefficient for each cycle is determined. By combining the speed fluctuation factor and the speed deviation coefficient, the significant deviation value of the spindle speed in each cycle is obtained.

2. The method for controlling the spindle speed of a spinning frame as described in claim 1, characterized in that, Further determination of the significant value of the tension anomaly includes: The correlation is non-negatively mapped, and the product of the mean and the absolute value of the skewness is calculated. The significance value of the tension anomaly is the ratio of the product to the result of the non-negative mapping.

3. The method for controlling the spindle speed of a spinning frame as described in claim 1, characterized in that, The determination of the speed deviation coefficient for each cycle includes: Calculate the sum of the absolute values ​​of the differences between all extreme points on the fitted curve and the target speed, whereby the speed deviation coefficient is the ratio of the sum to the target speed.

4. The method for controlling the spindle speed of a spinning frame as described in claim 1, characterized in that, The speed state difference value is the degree of dispersion of the significant deviation values ​​of the speed of all spindles of the spinning machine in each cycle.

5. The method for controlling the spindle speed of a spinning frame as described in claim 1, characterized in that, The abnormality impact is the normalized value of the correlation coefficient between the significant value of the abnormal tension and the difference in the rotational speed during all cycles of the spinning machine operation.

6. The method for controlling the spindle speed of a spinning frame as described in claim 1, characterized in that, The expression for the fitness function is: In the formula, J is the fitness function. The impact of abnormal spindle speed during the operation of the spinning frame. This is to address the overshoot during the PID controller's control of the spindle speed. The rise time is used to control the spindle speed using a PID controller. The steady-state error during the process of controlling the spindle speed by a PID controller is t, where t represents time.

7. The method for controlling the spindle speed of a spinning frame as described in claim 6, characterized in that, The objective of the optimization algorithm is to minimize the fitness function.

8. A spindle speed control system for a spinning frame, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-7.

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