Fabric winding machine control method and system for automobile interior fabric production

Abstract

The present application relates to the technical field of cloth winding machine control, and specifically to a cloth winding machine control method and system for the production of automotive interior fabrics. The method comprises: determining a correlation index by analyzing the correlation between the average level of all speed data in each speed data window in each time period and the fluctuation anomaly value; respectively analyzing the difference between the speed data and the correlation index and the corresponding fitting value, constructing a first and a second difference degree to determine the anomaly coefficient at the current moment; determining the tension complexity by analyzing the complexity of all tension data between the start of the fabric winding process and the current moment, and determining the tension anomaly value in combination with the anomaly coefficient to control the speed of the cloth winding roller during the fabric winding process at the current moment. The present application improves the accuracy of tension adjustment during the fabric winding process by reducing the interference of mechanical wear of the cloth winding machine on the speed adjustment during the fabric winding process.

Description

Technical Field

[0001] The present application relates to the technical field of cloth winding machine control, and in particular to a cloth winding machine control method and system for automobile interior fabric production. Background Art

[0002] As a key component of vehicle interior decoration, automotive interior fabrics are diverse and diverse, encompassing a wide range of applications. These primarily include fabrics, genuine leather, and artificial leather. Fabric winders play a crucial role in fabric production, ensuring uniform fabric winding and precise tension control, thereby ensuring accuracy during subsequent cutting or hot-pressing processes. As a key piece of equipment in the final stages of the fabric production process, the performance of these winders directly impacts the product's appearance, quality, dimensional stability, and processing performance.

[0003] Currently, fully automatic cloth winding machines are a more commonly used type on the market. They can automatically complete the winding of fabrics, greatly improving production efficiency. They are usually equipped with advanced sensors and control systems that can monitor and adjust the tension and speed during the winding process in real time, and can also perform deviation correction. When winding fabrics, the winding tension of the cloth winding machine has a significant impact on the quality of the fabric. Too little tension will cause the fabric to fold and wrinkle, while too much tension will stretch and deform the fabric, damaging the fabric. However, due to wear or damage to the swing roller cylinder and high-precision potentiometer components, the increase or decrease in the winding diameter during the winding process will lead to unstable tension control. Conventional cloth winding machines fail to fully consider the interference of the above factors during operation, reducing the tension adjustment accuracy of the cloth winding machine when winding fabrics. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a control method and system for a cloth winding machine for the production of automotive interior fabrics. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for controlling a cloth winding machine for producing automotive interior fabrics, the method comprising the following steps:

[0006] Real-time acquisition of fabric tension data during winding and cloth roller speed data;

[0007] The fabric winding process is divided into multiple time periods from the start to the current moment. In each time period, each speed data and all speed data in its window are fitted. By analyzing the change rate between all adjacent extreme values ​​on the fitting curve, the fluctuation abnormal value in each speed data window is determined. By analyzing the correlation between the average level of all speed data in each speed data window in each time period and the fluctuation abnormal value, the correlation index of each time period is determined.

[0008] Fit all speed data between the start of the fabric winding process and the current moment to obtain a speed fitting curve, and analyze the differences between all speed data and the fitting values ​​on the speed fitting curve to determine a first difference degree at the current moment; fit the correlation indexes of all time periods, analyze the differences between all correlation indexes and the fitting results to determine a second difference degree at the current moment, and combine the first difference degree to determine the abnormal coefficient at the current moment;

[0009] By analyzing the complexity of all tension data between the start of the fabric winding process and the current moment, the tension complexity at the current moment is determined, and combined with the abnormal coefficient, the tension abnormal value at the current moment is determined to control the rotation speed of the cloth winding roller during the fabric winding process at the current moment.

[0010] Preferably, the fluctuation abnormal value in each speed data window is the cumulative sum of the change rates between all adjacent extreme values ​​on the fitting curve in each speed data window.

[0011] Preferably, the method for determining the correlation index of each time period is:

[0012] The mean of all speed data in each speed data window in each time period is calculated, and the correlation coefficient between the mean and the fluctuation abnormal value in the window of all speed data in each time period is used as the correlation index of each time period.

[0013] Preferably, the first difference degree at the current moment is the cumulative sum of the differences between all rotational speed data and corresponding fitting values ​​on the rotational speed fitting curve between the start of the fabric winding process and the current moment.

[0014] Preferably, the method for determining the second difference at the current moment is:

[0015] The curve obtained by fitting the correlation index of all time periods between the start of the fabric winding process and the current moment is recorded as the correlation curve, and the result of accumulating the differences between the correlation index of all time periods and the corresponding fitting values ​​on the correlation curve is used as the second difference degree at the current moment.

[0016] Preferably, the abnormal coefficient at the current moment is a result of forward fusion of the first difference degree and the second difference degree at the current moment.

[0017] Preferably, the tension complexity at the current moment is the fractal dimension of all tension data between the start of the fabric winding process and the current moment.

[0018] Preferably, the expression of the abnormal tension value at the current moment is: Where, Indicates the abnormal tension value at the current moment; Indicates the abnormal coefficient at the current moment; Indicates the tension complexity at the current moment.

[0019] Preferably, the controlling of the rotation speed of the cloth winding roller during the fabric winding process at the current moment includes:

[0020] Gain coefficient at the current moment The expression is: Where, 、 Respectively represent the preset reference value and the preset correction value; Indicates the abnormal value of tension at the current moment; norm( ) indicates the normalization function;

[0021] The gain coefficient at the current moment is used as the gain coefficient of the sliding membrane variable structure in the motor during the fabric winding process to control the speed of the cloth winding roller. Secondly, an embodiment of the present application also provides a cloth winding machine control system for automotive interior fabric production, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the computer program, implements any of the steps of the aforementioned cloth winding machine control method for automotive interior fabric production.

[0022] This application has at least the following beneficial effects:

[0023] The present application constructs a fluctuation anomaly value by analyzing the changes in the speed data, which can detect the fluctuation of the speed of the cloth winding roller, promptly discover abnormal changes in the speed, and adjust the speed, thereby reducing the interference of mechanical vibration on the speed adjustment, and thus improving the tension control accuracy; further, by analyzing the correlation between the fluctuation anomaly value and the speed data, a correlation index is constructed, which can more accurately adjust the speed of the cloth winding roller, thereby improving the tension control accuracy during the fabric winding process, and helping to maintain constant tension during the fabric winding process; further, the differences between the speed data and the correlation index and the corresponding fitting values ​​are respectively analyzed to construct the first and second difference degrees, which help to comprehensively evaluate the operating status of the cloth winding machine, and timely and accurately adjust the speed of the cloth winding machine, thereby improving the tension control accuracy and improving the fabric winding quality; further, the present application constructs a tension anomaly value by comprehensively combining the first difference degree and the second difference degree, and combining the complexity of the tension data, which is used to optimize the gain coefficient in the control system of the cloth winding machine, and regulate the speed data, so as to more accurately adjust the speed of the cloth winding roller, thereby ensuring constant tension during the fabric winding process and improving the fabric winding quality. The present application ensures constant tension during the fabric winding process by real-time monitoring and regulation of the rotation speed of the cloth winding roller, reduces interference of mechanical wear on speed adjustment, and improves the accuracy of tension adjustment during the fabric winding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0025] Figure 1 A flowchart of a method for controlling a cloth winding machine for automotive interior fabric production provided in one embodiment of the present application;

[0026] Figure 2 A schematic diagram of the tension outlier value extraction process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] To further illustrate the technical means and effectiveness of this application's implementation of the intended invention, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of the winder control method and system for automotive interior fabric production proposed in this application. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0028] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0029] The specific scheme of the cloth winding machine control method and system for automobile interior fabric production provided by this application is described in detail below with reference to the accompanying drawings.

[0030] See also Figure 1 , which shows a flowchart of a method for controlling a cloth winding machine for automobile interior fabric production provided by an embodiment of the present application, the method comprising the following steps:

[0031] Step S1: Real-time acquisition of tension data of the fabric during winding and speed data of the fabric winding roller.

[0032] A fabric winder stores woven fabric or controls the winding tension to facilitate subsequent processes. During fabric winding, the winding tension significantly impacts fabric quality. A fabric winder typically consists of a roll, a frame, a drive system, and a control system. The roll is mounted on the frame, and the drive system is directly connected to it. This system rotates the roll, winding the fabric onto the roll. Maintaining constant fabric tension during winding is crucial. This is achieved by adjusting the roll's speed, which is controlled by the control system. To monitor fabric tension in real time during winding, a tension sensor collects tension data, while a speed sensor collects roll speed data. Both tension and speed data are collected at a frequency of f.

[0033] It should be noted that the value of the data acquisition frequency f is manually set. In this embodiment, the value of the data acquisition frequency f is 10 Hz. In actual application, the implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0034] Step S2: Divide the fabric winding process from the start to the current moment into multiple time periods. In each time period, fit each speed data and all speed data in its window. By analyzing the change rate between all adjacent extreme values ​​on the fitting curve, the fluctuation anomaly value in each speed data window is determined; by analyzing the correlation between the average level of all speed data in each speed data window in each time period and the fluctuation anomaly value, the correlation index of each time period is determined.

[0035] Maintaining constant tension during the fabric winding process is crucial during fabric winding machine operation. For example, too little tension can cause fabric to wrinkle, while too much tension can cause stretching and deformation, both of which can affect subsequent storage or production, and even damage the fabric. However, during fabric winding, the roll speed can be difficult to maintain stable due to mechanical transmission system anomalies. For example, a gear or bearing failure in the roll can affect the roll speed. Abnormal speed fluctuations are a major factor affecting constant fabric tension. Furthermore, as the roll diameter increases, the roll diameter gradually increases. Maintaining constant tension during fabric winding requires maintaining a constant circumferential speed, so the roll speed must be adjusted accordingly. As the roll diameter increases, the roll speed must decrease accordingly. This is because the roll length required to be wound on the roll surface increases in the same amount of time. If the speed remains constant, the fabric tension increases, affecting the quality and smoothness of the fabric. Therefore, the characteristics of possible localized speed anomalies and overall speed fluctuations of the roll are analyzed.

[0036] First, under the influence of wear of the mechanical structure of the drive system, such as the presence of surface scratches and grooves, or poor contact between the rolling elements inside the bearing and the inner and outer ring raceways, the speed of the cloth roller will cause rapid up and down jumps in a short period of time. As the cloth roller continues to rotate, the resulting up and down rapid jumps show periodic changes that are proportional to the speed of the cloth roller.

[0037] Therefore, by analyzing the changing characteristics of the cloth roller speed and determining the abnormal fluctuation value, it is possible to judge whether the cloth roller speed is abnormal in a short period of time. The specific process is as follows:

[0038] The fabric winding process to the current moment is divided into multiple time periods. In each time period, each speed data is taken as the starting point, and each speed data and a preset number of adjacent speed data thereafter are used to form a window of each speed data. Each speed data and all speed data in the window are fitted to obtain a fitting curve. The cumulative sum of the change rates between all adjacent extreme values ​​on the fitting curve is used as the fluctuation anomaly value in each speed data window, which is used to characterize the local jump degree and jump frequency characteristics of the speed data. If the change rate is larger, it means that the local jump degree of the speed data is larger, and the obtained fluctuation anomaly value is larger, indicating that the cloth roller is more disturbed by the wear of the mechanical structure of the dynamic system, and the speed data is less valuable for reference. Conversely, if the change rate is smaller, it means that the local jump degree of the speed data is smaller, and the obtained fluctuation anomaly value is smaller, indicating that the cloth roller is less disturbed by the wear of the mechanical structure of the dynamic system, and the speed data is more valuable for reference.

[0039] It should be noted that the value of the preset number is set manually. In this embodiment, the value of the preset number is 11. The implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0040] It should be understood that the calculation method of the change rate in this embodiment is: the ratio of the absolute value of the difference between each adjacent extreme value on the fitting curve to the corresponding time interval.

[0041] In addition, it is supplemented that there are many commonly used fitting methods. In this embodiment, the least squares method is used to fit the speed data. In actual application, the implementer can also use other fitting methods such as polynomial function fitting method according to the specific situation. Regarding the selection of fitting method, this embodiment does not impose any special restrictions. Among them, in this embodiment, all fitting processes involved use the least squares fitting method. The least squares fitting method is a well-known technology, and the specific process of using it to fit the speed data will not be repeated.

[0042] It is particularly noted that in this embodiment, there may be a situation where there are less than a preset number of adjacent and continuous speed data after the speed data. Therefore, in this situation, the speed data that is adjacent and continuous to the speed data before the speed data is used to fill the gap.

[0043] Furthermore, as the cloth roll rotates, in order to avoid the situation where the cloth roll diameter increases but the fabric tension increases due to the unchanged rotation speed, thereby affecting the cloth roll quality and the flatness of the fabric, under normal circumstances, the rotation speed gradually decreases as the cloth roll diameter increases. The corresponding up and down rapid jump characteristics show a periodic change that is proportional to the rotation speed of the cloth roll. Therefore, based on the above characteristics, by analyzing the correlation between the average level of all speed data in each speed data window in each time period and the fluctuation abnormal value, the correlation index of each time period is determined to reflect whether the up and down rapid jump characteristics are proportional to the speed, so as to judge whether the speed data is abnormal and whether it needs to be adjusted. Specifically:

[0044] In this embodiment, the mean of all speed data in each speed data window in each time period is calculated, and the correlation coefficient between the mean value in the window of all speed data in each time period and the fluctuation abnormal value is used as the correlation index of each time period, which is used to reflect whether there is a regular correlation change between the up and down rapid jump feature and the speed of the cloth winding roller. If the correlation coefficient is larger, it means that there is a strong correlation between the up and down rapid jump feature and the speed of the cloth winding roller, that is, the larger the correlation index is, the speed data is not abnormal and no adjustment is required; on the contrary, if the correlation coefficient is smaller, it means that there is a weak correlation between the up and down rapid jump feature and the speed of the cloth winding roller, that is, the smaller the correlation index is, it indicates that the speed data is abnormal and needs to be adjusted.

[0045] It should be noted that there are many methods for calculating the correlation coefficient. In this embodiment, the Spearman correlation coefficient between the mean value and the fluctuation abnormal value in the window of all speed data in each time period is used as the correlation coefficient between the mean value and the fluctuation abnormal value in the window of all speed data in each time period. In actual application, the implementer may also adopt other correlation coefficient calculation methods such as the Pearson correlation coefficient based on specific circumstances. This embodiment does not impose any special restrictions on the selection of the correlation coefficient calculation method.

[0046] The calculation method of the Spearman correlation coefficient is a well-known technique, and the specific calculation process will not be described in detail.

[0047] At this point, by analyzing the abnormal fluctuation values ​​of the speed data, it is determined whether there are abnormal conditions such as mechanical structure wear of the cloth winding roller. By analyzing the correlation between the speed data and the abnormal fluctuation values, it is determined whether the speed data is abnormal, so as to improve the accuracy of the speed adjustment, thereby improving the tension adjustment accuracy during the fabric winding process, maintaining constant tension, and thus improving the cloth winding quality and fabric flatness.

[0048] Step S3: Fit all speed data between the start of the fabric winding process and the current moment to obtain a speed fitting curve, and analyze the differences between all speed data and the fitting values ​​on the speed fitting curve to determine the first difference degree at the current moment; fit the relevant indexes of all time periods, analyze the differences between all relevant indexes and the fitting results, determine the second difference degree at the current moment, and combine the first difference degree to determine the abnormal coefficient at the current moment.

[0049] As the fabric winder operates, the linear velocity of the fabric roll is relatively constant to ensure stable tension. The relationship between the linear velocity v of the fabric roll and the speed n of the fabric roll is: v = πdn, where d is the fabric roll diameter. As the fabric roll diameter d increases during the fabric winding process, the speed n of the fabric roll must decrease inversely to maintain a constant linear velocity v. The rate of increase in the fabric roll diameter decreases gradually, causing the rate of decrease in the fabric roll speed to also decrease as the fabric is wound. Therefore, the speed-time curve of the fabric roll approximates the first quadrant of an inverse proportional function. Therefore, when the fabric winder is operating properly, the speed-time curve should be relatively smooth. However, mechanical wear can reduce the smoothness of this curve, deviating from the inverse proportional function. Consequently, non-smooth speed fluctuations can affect fabric tension fluctuations during winding.

[0050] Based on the above analysis, by fitting all the speed data between the start of the fabric winding process and the current moment, a speed fitting curve is obtained. The differences between all the speed data and the fitting values ​​on the speed fitting curve are analyzed to determine the first difference degree at the current moment to characterize the degree of non-smooth change in the speed of the cloth winding roller. It is further judged whether the speed data is interfered by mechanical structure wear. Specifically:

[0051] All speed data between the start of the fabric winding process and the current moment are fitted to obtain a speed fitting curve. The cumulative sum of the differences between all speed data between the start of the fabric winding process and the current moment and the corresponding fitting values ​​on the speed fitting curve is taken as the first difference degree at the current moment, which reflects the non-smooth change of the speed of the cloth winding roller. If the difference between the speed data and the corresponding fitting value on the speed fitting curve is greater, it means that the speed fitting curve is less smooth, and the obtained first difference degree is greater, indicating that the speed of the cloth winding roller is more likely to be affected by mechanical structure wear; conversely, if the difference between the speed data and the corresponding fitting value on the speed fitting curve is smaller, it means that the speed fitting curve is smoother, and the obtained first difference degree is smaller, indicating that the speed of the cloth winding roller is less likely to be affected by mechanical structure wear, that is, the cloth winding machine is in normal operation.

[0052] It should be noted that there are many methods for measuring the differences between data. In this embodiment, the absolute value of the difference between all the speed data between the start of the fabric winding process and the current moment and the corresponding fitting value on the speed fitting curve is used as the difference between all the speed data between the current moment and the corresponding fitting value on the speed fitting curve. In actual application, as other implementation methods, the implementer can also use other methods for measuring the differences between data, such as the square or ratio of the difference, based on the specific circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between data.

[0053] It is additionally noted that, in this embodiment, all the contents involving the calculation of differences adopt the method of taking the absolute value of the difference.

[0054] Furthermore, the significant values ​​with abnormal jump and periodic characteristics also have similar variation characteristics to the cloth roller speed curve. Specifically, in the early stages of the cloth roller operation, the cloth roller speed is relatively high and its speed decreases rapidly, which corresponds to the significant values ​​with abnormal jump and periodic characteristics being relatively high and decreasing rapidly. As the cloth roll diameter increases, the cloth roller speed slows down, and its speed decreases more slowly, which corresponds to the significant values ​​with abnormal jump and periodic characteristics becoming lower and decreasing more slowly.

[0055] Therefore, the correlation indexes of all time periods are fitted, and the differences between all correlation indexes and the fitting results are analyzed to determine the second difference degree at the current moment, specifically:

[0056] The curve obtained by fitting the correlation index of all time periods between the start of the fabric winding process and the current moment is recorded as the correlation curve. The result of accumulating the differences between the correlation index of all time periods and the corresponding fitting values ​​on the correlation curve is taken as the second difference degree at the current moment, which reflects the degree of non-smooth change of the correlation between the up and down jump characteristics and the speed data under the influence of mechanical structure wear. If the difference between the correlation index and the corresponding fitting value is greater, it means that the correlation between the up and down jump characteristics and the speed data changes less smoothly, that is, the greater the second difference degree, it indicates that the speed of the cloth roller is more disturbed by the wear of the mechanical structure, etc. Conversely, if the difference between the correlation index and the corresponding fitting value is smaller, it means that the correlation between the up and down jump characteristics and the speed data changes more smoothly, that is, the smaller the second difference degree, it indicates that the speed of the cloth roller is less disturbed by the wear of the mechanical structure, etc.

[0057] Furthermore, the second difference degree at the current moment is combined with the first difference degree to determine the abnormality coefficient at the current moment, specifically:

[0058] The result of the forward fusion of the first difference and the second difference at the current moment is used as the abnormality coefficient at the current moment to characterize the smoothness of the change in the cloth roller speed and the correlation. If the abnormality coefficient is larger, it means that the cloth roller speed and the correlation change are more unstable, that is, the corresponding first and second differences are larger. Conversely, if the abnormality coefficient is smaller, it means that the cloth roller speed and the correlation change are more stable, that is, the corresponding first and second differences are smaller.

[0059] It should be understood that forward fusion refers to combining two or more indicators through addition or multiplication to obtain a comprehensive indicator, thereby more comprehensively and accurately evaluating a phenomenon or problem. This fusion method is not limited to simple arithmetic operations and can also include more complex statistical models and analysis methods. Implementers can choose according to their specific circumstances and this embodiment does not impose any special restrictions.

[0060] Preferably, in this embodiment, the sum of the first difference degree and the second difference degree at the current moment is used as the abnormality coefficient at the current moment.

[0061] At this point, by fitting the speed data and related indexes during the fabric winding process and analyzing the differences in the remaining fitting curves, the first and second difference degrees are calculated, and the two are forward fused to obtain the anomaly coefficient. This anomaly coefficient is used to characterize the smoothness of the changes in the speed of the cloth winding roller and its correlation, so as to promptly detect whether there are abnormal conditions such as mechanical structure wear of the cloth winding machine, improve the tension control accuracy during the fabric winding process, ensure constant tension, and thus improve the cloth winding quality and fabric flatness.

[0062] Step S4: By analyzing the complexity of all tension data between the start of the fabric winding process and the current moment, the tension complexity at the current moment is determined, and combined with the abnormal coefficient, the tension abnormal value at the current moment is determined to control the rotation speed of the cloth winding roller during the fabric winding process at the current moment.

[0063] In addition to the influence of the rotation speed of the cloth roller, the unevenness of the raw material properties and changes in the ambient humidity will also interfere with the tension of the fabric winding process, resulting in irregular random fluctuations in the tension data during fabric winding. In order to reduce the random fluctuations of the fabric tension, it is necessary to timely regulate the rotation speed of the cloth roller. The greater the degree of random fluctuation of the tension data and the greater the influence of the rotation speed of the cloth roller, the faster the response rate of the system control should be. Therefore, combined with the fluctuation state characteristics of the fabric tension and the abnormal characteristics of the non-smooth change of the rotation speed of the cloth roller, that is, by analyzing the complexity of all tension data between the start of the fabric winding process and the current moment, the tension complexity at the current moment is determined, and combined with the abnormal coefficient, the tension abnormal value at the current moment is determined, specifically:

[0064] The fractal dimension of all tension data between the start of the fabric winding process and the current moment is taken as the tension complexity at the current moment, which reflects the degree of random fluctuation of the tension data during the fabric winding process. The larger the fractal dimension of the tension data, the greater the degree of random fluctuation of the tension data during the fabric winding process. Conversely, the smaller the fractal dimension of the tension data, the smaller the degree of random fluctuation of the tension data during the fabric winding process.

[0065] The calculation method of the fractal dimension is a well-known technology, and the specific calculation process will not be described in detail.

[0066] Furthermore, based on the tension complexity and the abnormal coefficient at the current moment, the tension complexity at the current moment is determined, specifically:

[0067] Abnormal tension value at the current moment The expression is: Where, Indicates the abnormal coefficient at the current moment; Indicates the tension complexity at the current moment.

[0068] According to the tension anomaly value at the current moment, it can be understood that if the anomaly coefficient is larger, it means that the cloth roller speed and the correlation change are more unstable, the cloth roller speed is more disturbed by mechanical wear, the possibility of tension anomaly is greater, and the greater the tension complexity is, the greater the random fluctuation degree of tension data is, the greater the possibility of tension anomaly is, and the corresponding tension anomaly value is larger; conversely, if the anomaly coefficient is smaller, it means that the cloth roller speed and the correlation change are more stable, the cloth roller speed is normal, the possibility of tension anomaly is smaller, and the tension complexity is smaller, the random fluctuation degree of tension data is smaller, the possibility of tension anomaly is smaller, and the corresponding tension anomaly value is smaller.

[0069] Preferably, the schematic diagram of the tension abnormal value extraction process provided in this embodiment is as follows Figure 2 shown.

[0070] Furthermore, according to the abnormal tension value, the control system in the cloth winding machine is used to adjust the speed of the cloth winding roller to ensure constant tension when the fabric is wound. Specifically:

[0071] Based on the abnormal tension value, the gain coefficient at the current moment is determined. According to the gain coefficient, the gain coefficient in the control system of the cloth winding machine is optimized to control the speed of the cloth winding roller, specifically:

[0072] Gain coefficient at the current moment The expression is: Where, 、 Respectively represent the preset reference value and the preset correction value; Indicates the abnormal value of tension at the current moment; norm( ) indicates the normalization function;

[0073] The gain coefficient at the current moment is used as the gain coefficient of the sliding membrane variable structure in the motor during the fabric winding process to control the speed of the cloth winding roller.

[0074] It should be noted that the values ​​of the preset baseline value and the preset correction value are both artificially set. The preset baseline value and the preset correction value are both used to adjust the gain coefficient. Since the value range of the gain coefficient is [-7, -2], the preset baseline value is set to -7 and the preset correction value is set to 5 in this embodiment. In actual application, the implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0075] Based on the same inventive concept as the above method, an embodiment of the present application also provides a cloth winding machine control system for automobile interior fabric production, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-mentioned cloth winding machine control methods for automobile interior fabric production.

[0076] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0077] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0078] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A control method for a cloth winding machine for automobile interior fabric production, characterized in that: The method comprises the following steps: Real-time acquisition of fabric tension data during winding and cloth roller speed data; The fabric winding process is divided into multiple time periods from the start to the current moment. In each time period, each speed data and all speed data in its window are fitted. By analyzing the change rate between all adjacent extreme values ​​on the fitting curve, the fluctuation abnormal value in each speed data window is determined. By analyzing the correlation between the average level of all speed data in each speed data window in each time period and the fluctuation abnormal value, the correlation index of each time period is determined. Fit all speed data between the start of the fabric winding process and the current moment to obtain a speed fitting curve, and analyze the differences between all speed data and the fitting values ​​on the speed fitting curve to determine a first difference degree at the current moment; fit the correlation indexes of all time periods, analyze the differences between all correlation indexes and the fitting results to determine a second difference degree at the current moment, and combine the first difference degree to determine the abnormal coefficient at the current moment; By analyzing the complexity of all tension data between the start of the fabric winding process and the current moment, the tension complexity at the current moment is determined, and combined with the abnormal coefficient, the tension abnormal value at the current moment is determined to control the rotation speed of the cloth winding roller during the fabric winding process at the current moment.

2. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The fluctuation abnormal value in each speed data window is the cumulative sum of the change rates between all adjacent extreme values ​​on the fitting curve in the window of each speed data.

3. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The method for determining the relevant index of each time period is as follows: The mean of all speed data in each speed data window in each time period is calculated, and the correlation coefficient between the mean and the fluctuation abnormal value in the window of all speed data in each time period is used as the correlation index of each time period.

4. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The first difference degree at the current moment is the cumulative sum of the differences between all rotational speed data and corresponding fitting values ​​on the rotational speed fitting curve between the start of the fabric winding process and the current moment.

5. The control method for a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The method for determining the second difference at the current moment is: The curve obtained by fitting the correlation index of all time periods between the start of the fabric winding process and the current moment is recorded as the correlation curve, and the result of accumulating the differences between the correlation index of all time periods and the corresponding fitting values ​​on the correlation curve is used as the second difference degree at the current moment.

6. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The abnormal coefficient at the current moment is a result of forward fusion of the first difference degree and the second difference degree at the current moment.

7. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The tension complexity at the current moment is the fractal dimension of all tension data between the start of the fabric winding process and the current moment.

8. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The expression of the abnormal tension value at the current moment is: Where, Indicates the abnormal tension value at the current moment; Indicates the abnormal coefficient at the current moment; Indicates the tension complexity at the current moment.

9. The method for controlling a cloth winding machine for automobile interior fabric production according to claim 1, characterized in that: The control of the rotation speed of the cloth winding roller during the fabric winding process at the current moment includes: Gain coefficient at the current moment The expression is: Where, 、 Respectively represent the preset reference value and the preset correction value; Indicates the abnormal value of tension at the current moment; norm( ) indicates the normalization function; The gain coefficient at the current moment is used as the gain coefficient of the sliding membrane variable structure in the motor during the fabric winding process to control the speed of the cloth winding roller.

10. A cloth winding machine control system for automobile interior fabric production, 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, the steps of the cloth winding machine control method for automobile interior fabric production as described in any one of claims 1 to 9 are implemented.

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