Cloth rolling machine control method and system for automobile interior fabric production

Abstract

The invention relates to the technical field of cloth rolling machine control, in particular to a cloth rolling machine control method and system for automobile interior fabric production, and the method comprises the steps that correlation indexes are determined by analyzing the correlation between the average level of all rotating speed data in each rotating speed data window in each time period and a fluctuation abnormal value; respectively analyzing the difference between the rotating speed data and the correlation index and the corresponding fitting value, and constructing a first difference degree and a second difference degree to determine an abnormal coefficient at the current moment; and determining the tension complexity by analyzing the complexity of all tension data from the beginning of the fabric winding process to the current moment, and determining a tension abnormal value by combining the abnormal coefficient so as to control the rotating speed of a cloth roller in the fabric winding process at the current moment. Interference of mechanical abrasion of the cloth rolling machine in the fabric rolling process on rotation speed adjustment is reduced, and the tension adjusting precision in the fabric rolling process is improved.

Description

Technical Field

[0001] This application relates to the technical field of cloth winding machine control, and specifically relates to a cloth winding machine control method and system for automotive interior fabric production. Background Art

[0002] As a key part of automotive interior decoration, automotive interior fabrics are rich in variety and widely used, mainly including fabric fabrics, genuine leather fabrics, artificial leather fabrics, etc. During the fabric production process, the cloth winding machine plays a crucial role. It can achieve uniform winding of the fabric and precise tension control, thus ensuring the accuracy of subsequent cutting or hot pressing processes. As a key equipment in the latter process of the fabric production process, the performance of the cloth winding machine directly has an important impact on aspects such as the appearance quality, dimensional stability, and processing performance of the product.

[0003] At present, the fully automatic cloth winding machine is a relatively common type on the market. The fully automatic cloth winding machine can automatically complete the winding work of the cloth, greatly improving the production efficiency. It is usually equipped with advanced sensors and control systems, which can monitor and adjust the tension, speed during the cloth winding process in real time, and can perform deviation correction. When curling the fabric, the winding tension of the cloth winding machine has an important impact on the quality of the fabric. Too small a tension will cause the fabric to fold and wrinkle, and too large a tension will cause the fabric to stretch and deform, damaging the fabric. However, due to the wear or damage of the swing roller cylinder and high-precision potentiometer components, with the increase or decrease of the roll diameter during the cloth winding process, the tension control will become unstable. The conventional cloth winding machine fails to fully consider the interference of the above factors during operation, reducing the tension adjustment accuracy when the cloth winding machine winds the fabric. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a cloth winding machine control method and system for automotive interior fabric production. The specific technical solutions adopted are as follows: In the first aspect, an embodiment of this application provides a cloth winding machine control method for automotive interior fabric production. The method includes the following steps: Obtain the tension data and the rotational speed data of the cloth winding roller in real time during the fabric winding process; Divide the period from the start to the current moment of the fabric winding process into multiple time periods. In each time period, fit each rotational speed data and all rotational speed data within its window. By analyzing the change rate between all adjacent extreme values on the fitted curve, determine the abnormal fluctuation value within each rotational speed data window; by analyzing the correlation between the average level of all rotational speed data within each rotational speed data window and the abnormal fluctuation value in each time period, determine the correlation index of each time period; Fit all the rotational speed data from the start of the fabric coiling process to the current moment to obtain a rotational speed fitting curve, analyze the difference between all the rotational speed data and the fitting values on the rotational speed fitting curve, and determine the first difference degree at the current moment; fit the correlation indices for all time periods, analyze the difference between all the correlation indices and the fitting results, determine the second difference degree at the current moment, and combine the first difference degree to determine the anomaly coefficient at the current moment; By analyzing the complexity of all the tension data from the start of the fabric coiling process to the current moment, determine the tension complexity at the current moment, and combine the anomaly coefficient to determine the tension anomaly value at the current moment, so as to control the rotational speed of the cloth winding roller during the fabric coiling process at the current moment.

[0005] Preferably, the fluctuation anomaly value within each rotational speed data window is the cumulative sum of the change rates between all adjacent extreme values on the fitting curve within the window of each rotational speed data.

[0006] Preferably, the method for determining the correlation indices for each time period is as follows: Calculate the mean value of all the rotational speed data within each rotational speed data window for each time period, and use the correlation coefficient between the mean value within the window of all the rotational speed data for all time periods and the fluctuation anomaly value as the correlation index for each time period.

[0007] Preferably, the first difference degree at the current moment is the cumulative sum of the differences between all the rotational speed data from the start of the fabric coiling process to the current moment and the corresponding fitting values on the rotational speed fitting curve.

[0008] Preferably, the method for determining the second difference degree at the current moment is as follows: Denote the curve obtained by fitting the correlation indices for all time periods from the start of the fabric coiling process to the current moment as the correlation curve, and use the result of accumulating the differences between all the correlation indices for all time periods and the corresponding fitting values on the correlation curve as the second difference degree at the current moment.

[0009] Preferably, the anomaly coefficient at the current moment is the result of the positive fusion of the first difference degree and the second difference degree at the current moment.

[0010] Preferably, the tension complexity at the current moment is the fractal dimension of all the tension data from the start of the fabric coiling process to the current moment.

[0011] Preferably, the expression for the tension anomaly value at the current moment is: ; where, represents the tension anomaly value at the current moment; represents the anomaly coefficient at the current moment; represents the tension complexity at the current moment.

[0012] Preferably, controlling the rotation speed of the cloth winding roller during the fabric winding process at the current moment includes: The gain coefficient at the current moment The expression of is: ; In the formula, , respectively represent the preset reference value and the preset correction value; represents the tension anomaly value at the current moment; norm( ) represents the normalization function; Take the gain coefficient at the current moment as the gain coefficient in the internal sliding mode variable structure of the motor during the fabric winding process to control the rotation speed of the cloth winding roller. In the second aspect, the embodiment of the present application also provides a cloth winding machine control system for automotive 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 the cloth winding machine control method for automotive interior fabric production described in any one of the above.

[0013] The present application has at least the following beneficial effects: By analyzing the change of the rotation speed data, the present application constructs a fluctuation anomaly value, which can detect the fluctuation of the rotation speed of the cloth winding roller, timely discover the abnormal change of the rotation speed, adjust the rotation speed, so as to reduce the interference of mechanical vibration on the rotation speed adjustment, and further improve the tension control accuracy; further, by analyzing the correlation between the fluctuation anomaly value and the rotation speed data, the present application constructs a correlation index, which can more accurately adjust the rotation speed of the cloth winding roller, thereby improving the tension control accuracy during the fabric winding process and helping to keep the tension constant during the fabric winding process; further, by analyzing the differences between the rotation speed data and the correlation index and the corresponding fitting values respectively, the present application constructs the first and second difference degrees, which helps to comprehensively evaluate the operating condition of the cloth winding machine, timely and accurately adjust the rotation speed of the cloth winding machine, thereby improving the tension control accuracy and the fabric winding quality; further, by synthesizing the first difference degree and the second difference degree and combining the complexity of the tension data, the present application constructs a tension anomaly value to optimize the gain coefficient in the internal control system of the cloth winding machine and regulate the rotation speed data, which can more accurately adjust the rotation speed of the cloth winding roller, thereby ensuring the tension constant during the fabric winding process and improving the fabric winding quality. The present application ensures the tension constant during the fabric winding process by real-time monitoring and regulating the rotation speed of the cloth winding roller, reduces the interference of mechanical wear on the rotation speed adjustment, and improves the tension adjustment accuracy during the fabric winding process. Description of the Drawings

[0014] To more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0015] Figure 1 It is a flowchart of the steps of a cloth winding machine control method for automotive interior fabric production provided by an embodiment of the present application; Figure 2 It is a schematic diagram of the process of extracting the abnormal tension value provided by an embodiment of the present application. Detailed implementation manners

[0016] In order to further elaborate on the technical means and effects adopted by the present application to achieve the intended invention purpose, the following will, in conjunction with the drawings and preferred embodiments, detail the specific implementation manners, structures, features, and effects of the cloth winding machine control method and system for automotive interior fabric production proposed according to the present application. 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.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs.

[0018] The following will specifically describe the specific solutions of the cloth winding machine control method and system for automotive interior fabric production provided by the present application in conjunction with the drawings.

[0019] Please refer to Figure 1 , which shows a flowchart of the steps of a cloth winding machine control method for automotive interior fabric production provided by an embodiment of the present application. The method includes the following steps: Step S1: Real-time obtain the tension data during the fabric winding process and the rotational speed data of the cloth winding roller.

[0020] The function of the cloth winder is to store the woven fabric or control the winding tension of the fabric, facilitating the work of the next process. When winding the fabric, the winding tension in fabric production has an important impact on the quality of the fabric. The cloth winder equipment usually consists of a cloth winding roller, a frame, a drive system, and a control system. The cloth winding roller is installed on the frame, and the drive system is directly connected to the cloth winding roller. The drive system drives the cloth winding roller to rotate, thereby winding the produced fabric onto the cloth winding roller. When winding, it is necessary to maintain a constant fabric tension, and the magnitude of the fabric tension is achieved by adjusting the rotational speed of the cloth winding roller, that is, the rotational speed during the rotation of the cloth winding roller is controlled through the control system. Thus, in order to monitor the tension state of the fabric during the winding process in real time, the tension data during the fabric winding process is collected through a tension sensor, and the rotational speed data of the cloth winding roller is collected through a rotational speed sensor. Among them, the acquisition frequencies of the tension data and the rotational speed data are both set to f.

[0021] It should be noted that the value of the data acquisition frequency f is set artificially. In this embodiment, the value of the data acquisition frequency f is 10Hz. In the actual application process, the implementer can also set it according to the specific situation by himself / herself, and this embodiment does not make special restrictions.

[0022] Step S2: Divide the period from the start to the current moment of the fabric winding process into multiple time periods. Within each time period, fit each rotational speed data and all the rotational speed data within its window. By analyzing the change rate between all adjacent extreme values on the fitted curve, determine the fluctuation outliers within each rotational speed data window; by analyzing the correlation between the average level of all the rotational speed data within each rotational speed data window and the fluctuation outliers under each time period, determine the correlation index of each time period.

[0023] During the operation of the cloth winder, it is crucial to control the constant tension during the fabric winding process. For example, when the tension is too small, the fabric will fold and wrinkle, and when the tension is too large, the fabric will stretch and deform, both of which will affect subsequent storage or production and even damage the fabric. However, when winding the fabric, it is difficult to maintain high stability of the rotational speed of the cloth winding roller under the influence of abnormal mechanical transmission devices. For example, after a failure occurs in the gears or bearings of the cloth winder, it will affect the rotational speed of the cloth winding roller, and the abnormal change in rotational speed is the main factor affecting the constant fabric tension. And as the cloth winder operates, the diameter of its cloth roll will gradually increase. Since maintaining a constant fabric tension during winding requires keeping the circumferential linear speed of the cloth roll constant, therefore, the rotational speed of the cloth winding roller is adjusted accordingly. When the diameter of the cloth roll gradually increases, the corresponding rotational speed of the cloth winding roller needs to be reduced accordingly. This is because after the diameter of the cloth roll increases, the length of the fabric that needs to be wound on the surface of the cloth winding roller within the same time increases. If the rotational speed remains unchanged, it will cause the fabric tension to increase, thereby affecting the winding quality and the flatness of the fabric. Thus, further analyze the possible local rotational speed abnormal characteristics and the overall rotational speed change state of the cloth winding roller.

[0024] First, under the influence of the wear of the mechanical structure of the drive system, such as the existence of surface scars, grooves, or poor contact between the rolling elements inside the bearing and the inner and outer ring raceways, the rotational speed of the fabric winding roller will experience rapid up-and-down jumps in the short term. And as the fabric winding roller continues to rotate, the obtained rapid up-and-down jumps show a periodic change proportional to the rotational speed of the fabric winding roller.

[0025] Therefore, by analyzing the change characteristics of the rotational speed of the fabric winding roller, determining the fluctuation abnormal value, and thus judging whether there is an abnormality in the rotational speed of the fabric winding roller in a short time, the specific process is as follows: Divide the period from the start of the fabric winding process to the current moment into multiple time periods. In each time period, starting from each rotational speed data, form a window for each rotational speed data by taking each rotational speed data and the subsequent adjacent and continuous preset number of rotational speed data. Fit each rotational speed data and all the rotational speed data within its window to obtain a fitting curve. Take the cumulative sum of the change rates between all adjacent extreme values on the fitting curve as the fluctuation abnormal value within each rotational speed data window, which is used to characterize the local jump degree and jump frequency characteristics of the rotational speed data. If the change rate is larger, it means the local jump degree of the rotational speed data is larger, and the obtained fluctuation abnormal value is larger, indicating that the fabric winding roller is more disturbed by the wear of the mechanical structure of the drive system, and this rotational speed data is less valuable as a reference; on the contrary, if the change rate is smaller, it means the local jump degree of the rotational speed data is smaller, and the obtained fluctuation abnormal value is smaller, indicating that the fabric winding roller is less disturbed by the wear of the mechanical structure of the drive system, and this rotational speed data is more valuable as a reference.

[0026] 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, and the implementer can also set it according to the specific situation, and this embodiment does not make special restrictions.

[0027] It should be understood that in this embodiment, the calculation method of the change rate is: the ratio of the absolute value of the difference between each adjacent extreme value on the fitting curve to the corresponding time interval.

[0028] In addition, it should be supplemented that there are many commonly used fitting methods. In this embodiment, the least squares method is used to fit the rotational speed data. In the actual application process, the implementer can also use other fitting methods such as the polynomial function fitting method according to the specific situation. Regarding the selection of the fitting method, this embodiment does not make special restrictions. Among them, in this embodiment, whenever the fitting process is involved, the least squares fitting method is used. The least squares fitting method is a well-known technology, and the specific process of using it to fit the rotational speed data will not be elaborated here.

[0029] It should be noted particularly that in this embodiment, there is a situation where there are not enough adjacent and continuous rotational speed data after a rotational speed data. Therefore, for this situation, the adjacent and continuous rotational speed data before the rotational speed data is used to fill the gap.

[0030] Furthermore, as the fabric roll rotates, to avoid the situation where the fabric tension increases due to the constant rotational speed after the diameter of the fabric roll increases, which in turn affects the fabric rolling quality and the flatness of the fabric. Under normal circumstances, the rotational speed gradually decreases as the diameter of the fabric roll increases. The corresponding up-and-down rapid jump feature shows a periodic change proportional to the rotational speed of the fabric roll. Therefore, based on the above features, by analyzing the correlation between the average level and the fluctuation anomaly value of all rotational speed data within each rotational speed data window at each time period, the correlation index for each time period is determined to reflect whether the up-and-down rapid jump feature is proportional to the rotational speed, thereby determining whether there is an anomaly in the rotational speed data and whether adjustment is required. Specifically: In this embodiment, the mean value of all rotational speed data within each rotational speed data window at each time period is calculated, and the correlation coefficient between the mean value within the window of all rotational speed data at each time period and the fluctuation anomaly value is used as the correlation index for 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 rotational speed of the fabric roll. If the correlation coefficient is larger, it indicates that there is a strong correlation between the up-and-down rapid jump feature and the rotational speed of the fabric roll, that is, the larger the correlation index, the rotational speed data has no anomaly and no adjustment is required; on the contrary, if the correlation coefficient is smaller, it indicates that the correlation between the up-and-down rapid jump feature and the rotational speed of the fabric roll is weaker, that is, the smaller the correlation index, it indicates that the rotational speed data has an anomaly and needs to be adjusted.

[0031] It should be noted that there are many calculation methods for the correlation coefficient. In this embodiment, the Spearman correlation coefficient between the mean value within the window of all rotational speed data at each time period and the fluctuation anomaly value is used as the correlation coefficient between the mean value within the window of all rotational speed data at each time period and the fluctuation anomaly value. In the actual application process, the implementer can also use other correlation coefficient calculation methods such as the Pearson correlation coefficient according to the specific situation. Regarding the selection of the correlation coefficient calculation method, this embodiment does not make special restrictions.

[0032] Among them, the calculation method of the Spearman correlation coefficient is a well-known technology, and its specific calculation process will not be elaborated here.

[0033] So far, by analyzing the fluctuation anomaly value of the rotational speed data, it is judged whether there is an abnormal situation such as mechanical structure wear of the fabric roll, and by analyzing the correlation between the rotational speed data and the fluctuation anomaly value, it is judged whether there is an anomaly in the rotational speed data, so as to improve the accuracy of rotational speed adjustment, thereby improving the tension adjustment accuracy during the fabric winding process, keeping the tension constant, and further improving the fabric rolling quality and the flatness of the fabric.

[0034] 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.

[0035] 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.

[0036] 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: 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.

[0037] It should be noted that there are many methods to measure the difference between data. In this embodiment, the absolute value of the difference between all rotational speed data from the start of the fabric coiling process to the current moment and the corresponding fitted values on the rotational speed fitting curve is used as the difference between all rotational speed data at the current moment and the corresponding fitted values on the rotational speed fitting curve. In the actual application process, as other implementation manners, the implementer can also adopt other methods to measure the difference between data, such as the square or ratio of the difference, according to the specific situation. Regarding the selection of the method to measure the difference between data, no special restrictions are made in this embodiment.

[0038] It should be supplemented and explained that in this embodiment, for all content related to calculating the difference, the method of taking the absolute value of the difference is adopted.

[0039] Furthermore, the significant values with abnormal jumps and periodic characteristics also have similar change characteristics to the rotational speed curve of the cloth winding roller. Specifically, in the initial stage of the operation of the cloth winding machine, the speed of the cloth winding roller is relatively high, and its speed reduction rate is relatively fast. Correspondingly, the significant values with abnormal jumps and periodic characteristics are also relatively high, and their speed reduction rate is relatively fast. Correspondingly, the significant values with abnormal jumps and periodic characteristics are also relatively high and the speed reduction is relatively fast. After the diameter of the cloth roll becomes larger, the speed of the cloth winding roller becomes slower, and its speed reduction rate becomes slower. Correspondingly, the significant values with abnormal jumps and periodic characteristics also become lower and the reduction rate slows down.

[0040] Therefore, fit the relevant indices for all time periods, analyze the differences between all relevant indices and the fitting results, and determine the second difference degree at the current moment. Specifically: The curve obtained by fitting the relevant indices for all time periods from the start of the fabric coiling process to the current moment is denoted as the relevant curve. The result of accumulating the differences between all relevant indices and the corresponding fitted values on the relevant curve is used as the second difference degree at the current moment, which reflects the non-smooth change degree of the correlation between the up-and-down jump characteristics and the rotational speed data under the influence of mechanical structure wear. If the difference between the relevant index and the corresponding fitted value is larger, it indicates that the change of the correlation between the up-and-down jump characteristics and the rotational speed data is more non-smooth, that is, the second difference degree is larger, indicating that the rotational speed of the cloth winding roller is more disturbed by mechanical structure wear, etc. On the contrary, if the difference between the relevant index and the corresponding fitted value is smaller, it indicates that the change of the correlation between the up-and-down jump characteristics and the rotational speed data is smoother, that is, the second difference degree is smaller, indicating that the rotational speed of the cloth winding roller is less disturbed by mechanical structure wear, etc.

[0041] Further, determine the anomaly coefficient at the current moment by combining the second difference degree at the current moment and the first difference degree. Specifically: The result of positively fusing the first difference degree and the second difference degree at the current moment is used as the anomaly coefficient at the current moment, which is used to characterize the smoothness of the winding roller speed and the change of the correlation. If the anomaly coefficient is larger, it indicates that the winding roller speed and the change of the correlation are less smooth, that is, the corresponding first and second difference degrees are both larger. On the contrary, if the anomaly coefficient is smaller, it indicates that the winding roller speed and the change of the correlation are more smooth, that is, the corresponding first and second difference degrees are both smaller.

[0042] It should be understood that positive fusion means combining two or more indicators through addition, multiplication or other methods in order to obtain a comprehensive indicator, so as to more comprehensively and accurately evaluate a certain phenomenon or problem. This fusion method is not limited to simple arithmetic operations, but can also include more complex statistical models and analysis methods, which can be selected by the implementer according to the specific situation, and this embodiment does not make special restrictions.

[0043] Preferably, in this embodiment, the sum value of the first difference degree and the second difference degree at the current moment is used as the anomaly coefficient at the current moment.

[0044] So far, by fitting the rotational speed data and related indices during the fabric winding process, analyzing the differences from the fitting curves of the rest, calculating the first and second difference degrees, and positively fusing the two to obtain the anomaly coefficient, this anomaly coefficient is used to characterize the smoothness of the winding roller speed and its correlation change, so as to timely detect whether there are abnormal situations such as mechanical structure wear in the winding machine, improve the control accuracy of the tension during the fabric winding process to ensure the tension is constant, and further improve the winding quality and fabric flatness.

[0045] Step S4: By analyzing the complexity of all tension data from the start of the fabric winding process to the current moment, determine the tension complexity at the current moment, and combine the anomaly coefficient to determine the tension anomaly value at the current moment, so as to control the rotational speed of the winding roller during the fabric winding process at the current moment.

[0046] In addition to the influence of the rotational speed of the winding roller, the non-uniformity of the raw material properties and the change of environmental humidity will also interfere with the tension during the fabric winding process, resulting in irregular random fluctuations in the tension data during fabric winding. To reduce the random fluctuations of the fabric tension, it is necessary to timely adjust the rotational speed of the winding roller. When the random fluctuation degree of the tension data is larger and the influence of the rotational speed of the winding roller is greater, the response rate of the system regulation should be faster. Therefore, combining the fluctuation state characteristics of the fabric tension and the abnormal characteristics of the non-smooth change of the winding roller speed, that is, by analyzing the complexity of all tension data from the start of the fabric winding process to the current moment, determine the tension complexity at the current moment, and combine the anomaly coefficient to determine the tension anomaly value at the current moment, specifically: The fractal dimension of all the tension data from the start of the fabric coiling process to the current moment is taken as the tension complexity at the current moment, which reflects the random fluctuation degree of the tension data during the fabric coiling process. The larger the fractal dimension of the tension data, the greater the random fluctuation degree of the tension data during the fabric coiling process. Conversely, if the fractal dimension of the tension data is smaller, it indicates that the random fluctuation degree of the tension data during the fabric coiling process is smaller.

[0047] Among them, the calculation method of the fractal dimension is a well-known technology, and its specific calculation process will not be elaborated here.

[0048] Furthermore, based on the tension complexity and the anomaly coefficient at the current moment, the tension anomaly value at the current moment is determined. Specifically: The tension anomaly value at the current moment The expression is: ; In the formula, represents the anomaly coefficient at the current moment; represents the tension complexity at the current moment.

[0049] From the tension anomaly value at the current moment, it can be understood that if the anomaly coefficient is larger, it indicates that the rotation speed of the cloth winding roller and the change of the correlation are less stable, the rotation speed of the cloth winding roller is more interfered by mechanical wear, the possibility of tension anomaly is greater, and the greater the tension complexity, the greater the random fluctuation degree of the tension data, and the greater the possibility of tension anomaly, and the corresponding tension anomaly value is larger; conversely, if the anomaly coefficient is smaller, it indicates that the rotation speed of the cloth winding roller and the change of the correlation are more stable, the rotation speed of the cloth winding roller is normal, the possibility of tension anomaly is smaller, and the smaller the tension complexity, the smaller the random fluctuation degree of the tension data, the smaller the possibility of tension anomaly, and the corresponding tension anomaly value is smaller.

[0050] Preferably, the schematic diagram of the process for extracting the tension anomaly value provided in this embodiment is as Figure 2 shown.

[0051] Furthermore, according to the tension anomaly value, the rotation speed of the cloth winding roller is regulated by using the control system in the cloth winding machine to ensure the constancy of the tension during fabric coiling. Specifically: Based on the tension anomaly 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, thereby controlling the rotation speed of the cloth winding roller. Specifically: The gain coefficient at the current moment The expression is: ; In the formula, , respectively represent the preset reference value and the preset correction value; represents the tension anomaly value at the current moment; norm( ) represents the normalization function; Take the gain coefficient at the current moment as the gain coefficient in the sliding mode variable structure of the motor during the fabric coiling process to control the rotation speed of the fabric coiling roller.

[0052] It should be noted that the values of the preset reference value and the preset correction value are both artificially set. The preset reference value and the preset correction value are both used to regulate the gain coefficient. Since the value range of the gain coefficient is [-7, -2], in this embodiment, the value of the preset reference value is set to -7, and the value of the preset correction value is set to 5. In the actual application process, the implementer can also set them according to the specific situation by himself / herself, and this embodiment does not make special restrictions.

[0053] Based on the same inventive concept as the above method, the embodiment of the present application also provides a fabric coiling machine control system for automotive 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 methods for controlling a fabric coiling machine for automotive interior fabric production.

[0054] It should be noted that: the above sequence of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0055] Each embodiment in this specification is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present application shall be included in the protection scope of the present application.

Claims

1. A control method for a cloth winding machine for automotive interior fabric production, characterized in that, The method includes the following steps: Obtain the tension data and the rotational speed data of the cloth winding roller in real time during the fabric winding process; Divide the period from the start of the fabric winding process to the current moment into multiple time periods. Within each time period, fit each rotational speed data and all rotational speed data within its window. By analyzing the change rate between all adjacent extreme values on the fitting curve, determine the fluctuation outlier within each rotational speed data window; by analyzing the correlation between the average level of all rotational speed data within each rotational speed data window and the fluctuation outlier in each time period, determine the correlation index for each time period; Fit all rotational speed data from the start of the fabric winding process to the current moment to obtain a rotational speed fitting curve, and analyze the difference between all rotational speed data and the fitting values on the rotational speed fitting curve to determine the first difference degree at the current moment; fit the correlation indexes of all time periods, analyze the difference between all correlation indexes and the fitting results, determine the second difference degree at the current moment, and combine the first difference degree to determine the anomaly coefficient at the current moment; By analyzing the complexity of all tension data from the start of the fabric winding process to the current moment, determine the tension complexity at the current moment, and combine the anomaly coefficient to determine the tension outlier at the current moment, so as to control the rotational speed of the cloth winding roller during the fabric winding process at the current moment.

2. The cloth rewinder control method for automotive interior fabric production according to claim 1, wherein The fluctuation outlier within each rotational speed data window is the sum of the change rates between all adjacent extreme values on the fitting curve within the window of each rotational speed data.

3. The cloth rewinding machine control method for automotive interior fabric production according to claim 1, characterized in that, The method for determining the correlation index for each time period is as follows: Calculate the mean value of all rotational speed data within each rotational speed data window in each time period, and use the correlation coefficient between the mean value within the window of all rotational speed data in each time period and the fluctuation outlier as the correlation index for each time period.

4. The control method of the cloth winder for automotive interior fabric production according to claim 1, characterized in that, The first difference degree at the current moment is the sum of the differences between all rotational speed data from the start of the fabric winding process to the current moment and the corresponding fitting values on the rotational speed fitting curve.

5. The control method of the cloth rewinder for automotive interior fabric production according to claim 1, characterized in that The method for determining the second difference degree at the current moment is as follows: Denote the curve obtained by fitting the correlation indexes of all time periods from the start of the fabric winding process to the current moment as the correlation curve, and use the result of accumulating the differences between all correlation indexes of all time periods and the corresponding fitting values on the correlation curve as the second difference degree at the current moment.

6. The cloth rewinder control method for automotive interior fabric production according to claim 1, characterized in that, The anomaly coefficient at the current moment is the result of the positive fusion of the first difference degree and the second difference degree at the current moment.

7. The control method of the 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 from the start of the fabric winding process to the current moment.

8. The cloth rewinder control method for automotive interior fabric production according to claim 1, characterized in that The expression for the tension anomaly value at the current moment is as follows: ; In the formula, represents the tension anomaly value at the current moment; represents the anomaly coefficient at the current moment; represents the tension complexity at the current moment.

9. The winding machine control method for automotive interior fabric production according to claim 1, characterized in that, The control of the rotational 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 as follows: ; In the formula, , respectively represent the preset reference value and the preset correction value; represents the tension anomaly value at the current moment; norm( ) represents the normalization function; Use the gain coefficient at the current moment as the gain coefficient in the sliding mode variable structure of the motor during the fabric winding process to control the rotational speed of the cloth winding roller.

10. The coiler control system for automotive interior fabric production includes 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 cloth winding machine control method for automotive interior fabric production according to any one of claims 1-9.

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