A cutting control system for elastic band

Abstract

The present invention discloses a cutting control system for an elastic band, and relates to the field of cutting control technology. The system comprises: an elastic band raw material information acquisition module, which is used to obtain elastic band raw material information; a stretching tension threshold acquisition module, which is used to perform tension threshold analysis and obtain stretching tension threshold; a feed roller constraint speed generation module, which is used to generate a feed roller constraint speed; a cutting constraint speed acquisition module, which is used to obtain a cutting constraint speed; an elastic band cutting length configuration module, which is used to configure the elastic band cutting length; an elastic band cutting cycle configuration module, which is used to configure the elastic band cutting cycle; and an elastic band cutting control module, which is used for elastic band cutting control. The system solves the technical problems existing in the existing elastic band cutting control, such as the lack of quantitative configuration of the feed roller speed, the difficulty in accurately controlling the elastic band tension, and the poor accuracy and reliability of the cutting control, and achieves the technical effect of improving the accuracy and reliability of the elastic band cutting control.

Description

Technical Field

[0001] The present application relates to the technical field related to cutting control, and in particular to a cutting control system for an elastic band. Background Art

[0002] With the rapid development of modern manufacturing, the demand for high-precision and high-efficiency production is growing. In the textile, rubber, plastic and other industries, elastic bands are a common material and are widely used in various products such as clothing, sports equipment, medical equipment, etc. However, the cutting process of elastic bands often faces many challenges, such as tension control, cutting accuracy, production efficiency and other issues. The traditional elastic band cutting method mainly relies on simple mechanical control and setting the feed roller speed to control the tension of the elastic band, which is difficult to ensure the cutting accuracy and stability. Due to the elasticity and retraction of the elastic band material itself, it is easy to cause the cutting quality to decline or even damage the material due to uneven tension or improper control during the cutting process, affecting the stability and reliability of the cutting results.

[0003] Therefore, in the current technology related to cutting control of elastic bands, there is a technical problem that the speed of the feed roller is not quantitatively configured, making it difficult to accurately control the tension of the elastic band, which in turn leads to poor accuracy and reliability of cutting control. Summary of the invention

[0004] The present application provides an elastic band cutting control system, which adopts tension threshold analysis, speed optimization and other technical means to solve the technical problem that the existing elastic band cutting control has no quantitative configuration of the feed roller speed, making it difficult to accurately control the elastic band tension, thereby resulting in poor accuracy and reliability of the cutting control, thereby achieving the technical effect of improving the accuracy and reliability of the elastic band cutting control.

[0005] The present application provides an elastic band cutting control system, the system comprising: an elastic band raw material information acquisition module, used to obtain elastic band raw material information, wherein the elastic band raw material information comprises elastic band width information, elastic band thickness information, feed distance information, elastic band raw material type information, the feed distance information represents the distance between a feed roller and a feed roller, the feed roller is driven by a motor, and the feed roller rotates as the feed roller rotates; a stretching tension threshold acquisition module, used to perform tension threshold analysis on the elastic band according to the elastic band width information, the elastic band thickness information, and the elastic band raw material type information, to obtain a stretching tension threshold; a feed roller constraint speed generation module, used to generate a tension threshold value based on the stretching tension threshold, The module optimizes the feed roller speed according to the elastic band width information, the elastic band thickness information, the feed distance information, and the elastic band raw material type information to generate a feed roller constraint speed; a cutting constraint speed acquisition module is used to optimize the cutting speed according to the elastic band raw material type and the cutting blade model to obtain the cutting constraint speed; an elastic band cutting length configuration module is used to configure the elastic band cutting length; an elastic band cutting cycle configuration module is used to calculate and configure the elastic band cutting cycle according to the elastic band cutting length in combination with the feed roller constraint speed; an elastic band cutting control module is used to control the elastic band cutting according to the elastic band cutting cycle, the feed roller constraint speed, and the cutting constraint speed.

[0006] In a possible implementation, the stretch tension threshold acquisition module further performs the following processing: collecting elastic band stretch test information according to the elastic band width information, the elastic band thickness information, and the elastic band raw material type information, wherein the elastic band stretch test information includes a set of stretch critical tension record values; clustering the set of stretch critical tension record values ​​based on tension consistency deviation to generate multiple clusters of stretch critical tension record values; traversing the multiple clusters of stretch critical tension record values ​​to perform center tension analysis to generate multiple center tension record values; performing weighted mean analysis on the multiple center tension record values ​​according to the proportion of the number of clusters within multiple clusters of the multiple clusters of stretch critical tension record values ​​to generate the stretch tension threshold.

[0007] In a possible implementation, the stretching tension threshold acquisition module also performs the following processing: extracting the first stretching critical tension record value of the first cluster of stretching critical tension record values ​​of the multiple clusters of stretching critical tension record values; calculating the mean of the deviation sum of the first stretching critical tension record value and other tension record values ​​in the cluster, and setting it as the cluster distribution parameter; calculating the mean of the first cluster distribution parameter; calculating the mean of the first cluster distribution parameter and the cluster distribution parameter to generate the centrality of the first stretching critical tension record value, and adding it to the first cluster centrality set; extracting the minimum value of the first cluster centrality set, sorting the first cluster center tension record value from the first cluster stretching critical tension record value, and adding it to the multiple center tension record values.

[0008] In a possible implementation, the feed roller constraint speed generation module also performs the following processing: based on the elastic band raw material type information, activating the tension prediction model, wherein the tension prediction model is trained and generated with the elastic band raw material type information as a constraint, the elastic band width information, the elastic band thickness information, the feed distance information and the feed roller speed as input variables, and the elastic band tension value as an output variable; based on the stretching tension threshold, configuring the first convergence constraint tension interval; constructing an energy consumption optimization fitness function, wherein the energy consumption optimization fitness function is the inverse of the feed roller speed, which is used to characterize the energy consumption; according to the first convergence constraint tension interval and the energy consumption optimization fitness function, combined with the tension prediction model, optimizing the feed roller speed, and outputting the feed roller constraint speed when the first convergence constraint tension interval is met and the preset number of iterations is met.

[0009] In a possible implementation, the feed roller constrained speed generation module also performs the following processing: randomly taking a value according to the feed roller speed value interval to obtain a first feed roller speed; fitting the first feed roller speed, the elastic band width information, the elastic band thickness information, and the feed distance information through the tension prediction model to generate a first predicted tension; when the first predicted tension belongs to the first convergence constraint tension interval, adding the first feed roller speed to the speed set to be sorted; when the preset number of iterations is met, sorting the speed set to be sorted according to the energy consumption optimization fitness function to generate the feed roller constrained speed.

[0010] In a possible implementation, the cutting constraint speed acquisition module also performs the following processing: randomly taking a value according to a cutting speed value interval to obtain a first cutting speed; collecting a blade cutting history record of the elastic band material type being cut by the cutting blade model at the first cutting speed, wherein the blade cutting history record includes cutting section flatness record data; calculating a variance parameter of the cutting section flatness record data and setting it as a first cutting speed evaluation factor; calculating a mean of the cutting section flatness record data and setting it as a second cutting speed evaluation factor; when the second cutting speed evaluation factor is greater than or equal to a flatness threshold, and the first cutting speed evaluation factor is less than or equal to a convergence variance threshold, setting the first cutting speed to the cutting constraint speed.

[0011] In a possible implementation, the elastic band cutting control module also performs the following processing: selecting a number of elastic band samples, cutting and testing them based on the cutting constraint speed, obtaining a number of cutting section size deviations and a number of cutting section flatness deviations, the cutting section size deviation being the area ratio of the size deviation region, and the cutting section flatness deviation being the deviation between the detected flatness and the expected flatness; counting the ratio of the several cutting section size deviations being greater than or equal to the first deviation threshold, and setting it as the first fluctuation coefficient; counting the ratio of the several cutting section flatness deviations being greater than or equal to the second deviation threshold, and setting it as the second fluctuation coefficient; when the first fluctuation coefficient and the second fluctuation coefficient are both less than or equal to the fluctuation coefficient threshold, performing elastic band cutting control according to the elastic band cutting cycle, the feed roller constraint speed and the cutting constraint speed.

[0012] In a possible implementation, the elastic band cutting control module further performs the following processing: when the first fluctuation coefficient and / or the second fluctuation coefficient are both greater than the fluctuation coefficient threshold, a cutting blade maintenance instruction is generated and sent to the management end.

[0013] It is intended to obtain elastic band raw material information through an elastic band cutting control system proposed in the present application, wherein the elastic band raw material information includes elastic band width information, elastic band thickness information, feed distance information, and elastic band raw material type information, wherein the feed distance information represents the distance between a feed roller and a feed roller, and the feed roller is driven by a motor, and the feed roller rotates as the feed roller rotates; perform tension threshold analysis on the elastic band according to the elastic band width information, the elastic band thickness information, and the elastic band raw material type information to obtain a stretching tension threshold; and perform a tension threshold analysis on the elastic band according to the stretching tension Threshold, based on the elastic band width information, the elastic band thickness information, the feed distance information, and the elastic band raw material type information, optimize the feed roller speed to generate the feed roller constraint speed; optimize the cutting speed according to the elastic band raw material type and the cutting blade model to obtain the cutting constraint speed; configure the elastic band cutting length; calculate according to the elastic band cutting length and the feed roller constraint speed to configure the elastic band cutting cycle; control the elastic band cutting according to the elastic band cutting cycle, the feed roller constraint speed, and the cutting constraint speed. The technical problem of the existing elastic band cutting control that the feed roller speed is not quantitatively configured, it is difficult to accurately control the elastic band tension, and thus the accuracy and reliability of the cutting control are poor is solved, and the technical effect of improving the accuracy and reliability of the elastic band cutting control is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of the structure of a cutting control system for an elastic band provided in an embodiment of the present application;

[0016] Figure 2 A schematic diagram of the execution process of a stretching tension threshold value obtaining module in a cutting control system of an elastic band provided in an embodiment of the present application.

[0017] Explanation of the reference numerals: elastic band raw material information obtaining module 10, stretching tension threshold obtaining module 20, feed roller constraint rotation speed generating module 30, cutting constraint speed obtaining module 40, elastic band cutting length configuring module 50, elastic band cutting cycle configuring module 60, elastic band cutting control module 70. DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0021] The present application embodiment provides a cutting control system for an elastic band, such as Figure 1 As shown, the system comprises:

[0022] The elastic band raw material information acquisition module 10 is used to obtain the elastic band raw material information, wherein the elastic band raw material information includes elastic band width information, elastic band thickness information, feed distance information, elastic band raw material type information, the feed distance information represents the distance between the feed roller and the feed roller, the feed roller is driven by a motor, and the feed roller rotates as the feed roller rotates. Elastic band raw material information refers to various information related to the raw materials required for the production of elastic bands, including elastic band width information, elastic band thickness information, and feed distance information. Specifically, the width of the elastic band is an important parameter that needs to be controlled in the manufacturing process. Common elastic band width specifications include 3mm, 4mm, 5mm, 6mm, 8mm, 10mm, 12mm, etc.; the thickness of the elastic band affects the elasticity and transparency of the elastic band. Common thickness specifications include 0.12mm, 0.16mm, 0.20mm, 0.30mm, etc.; the feed distance information refers to the distance between the feed roller and the feed roller; the elastic band raw material type information refers to the type of raw material used to manufacture the elastic band, such as natural latex or synthetic rubber. Different raw material types may have different physical and chemical properties. Among them, the feed roller is driven by a motor and is responsible for feeding the raw material into the production line. The feed roller rotates with the rotation of the feed roller, playing a role in assisting the transmission of raw materials, ensuring the stable transmission of raw materials on the production line, and reducing production failures caused by poor raw material transmission.

[0023] The stretching tension threshold acquisition module 20 is used to perform tension threshold analysis on the elastic band according to the elastic band width information, the elastic band thickness information, and the elastic band raw material type information to obtain the stretching tension threshold. Based on the obtained elastic band information, a mechanical model is established to simulate the mechanical behavior of the elastic band during the stretching process. Specifically, according to the width, thickness and raw material type information of the elastic band, various parameters of the model, such as elastic modulus, yield strength, Poisson's ratio, etc., are set, and the model is simulated and calculated to simulate the stress distribution and deformation of the elastic band under different stretching conditions. According to the simulation results, the maximum tolerable tension of the elastic band under different stretching conditions, that is, the stretching tension threshold, is determined to ensure that during the production process, the elastic band will not be damaged or fail due to excessive stretching.

[0024] The feed roller constraint speed generating module 30 is used to optimize the feed roller speed according to the stretching tension threshold, based on the elastic band width information, the elastic band thickness information, the feed distance information, and the elastic band raw material type information, and generate the feed roller constraint speed. According to the tensile tension threshold and the elastic band raw material information, the feed roller speed is optimized and a suitable feed roller constraint speed is generated to ensure that the elastic band maintains stable performance and quality in the cutting and processing links. Specifically, a mathematical model describing the elastic band transmission process is established based on the elastic band width information, elastic band thickness information, feed distance information, and elastic band raw material type information, and an objective function is set to reflect the relationship between the feed roller speed and the tensile tension. That is, the setting of the objective function does not make the feed roller speed reach the optimal value (such as maximizing production efficiency, minimizing energy consumption, etc.) under the premise of meeting the tensile tension threshold. The tensile tension threshold, feed distance, and elastic band raw material type are used as constraints to limit the range of the feed roller speed. The objective function is solved by an optimization algorithm (such as a genetic algorithm, a particle swarm algorithm, etc.) to find the optimal feed roller speed that meets the constraints. Finally, the optimal feed roller speed is obtained, which is the feed roller constraint speed. This speed ensures that the elastic band maintains stable tension and transmission speed during transmission, while meeting the requirements of production efficiency and energy consumption.

[0025] The cutting constraint speed acquisition module 40 is used to optimize the cutting speed according to the elastic band material type and the cutting blade model to obtain the cutting constraint speed. The cutting speed is optimized according to the elastic band material type and the cutting blade model to obtain the best cutting constraint speed to ensure the smooth progress of the cutting process. Specifically, based on the elastic band material type and the cutting blade model, a mathematical model describing the cutting process is established. The model can reflect the relationship between factors such as cutting speed, cutting quality, and blade life. The objective function is usually set to maximize the cutting speed or maximize the blade life under the premise of meeting the cutting quality requirements. For example, the objective function can be set to maximize the cutting efficiency (cutting length / cutting time) while ensuring the smoothness and burr-free of the cutting surface. The constraint conditions include the upper and lower limits of the cutting speed (based on the cutting speed). The objective function is solved by an optimization algorithm (such as a genetic algorithm, a particle swarm algorithm, etc.) to find the optimal cutting speed that meets the constraints, based on the blade model and raw material characteristics), cutting quality standards (such as smoothness, burr-free, etc.) and blade life. In this process, the influence of the raw material type on the cutting speed (such as hard raw materials require a lower cutting speed to prevent blade wear) and the restrictions on the cutting speed imposed by the blade model (such as some blade models can only work within a specific speed range) are considered. The optimal cutting speed obtained in the end is the cutting constraint speed, which is the cutting speed that can maximize the cutting efficiency or blade life while meeting the cutting quality requirements.

[0026] The elastic band cutting length configuration module 50 is used to configure the elastic band cutting length. Configuring the elastic band cutting length means setting or adjusting the specific length of the elastic band to be cut according to actual needs or specification requirements during the elastic band production process.

[0027] The elastic band cutting cycle configuration module 60 is used to calculate and configure the elastic band cutting cycle according to the elastic band cutting length and the feed roller constraint speed. The elastic band cutting cycle is calculated and configured according to the elastic band cutting length and the feed roller constraint speed. Specifically, the feed speed is calculated according to the feed roller constraint speed and the width of the elastic band. It is usually calculated by the following formula: feed speed (v) = feed roller circumference × feed roller speed, where the feed roller circumference depends on the feed roller diameter. Assuming that the feed roller diameter is D (meters), the feed roller circumference = π × D, and the feed speed = π × D × feed roller speed. The cutting cycle refers to the time interval from the start of cutting one elastic band to the start of cutting the next elastic band. The formula is calculated as follows: cutting cycle (T) = cutting speed / feed speed, that is, the cutting cycle is equal to the elastic band cutting length divided by the feed speed.

[0028] The elastic band cutting control module 70 is used to control the elastic band cutting according to the elastic band cutting cycle, the feed roller constraint speed and the cutting constraint speed. According to the feed roller constraint speed, the feed roller drive motor is controlled to adjust the feed roller speed to ensure that the elastic band enters the cutting area at a constant speed. The cutting cycle of the elastic band is monitored by a sensor or a timer. When the predetermined cutting cycle is reached, the cutting mechanism is triggered to perform the cutting action. According to the cutting constraint speed, the cutting speed of the cutting mechanism is adjusted, for example, by controlling the driving system of the cutting mechanism (such as a motor, a cylinder, etc.), to ensure that the cutting speed is within the allowable range, and to avoid excessive or excessive slowness causing a decrease in cutting quality. During the cutting process, the feed roller speed and the cutting speed are adjusted synchronously according to the actual situation. If the feed roller speed is too fast, the cutting mechanism may not be able to cut off the elastic band in time; if the cutting speed is too fast, the cutting quality may be unstable. These parameters are monitored and adjusted in real time through the feedback control system to ensure the stability and accuracy of the cutting process.

[0029] According to an embodiment of the present invention, a cutting control system for an elastic band is used to solve the technical problem that it is difficult to monitor and accurately control the key parameters in the extrusion process in real time in the existing engineering material extrusion control, which leads to unstable product quality and low production efficiency, and realizes automatic adjustment of extrusion parameters, thereby achieving the technical effect of improving the stability of product quality and production efficiency. A cutting control system for an elastic band includes: an elastic band raw material information acquisition module 10, a stretching tension threshold acquisition module 20, a feed roller constraint speed generation module 30, a cutting constraint speed acquisition module 40, an elastic band cutting length configuration module 50, an elastic band cutting cycle configuration module 60, and an elastic band cutting control module 70.

[0030] The specific configuration of the stretching tension threshold value obtaining module 20 will be described in detail below. Figure 2 As shown, the stretching tension threshold acquisition module 20 may further include: collecting the stretching test information of the elastic band according to the elastic band width information, the elastic band thickness information, and the elastic band raw material type information, wherein the elastic band stretching test information includes a set of stretching critical tension record values. According to the information such as the width, thickness and raw material type of the elastic band, the elastic band is subjected to a stretching test, and the tension data of the elastic band under different stretching states is recorded, with particular attention paid to the stretching critical tension, that is, the tension value at which the elastic band is about to break or obviously loses elasticity when stretched to a certain extent, and these stretching critical tension values ​​are combined into a record value set. It also includes, based on the tension consistency deviation, clustering the stretching critical tension record value set to generate multiple clusters of stretching critical tension record values. Since different samples or the same sample may have deviations in tension values ​​under different test conditions, it is necessary to perform cluster analysis on the set of stretch critical tension record values. Specifically, algorithms such as K-means and hierarchical clustering are used, and based on the tension consistency deviation (i.e., the degree of difference between tension values) as the basis for clustering, similar (i.e., similar tension values) stretch critical tension record values ​​are grouped together to form multiple clusters, i.e., multiple clusters of stretch critical tension record values.

[0031] The stretch tension threshold acquisition module 20 also includes traversing the multiple clusters of stretch critical tension record values ​​to perform central tension analysis and generate multiple central tension record values. Traversing each cluster (i.e., each group of similar stretch critical tension record values) to calculate the central tension value of the cluster, the central tension value can usually be obtained by calculating the mean, median or mode of all record values ​​in the cluster, representing the average or typical stretch critical tension of the elastic band samples in the cluster. It also includes performing weighted mean analysis on the multiple central tension record values ​​according to the multiple cluster quantity ratios of the multiple clusters of stretch critical tension record values ​​to generate the stretch tension threshold. The number of stretch critical tension record values ​​of different clusters may be different, that is, some clusters contain more sample data, while some clusters contain less. Specifically, the central tension record values ​​are weighted according to the cluster quantity ratio (i.e., the ratio of the number of record values ​​contained in each cluster to the total number of record values) to comprehensively consider the information of all clusters. The result of the weighted mean analysis is a stretch tension threshold that integrates the information of all clusters, i.e., the stretch tension threshold, which is used to judge whether the elastic band is qualified or the performance is good or bad.

[0032] The specific configuration of the stretch tension threshold value acquisition module 20 will be described in detail below. The stretch tension threshold value acquisition module 20 may further include: extracting the first stretch critical tension record value of the first cluster of stretch critical tension record values ​​of the multiple clusters of stretch critical tension record values. The first cluster of stretch critical tension record values ​​refers to any cluster of the multiple clusters of stretch critical tension record values, and the first stretch critical tension record value is a stretch critical tension record value randomly extracted from the first cluster of stretch critical tension record values. It also includes calculating the mean of the sum of the deviations of the first stretch critical tension record value and other tension record values ​​in the cluster, and setting it as the cluster distribution parameter. For each stretch critical tension record value in the first cluster (except the first stretch critical tension record value that has been selected), calculate its deviation from the first stretch critical tension record value (i.e., the difference between the two), add up all the calculated deviations, and calculate the mean, which represents the average deviation of the first stretch critical tension record value and other record values ​​in the cluster, called the cluster distribution parameter. It also includes calculating the mean of the first cluster distribution parameter. The mean of the sum of the deviations between each critical tension record value and other record values ​​in the cluster is repeatedly calculated to obtain multiple intra-cluster distribution parameters, and then the mean of these intra-cluster distribution parameters is calculated to obtain the mean of the first intra-cluster distribution parameters.

[0033] The stretch tension threshold acquisition module 20 also includes: calculating the mean of the first cluster distribution parameter and the cluster distribution parameter, generating the first stretch critical tension record value centrality, and adding it to the first cluster centrality set. Using the first cluster distribution parameter mean and the cluster distribution parameter of the first stretch critical tension record value, calculate the difference or ratio between the two, generate a value representing the degree of centrality of the first stretch critical tension record value in the cluster, called the first stretch critical tension record value centrality, and add this centrality value to the first cluster centrality set. It also includes: extracting the minimum value of the first cluster centrality set, sorting the first cluster central tension record value from the first cluster stretch critical tension record value, and adding it to the multiple central tension record values. Extract the minimum value from the first cluster centrality set, the stretch critical tension record value corresponding to this minimum value is most concentrated in the cluster, that is, the deviation from other record values ​​is the smallest, it is considered to represent the central tension of the cluster, and this stretch critical tension record value is used as the central tension record value of the first cluster, and added to the multiple central tension record value sets.

[0034] The specific configuration of the feed roller constraint speed generation module 30 will be described in detail below. The feed roller constraint speed generation module 30 may further include: based on the elastic band raw material type information, activating a tension prediction model, wherein the tension prediction model is trained and generated with the elastic band raw material type information as a constraint, the elastic band width information, the elastic band thickness information, the feed distance information and the feed roller speed as input variables, and the elastic band tension value as an output variable. According to the type of elastic band raw material currently used, the corresponding tension prediction model is activated, and the tension prediction model accepts the raw material type, width, thickness, feed distance and feed roller speed of the elastic band as input, and then outputs the predicted elastic band tension value, which can more accurately predict the tension of the elastic band under given process conditions. It also includes, based on the stretching tension threshold, configuring a first convergence constraint tension interval. Usually, a tension interval is set based on the stretching tension threshold, plus or minus a safety margin, that is, the first convergence constraint tension interval, to ensure product quality and production stability.

[0035] The feed roller constraint speed generation module 30 also includes constructing an energy consumption optimization fitness function, wherein the energy consumption optimization fitness function is the inverse of the feed roller speed, which is used to characterize the energy consumption. In the production process, in addition to considering tension control, energy consumption optimization also needs to be considered, because the feed roller speed is an important factor affecting energy consumption, so energy consumption optimization is achieved by adjusting the feed roller speed. Specifically, the energy consumption optimization fitness function is used to evaluate the energy consumption. For example, the inverse of the feed roller speed is selected as the fitness function, because the slower the feed roller speed, the lower the energy consumption is generally, so energy consumption optimization can be achieved by minimizing the fitness function (i.e., maximizing the inverse of the feed roller speed). It also includes optimizing the feed roller speed according to the first convergence constraint tension interval and the energy consumption optimization fitness function, combined with the tension prediction model, and outputting the feed roller constraint speed when the first convergence constraint tension interval is met and the preset number of iterations is met. The tension prediction model is used in combination with the current process parameters (such as elastic band width, thickness, feed distance and feed roller speed) to predict the tension value of the elastic band. The predicted tension value is compared with the first convergence constraint tension interval. If the predicted value exceeds this interval, the feed roller speed needs to be adjusted to bring the predicted value back within the interval. At the same time, the energy consumption optimization fitness function needs to be considered, that is, by gradually adjusting the feed roller speed and observing the changes in the tension prediction value and the energy consumption optimization fitness function, the energy consumption can be reduced as much as possible. When the predicted value meets the first convergence constraint tension interval and reaches the preset number of iterations, it is considered that the optimal feed roller speed, that is, the feed roller constraint speed, has been found.

[0036] The specific configuration of the feed roller constraint speed generation module 30 will be described in detail below. The feed roller constraint speed generation module 30 may further include: randomly taking a value according to the feed roller speed value interval to obtain a first feed roller speed. Randomly select a value within the feed roller speed value interval as the initial feed roller speed, recorded as the first feed roller speed. It also includes fitting the first feed roller speed, the elastic band width information, the elastic band thickness information, and the feed distance information through the tension prediction model to generate a first predicted tension. Using the trained tension prediction model, the first feed roller speed, the elastic band width information, the elastic band thickness information, and the feed distance information are used as input variables to calculate the predicted tension value of the elastic band under given process conditions, recorded as the first predicted tension.

[0037] The feed roller constraint speed generation module 30 also includes, when the first predicted tension belongs to the first convergence constraint tension interval, adding the first feed roller speed to the speed set to be sorted. Compare the first predicted tension with the first convergence constraint tension interval. If the first predicted tension meets the condition (i.e., belongs to the first convergence constraint tension interval), then add the first feed roller speed to a speed set to be sorted, and this set is used to store all speed values ​​that meet the tension requirements. It also includes, when the preset number of iterations is met, sorting the speed set to be sorted according to the energy consumption optimization fitness function to generate the feed roller constraint speed. Repeat the above steps of random value selection, tension prediction and judgment until the preset number of iterations is reached, and the speed set to be sorted contains multiple speed values ​​that meet the tension requirements. These speed values ​​are evaluated according to the energy consumption optimization fitness function (such as the inverse of the feed roller speed), and the speed value with the highest fitness (i.e., the speed value with the lowest energy consumption) is selected as the final feed roller constraint speed.

[0038] The specific configuration of the cutting constraint speed acquisition module 40 will be described in detail below. The cutting constraint speed acquisition module 40 may further include: randomly taking values ​​according to the cutting speed value interval to obtain a first cutting speed. The first cutting speed is a speed value randomly selected within the cutting speed value interval. It also includes collecting the blade cutting history record of the elastic band material type being cut by the cutting blade model at the first cutting speed, wherein the blade cutting history record includes the cutting section flatness record data. Collecting the history record of cutting the elastic band material using a specific blade model at a known first cutting speed, including the cutting section flatness record data, that is, the data set of the section flatness obtained after multiple cuttings. It also includes calculating the variance parameter of the cutting section flatness record data and setting it as the first cutting speed evaluation factor. Calculating the variance of the cutting section flatness record data reflects the discreteness of the data set, that is, the fluctuation of the cutting section flatness. This variance parameter is set as the first cutting speed evaluation factor to evaluate the stability of the cutting speed.

[0039] The cutting constraint speed acquisition module 40 also includes calculating the mean of the cutting section flatness record data and setting it as the second cutting speed evaluation factor. The mean of the cutting section flatness record data is calculated to reflect the average level of the data set, that is, the average condition of the cutting section flatness. This mean is set as the second cutting speed evaluation factor to evaluate the cutting quality under the cutting speed. It also includes that when the second cutting speed evaluation factor is greater than or equal to the flatness threshold, and the first cutting speed evaluation factor is less than or equal to the convergence variance threshold, the first cutting speed is set as the cutting constraint speed. According to the values ​​of the two evaluation factors, as well as the preset flatness threshold and convergence variance threshold, the cutting speed is evaluated. Specifically, if the second cutting speed evaluation factor (that is, the mean of the cutting section flatness) is greater than or equal to the flatness threshold, it means that the cutting quality has reached the expected level; at the same time, if the first cutting speed evaluation factor (that is, the variance of the cutting section flatness) is less than or equal to the convergence variance threshold, it means that the stability of the cutting speed is good. When these two conditions are met at the same time, the current first cutting speed is set as the cutting constraint speed.

[0040] The specific configuration of the elastic band cutting control module 70 will be described in detail below. The elastic band cutting control module 70 may further include: selecting a number of elastic band samples, cutting and testing based on the cutting constraint speed, obtaining a number of cutting section size deviations and a number of cutting section flatness deviations, wherein the cutting section size deviation is the area ratio of the size deviation area, and the cutting section flatness deviation is the deviation between the detected flatness and the expected flatness. Selecting a number of elastic band samples, cutting using the previously determined cutting constraint speed, testing the cut samples, and obtaining two key indicators, the cutting section size deviation and the cutting section flatness deviation, wherein the cutting section size deviation represents the area ratio of the deviation area between the actual cutting size and the expected size; and the cutting section flatness deviation represents the deviation between the actual detected flatness and the expected flatness. It also includes counting the proportion of the number of cutting section size deviations greater than or equal to the first deviation threshold, and setting it as the first fluctuation coefficient. Counting the proportion of samples with size deviations greater than or equal to the first deviation threshold in all tested cutting sections, this proportion is called the first fluctuation coefficient, which reflects the stability of the cutting size.

[0041] The elastic band cutting control module 70 also includes counting the proportion of the flatness deviation of the plurality of cutting sections being greater than or equal to the second deviation threshold, and setting it as the second fluctuation coefficient. Similarly, counting the proportion of samples whose flatness deviation is greater than or equal to the second deviation threshold in all the tested cutting sections, this proportion is called the second fluctuation coefficient, which reflects the stability of the cutting flatness. It also includes, when the first fluctuation coefficient and the second fluctuation coefficient are both less than or equal to the fluctuation coefficient threshold, performing elastic band cutting control according to the elastic band cutting cycle, the feed roller constraint speed and the cutting constraint speed. By comparing the first fluctuation coefficient and the second fluctuation coefficient with the preset fluctuation coefficient threshold, the effectiveness of the cutting constraint speed is verified. If both fluctuation coefficients are less than or equal to the fluctuation coefficient threshold, it is considered that the cutting constraint speed is effective and can meet the requirements for size and flatness in production. Then, according to this speed and known parameters such as the elastic band cutting cycle and the feed roller constraint speed, the cutting control of the elastic band is performed, that is, the cutting process of the elastic band is accurately controlled according to these parameters to ensure the quality and efficiency of the product.

[0042] The specific configuration of the elastic band cutting control module 70 will be described in detail below. The elastic band cutting control module 70 may further include: when the first fluctuation coefficient and / or the second fluctuation coefficient are both greater than the fluctuation coefficient threshold, a cutting blade maintenance instruction is generated and sent to the management end. If the first fluctuation coefficient is greater than the fluctuation coefficient threshold, or the second fluctuation coefficient is greater than the fluctuation coefficient threshold, or both are greater than the fluctuation coefficient threshold, it means that there may be a problem with the current state of the cutting blade, and further inspection and maintenance are required. A cutting blade maintenance instruction is generated, and the cutting blade maintenance instruction may contain specific maintenance content, such as replacing the blade, cleaning the blade, adjusting the blade position, etc. The management end receives the generated maintenance instruction and performs corresponding maintenance operations on the cutting blade according to the requirements of the instruction.

[0043] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0044] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A cutting control system for an elastic band, characterized in that: include: An elastic band raw material information acquisition module, used to obtain elastic band raw material information, wherein the elastic band raw material information includes elastic band width information, elastic band thickness information, feed distance information, elastic band raw material type information, the feed distance information represents the distance between the feed roller and the feed roller, the feed roller is driven by a motor, and the feed roller rotates as the feed roller rotates; A stretching tension threshold obtaining module, used to perform tension threshold analysis on the elastic band according to the elastic band width information, the elastic band thickness information, and the elastic band material type information to obtain a stretching tension threshold; A feed roller constraint speed generating module, configured to optimize the feed roller speed according to the stretching tension threshold, based on the elastic band width information, the elastic band thickness information, the feed distance information, and the elastic band raw material type information, and generate a feed roller constraint speed; A cutting constraint speed obtaining module, used to optimize the cutting speed according to the type of elastic band material and the model of the cutting blade, and obtain the cutting constraint speed; Elastic band cutting length configuration module, used to configure the elastic band cutting length; An elastic band cutting cycle configuration module, configured to configure the elastic band cutting cycle by calculation based on the elastic band cutting length and the feed roller constraint rotation speed; An elastic band cutting control module, used for controlling the elastic band cutting according to the elastic band cutting cycle, the feed roller constraint rotation speed and the cutting constraint speed; Wherein, performing tension threshold analysis on the elastic band according to the elastic band width information, the elastic band thickness information, and the elastic band material type information to obtain the stretching tension threshold includes: Collecting elastic band stretch test information according to the elastic band width information, the elastic band thickness information, and the elastic band material type information, wherein the elastic band stretch test information includes a set of stretch critical tension record values; Based on the tension consistency deviation, clustering is performed on the set of stretch critical tension record values ​​to generate multiple clusters of stretch critical tension record values; Traversing the plurality of clusters of stretch critical tension record values ​​to perform center tension analysis and generate a plurality of center tension record values; According to the proportion of the number of clusters of the multiple clusters of stretch critical tension recording values, weighted mean analysis is performed on the multiple center tension recording values ​​to generate the stretch tension threshold value; The central tension analysis is performed by traversing the multiple clusters of stretch critical tension record values ​​to generate multiple central tension record values, including: Extracting a first stretching critical tension record value of a first cluster of stretching critical tension record values ​​of the plurality of clusters of stretching critical tension record values; Calculate the mean of the sum of the deviations between the first critical tension recording value and other tension recording values ​​in the cluster, and set it as the distribution parameter in the cluster; Calculate the mean of the distribution parameter within the first cluster; Calculate the first cluster distribution parameter mean and the cluster distribution parameter to generate the first stretch critical tension record value centrality, and add it to the first cluster centrality set; Extracting the minimum value of the first cluster center degree set, sorting the first cluster center tension record values ​​from the first cluster stretch critical tension record values, and adding them into the plurality of center tension record values; According to the stretching tension threshold, based on the elastic band width information, the elastic band thickness information, the feed distance information, and the elastic band raw material type information, the feed roller speed is optimized to generate the feed roller constraint speed, including: Based on the elastic band raw material type information, a tension prediction model is activated, wherein the tension prediction model is generated by training with the elastic band raw material type information as a constraint, the elastic band width information, the elastic band thickness information, the feed distance information and the feed roller speed as input variables, and the elastic band tension value as an output variable; Based on the stretching tension threshold, configuring a first convergence constraint tension interval; Constructing an energy consumption optimization fitness function, wherein the energy consumption optimization fitness function is the inverse of the feed roller rotation speed, which is used to characterize the energy consumption; According to the first convergence constraint tension interval and the energy consumption optimization fitness function, combined with the tension prediction model, the feed roller speed is optimized, and when the first convergence constraint tension interval is satisfied and the preset number of iterations is satisfied, the feed roller constraint speed is output; According to the first convergence constraint tension interval and the energy consumption optimization fitness function, combined with the tension prediction model, the feed roller speed is optimized, and when the first convergence constraint tension interval is satisfied and the preset number of iterations is satisfied, the feed roller constraint speed is output, including: Randomly select a value according to the feed roller speed value interval to obtain the first feed roller speed; Generate a first predicted tension by fitting the first feed roller rotation speed, the elastic band width information, the elastic band thickness information, and the feed distance information through the tension prediction model; When the first predicted tension belongs to the first convergence constraint tension interval, adding the first feed roller speed to the speed set to be sorted; When the preset number of iterations is met, the rotation speed set to be sorted is sorted according to the energy consumption optimization fitness function to generate the feed roller constrained rotation speed.

2. The cutting control system of an elastic band as claimed in claim 1, characterized in that: According to the type of elastic band material and the model of cutting blade, the cutting speed is optimized to obtain the cutting constraint speed, including: Randomly select a value according to the cutting speed value interval to obtain a first cutting speed; Collecting blade cutting history records of the elastic band material type being cut by the cutting blade model at the first cutting speed, wherein the blade cutting history records include cutting section flatness record data; Calculating a variance parameter of the cut section flatness record data and setting it as a first cutting speed evaluation factor; Calculate the average of the recorded data of the flatness of the cutting section and set it as the second cutting speed evaluation factor; When the second cutting speed evaluation factor is greater than or equal to a flatness threshold, and the first cutting speed evaluation factor is less than or equal to a convergence variance threshold, the first cutting speed is set to the cutting constraint speed.

3. The cutting control system of an elastic band as claimed in claim 1, characterized in that: The elastic band cutting is controlled according to the elastic band cutting cycle, the feed roller constraint rotation speed and the cutting constraint speed, and the method also includes: Selecting a number of elastic band samples, cutting and testing them based on the cutting constraint speed, obtaining a number of cutting section size deviations and a number of cutting section flatness deviations, wherein the cutting section size deviation is the area ratio of the size deviation area, and the cutting section flatness deviation is the deviation between the detected flatness and the expected flatness; Counting the proportion of the plurality of cutting cross-section size deviations being greater than or equal to a first deviation threshold, and setting the proportion as a first fluctuation coefficient; Counting the proportion of the plurality of cut cross-section flatness deviations being greater than or equal to a second deviation threshold, and setting the proportion as a second fluctuation coefficient; When the first fluctuation coefficient and the second fluctuation coefficient are both less than or equal to the fluctuation coefficient threshold, the elastic band cutting control is performed according to the elastic band cutting cycle, the feed roller constraint rotation speed and the cutting constraint speed.

4. The cutting control system of an elastic band as claimed in claim 3, characterized in that: When the first fluctuation coefficient and / or the second fluctuation coefficient are both greater than the fluctuation coefficient threshold, a cutting blade maintenance instruction is generated and sent to the management end.

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