Automatic film material cutting control method and system

Abstract

The invention relates to the technical field of automatic control, in particular to an automatic film material cutting control method and system, and the method comprises the following steps: selecting a finite element to analyze and calculate the deformation condition of a film material in a differentiated tension state according to the elastic modulus and Poisson's ratio parameters of the film material, and analyzing the influence of tension distribution on the deformation of the film material in combination with a cutting position. According to the method, the physical characteristics of the membrane material are set, finite element analysis is combined, tension-deformation distribution data are obtained, a scientific basis is provided for optimizing a cutting path, an optimization model is constructed, a genetic algorithm is adopted for solving, tension fluctuation and deformation errors are effectively reduced, material waste is reduced, and the current tension state of the membrane material is monitored and obtained in real time; dynamic adjustment is carried out in combination with the optimized path, it is ensured that the cutting path is matched with the tension change of the membrane material, and the dynamic adjustment mechanism remarkably improves the cutting precision, improves the product quality, reduces material waste and improves the overall production efficiency.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to an automatic film material cutting control method and system. Background Art

[0002] The field of automated control technology mainly involves the use of various control systems to operate equipment, machinery and processes with less human intervention. These systems are able to monitor and adjust operations in the production process to optimize performance and efficiency. Automated control systems are widely used in industry, manufacturing, transportation and many other fields, and include mechanisms that use sensors, controllers and software to automatically perform tasks through feedback loops. These technologies enable companies to increase production, improve quality control, reduce material waste, and increase safety on production lines.

[0003] Among them, the automated film cutting control method refers to a technology used to automatically control the cutting process of film materials (such as plastic films, metal foils or other industrial films). The main purpose of this method is to improve cutting accuracy and speed, reduce material waste, and improve overall production efficiency. By using advanced algorithms and precise mechanical devices, automated film cutting can achieve complex cutting patterns and specifications while maintaining continuous production, and is widely used in the packaging, electronics and automotive industries.

[0004] The existing technology has defects in the film cutting process. The traditional cutting method relies on a fixed path and lacks real-time monitoring of the tension state of the film, resulting in insufficient cutting accuracy. Under tension fluctuations, uneven cutting is prone to occur, increasing material waste. When processing complex cutting patterns, it is unable to effectively adapt to film deformation, affecting the quality of the final product. For example, in the packaging industry, improper cutting may lead to packaging failure, resulting in increased costs and economic losses. These shortcomings limit the application of existing technologies in high-demand production environments. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an automatic film material cutting control method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: an automatic film material cutting control method, comprising the following steps: S1: According to the elastic modulus and Poisson's ratio parameters of the membrane material, finite element analysis is selected to calculate the deformation of the membrane material under the differential tension state. Combined with the cutting position, the influence of tension distribution on the deformation of the membrane material is analyzed, the deformation amount of the membrane material under the differential tension distribution condition is obtained, and the tension-deformation distribution data is generated; S2: according to the tension-deformation distribution data, the objective function is set, an optimization model for minimizing tension fluctuation, deformation error and material waste is constructed, a genetic algorithm is selected to solve the objective function, the optimization process is executed and the objective function is weighed, and an optimized cutting path solution is obtained; S3: obtaining the current tension state of the film material through real-time monitoring, combining the optimized cutting path scheme, calculating the influence of the tension distribution change on the cutting path, adjusting the cutting path to match the current tension state, and generating a real-time adjustment cutting path scheme; S4: Based on the real-time cutting path adjustment scheme, a dynamic path adjustment mechanism is set during the cutting process, the current tension fluctuation is compared with the deviation of the cutting path in real time, the cutting path is adjusted to match the film material tension change, and a dynamic cutting path adjustment value is generated; S5: According to the dynamic cutting path adjustment value, combined with the actual tension distribution and deformation data, the cutting path adjustment is performed to complete the cutting of the film material, and the cutting completion result is recorded.

[0007] The tension-deformation distribution data includes film material deformation, tension distribution, and cutting position; the optimization model includes objective function, deformation error, and material waste; the real-time adjustment of the cutting path plan includes current tension state, optimized cutting path plan, and tension distribution change; the dynamic cutting path adjustment value includes tension fluctuation, cutting path deviation, and film material tension change; the cutting completion result includes actual tension distribution, deformation data, and cutting path adjustment.

[0008] As a further solution of the present invention, the step of acquiring the tension-deformation distribution data is specifically as follows: S111: setting the physical properties of the membrane material, including elastic modulus and Poisson's ratio, using the parameters to initialize the finite element model, and obtaining preliminary deformation response data by simulating the response of the membrane material under differential tension conditions; S112: Analyze the preliminary deformation response data to identify the deformation characteristics of the film material at multiple cutting positions, using the formula: ; Calculate the stress distribution of the membrane under differential tension and obtain stress analysis data ; Where E represents the elastic modulus, ν represents the Poisson's ratio, Represents the shape variable; S113: Based on the stress analysis data, iteratively adjust model parameters to optimize the simulation of tension distribution, determine the optimal tension settings for multiple cutting positions through multiple iterations, and obtain tension-deformation distribution data.

[0009] As a further solution of the present invention, the step of obtaining the optimized cutting path solution is specifically as follows: S211: Based on the tension-deformation distribution data, define an objective function to minimize tension fluctuation, deformation error and material waste, and set objective function parameters by comprehensively referring to all key factors; S212: Select a genetic algorithm as a solution strategy, input the objective function parameters, and configure key operating parameters of the genetic algorithm, including population size, crossover rate, and mutation rate, perform algorithm initialization, and obtain algorithm configuration; S213: extracting the initial population and operating parameters from the algorithm configuration, executing the genetic algorithm, using the formula: ; Perform a new generation of path parameter calculation, calculate the new path parameters, and determine the optimized cutting path solution; in, Represents the new path parameter, which is the updated path value calculated according to the optimization algorithm and is used to guide the current path setting of the cutting machine. The path parameters of the previous generation represent the old setting values ​​of the cutting path before optimization, which are used as a reference. is the learning rate, which is a regulation factor used to control the step size of path parameter updates. is the path parameter with the best performance before, The path parameter used in the current iteration, that is, the real-time value of the current path configuration. as a scaling factor.

[0010] As a further solution of the present invention, the step of obtaining the real-time adjustment cutting path solution is specifically as follows: S311: collecting the current tension state data of the film material provided by the real-time monitoring system, integrating the data to analyze its influence on the optimized cutting path solution, and generating the current tension state analysis result; S312: according to the current tension state analysis result, using a mathematical model to quantify the influence of tension distribution change on the cutting path, determining the influence of tension change on cutting accuracy by calculation, and generating a tension influence evaluation result; S313: Using the tension impact evaluation result, adjust the cutting path to match the current tension state, using the formula: ; Perform path adjustment calculations and generate real-time adjustment cutting path solutions; in, Represents the adjusted clipping path, The original cutting path based on the preliminary optimization model, is the path adjustment coefficient, which is used to quantitatively adjust the effect of tension changes on the path. Indicates the recommended path deviation caused by tension.

[0011] As a further solution of the present invention, the step of obtaining the dynamic clipping path adjustment value is specifically as follows: S411: Analyze the current film material tension data and the preset cutting path in the real-time adjustment cutting path scheme, calculate the deviation between the tension data at each time point and the path setting value, and generate a deviation data set; S412: comparing each data point in the deviation data set with a set threshold, screening deviation points exceeding the threshold, calculating an average value of the deviation points exceeding the threshold, and obtaining an average deviation value; S413: Using the average deviation value and the real-time tension data of the film material, normalization is performed and the formula is adopted: ; Calculate and obtain the dynamic clipping path adjustment value; in, Indicates the dynamic clipping path adjustment value. represents the weight of each data point, For real-time tension data, For preset path data, is the adjustment coefficient, used to enhance the sensitivity of the adjustment. Represents the total number of data points.

[0012] As a further solution of the present invention, the step of recording the cutting completion result is specifically: S511: Based on the dynamic cutting path adjustment value, call the real-time monitored tension distribution and deformation data to evaluate the influence of tension on the cutting path, and obtain the cutting adjustment parameter by collectively comparing the difference between the current cutting path and the tension state; S512: According to the cutting adjustment parameters, the cutting path is corrected using a dynamic model, using the formula: ; The cutting path correction is completed to obtain the corrected cutting path; in, is the corrected clipping path, Adjust the value for the original dynamic clipping path. is the tension adjustment coefficient, which is used to adjust the correction effect of tension changes on the cutting path. is the current tension change measured in real time. is the reference tension value, used to compare the deviation of the current tension. is the deformation correction coefficient, referring to the influence of deformation on the cutting path. The difference in path length is used to correct path adjustment; S513: executing the corrected cutting path to cut the film material, recording key data and film material status during the cutting process, completing the cutting operation, and recording the cutting completion result.

[0013] An automated film material cutting control system, the automated film material cutting control system is used to execute the automated film material cutting control method, the system comprising: The physical property analysis module sets the physical properties of the membrane material based on the elastic modulus and Poisson's ratio of the membrane material, selects finite element analysis to calculate the deformation of the membrane material under the state of differential tension, analyzes the influence of tension distribution on the deformation of the membrane material in combination with the cutting position, obtains the deformation amount of the membrane material under the condition of differential tension distribution, and generates tension-deformation distribution data; The optimization path planning module sets the objective function based on the tension-deformation distribution data, constructs an optimization model that minimizes tension fluctuation, deformation error and material waste, executes the optimization process, and obtains an optimized cutting path solution; The real-time monitoring and adjustment module obtains the current tension state of the film material based on real-time monitoring, calculates the influence of the tension distribution change on the cutting path in combination with the optimized cutting path plan, adjusts the cutting path to match the current tension state, and generates a real-time adjustment cutting path plan; The cutting execution module sets a dynamic path adjustment mechanism during the cutting process based on the real-time adjustment of the cutting path scheme, compares the deviation between the current tension fluctuation and the cutting path in real time, adjusts the cutting path to match the tension change of the film material, generates a dynamic cutting path adjustment value, and executes the cutting path adjustment in combination with the actual tension distribution and deformation data, completes the cutting of the film material, and records the cutting completion results.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by setting the physical properties of the film material and combining finite element analysis, the tension-deformation distribution data is obtained to provide a scientific basis for optimizing the cutting path. The constructed optimization model is solved by genetic algorithm to effectively reduce tension fluctuations and deformation errors and reduce material waste. The current tension state of the film material is obtained by real-time monitoring, and dynamic adjustment is performed in combination with the optimization path to ensure that the cutting path matches the tension change of the film material. This dynamic adjustment mechanism significantly improves cutting accuracy, improves product quality, reduces material waste, and improves overall production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 A flow chart of the steps for obtaining tension-deformation distribution data of the present invention; Figure 3 A flow chart of the steps for obtaining the cutting path optimization solution of the present invention; Figure 4 A flowchart of the steps for obtaining a cutting path solution for adjusting the cutting path in real time according to the present invention; Figure 5 A flowchart of the steps for obtaining the dynamic cutting path adjustment value of the present invention; Figure 6 The present invention is a flow chart of the steps of recording the cutting completion results. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0018] Example 1: Please refer to Figure 1 The present invention provides a technical solution: an automatic film material cutting control method, comprising the following steps: S1: According to the elastic modulus and Poisson's ratio parameters of the membrane material, finite element analysis is selected to calculate the deformation of the membrane material under the differential tension state. Combined with the cutting position, the influence of tension distribution on the deformation of the membrane material is analyzed, the deformation amount of the membrane material under the differential tension distribution condition is obtained, and the tension-deformation distribution data is generated; S2: According to the tension-deformation distribution data, the objective function is set, and an optimization model that minimizes tension fluctuation, deformation error and material waste is constructed. The genetic algorithm is selected to solve the objective function, and the optimization process is executed and the objective function is weighed to obtain the optimized cutting path solution; S3: Obtain the current tension state of the film material through real-time monitoring, combine with the optimized cutting path plan, calculate the impact of the tension distribution change on the cutting path, adjust the cutting path to match the current tension state, and generate a real-time adjustment cutting path plan; S4: Based on the real-time adjustment of the cutting path solution, a dynamic path adjustment mechanism is set during the cutting process, the current tension fluctuation is compared with the deviation of the cutting path in real time, the cutting path is adjusted to match the film tension change, and a dynamic cutting path adjustment value is generated; S5: According to the dynamic cutting path adjustment value, combined with the actual tension distribution and deformation data, the cutting path adjustment is performed to complete the cutting of the film material and record the cutting completion result.

[0019] The tension-deformation distribution data includes the film deformation, tension distribution, and cutting position. The optimization model includes the objective function, deformation error, and material waste. The real-time adjustment of the cutting path plan includes the current tension state, optimized cutting path plan, and tension distribution changes. The dynamic cutting path adjustment value includes tension fluctuation, cutting path deviation, and film tension change. The cutting completion result includes the actual tension distribution, deformation data, and cutting path adjustment.

[0020] See also Figure 2 , the specific steps for obtaining the tension-deformation distribution data are: S111: setting the physical properties of the membrane material, including elastic modulus and Poisson's ratio, using the parameters to initialize the finite element model, and obtaining preliminary deformation response data by simulating the response of the membrane material under differential tension conditions; The finite element model is initialized according to the physical properties of the membrane material, and the initial tension and physical parameters including elastic modulus and Poisson's ratio are set. The response of the membrane material at multiple cutting positions is monitored by simulating differentiated tension conditions, and the deformation characteristics of the membrane material under the target tension are extracted from the simulation data. These data will serve as the basis for optimizing the model and parameter adjustment. The accuracy of the model will be refined through multiple iterations to ensure that the simulation results are as consistent as possible with the actual material behavior. These data can be used to iteratively analyze the stress distribution and potential weaknesses of the material, so as to make adjustments before cutting and obtain preliminary deformation response data.

[0021] S112: Analyze the preliminary deformation response data to identify the deformation characteristics of the film material at multiple cutting positions using the formula: ; Calculate the stress distribution of the membrane under differential tension and obtain stress analysis data ; Where E represents the elastic modulus, ν represents the Poisson's ratio, Represents the shape variable; formula: ; The benefit of the formula is that it calculates the stress distribution under differential deformation based on the basic physical properties of the material, including the elastic modulus and Poisson's ratio, thereby optimizing the application and performance of the material.

[0022] Detailed explanation of the formula and the process of formula calculation and derivation: Set up a situation where the elastic modulus E = 210 GPa, Poisson's ratio ν = 0.3, and deformation ε = 0.005. Substituting these values ​​into the formula gives: ; This calculation process shows how to apply theoretical models to material mechanics analysis. The results show that under given physical parameters and deformation conditions, the stress distribution of the membrane material can reach 159MPa, which helps to analyze the maximum stress that the material can withstand in practical applications, thereby conducting better design and safety assessments.

[0023] S113: Based on the stress analysis data, iteratively adjust the model parameters to optimize the simulation of the tension distribution, and determine the optimal tension settings for multiple cutting positions through multiple iterations to obtain the tension-deformation distribution data.

[0024] The stress analysis data is used to adjust the model parameters. Through multiple iterations of simulation optimization, attention is paid to the performance of the membrane material in actual application, including the selection of cutting position and the adjustment of tension, which can be optimized according to the stress distribution, which helps to avoid premature fatigue or failure of the material during use. During the optimization process, the tension configuration is adjusted cyclically to ensure that each position can achieve the optimal mechanical properties and the application effect of the membrane material. This method is used to determine the stress level and deformation response of each part, thereby obtaining the tension-deformation distribution data.

[0025] See also Figure 3 , the specific steps for obtaining the optimized cutting path solution are: S211: Based on the tension-deformation distribution data, define the objective function to minimize tension fluctuation, deformation error and material waste, and set the objective function parameters by comprehensively referring to all key factors; In the process of defining the objective function, reference is made to the factors of tension fluctuation, deformation error and material waste. By analyzing the influence of these factors on the performance of the membrane material, parameters are used to quantify these influences, including the tension fluctuation rate obtained by measuring the response difference of the membrane material under differentiated stress states, the deformation error is evaluated by comparing the difference between the expected deformation and the actual deformation, and the material waste is defined by analyzing the utilization rate of the remaining materials through experimental data. The reasonable setting of these parameters is based on batch experimental data and previous research results to ensure that the objective function can accurately reflect the key indicators that need to be optimized in actual production. The objective function setting can effectively guide the parameter optimization in the production process to minimize costs and improve material utilization.

[0026] S212: Select a genetic algorithm as a solution strategy, input objective function parameters, and configure key operation parameters of the genetic algorithm, including population size, crossover rate, and mutation rate, perform algorithm initialization, and obtain algorithm configuration; In the configuration process of the genetic algorithm, the objective function parameters are used as input, and the settings of the algorithm's population size, crossover rate, and mutation rate are adjusted according to previous cases and theoretical studies. The population size directly affects the breadth of the search and the convergence speed of the algorithm. The crossover rate and mutation rate determine the algorithm's ability to avoid local optimality and search the solution space. By analyzing the impact of differentiated parameter configurations on algorithm performance and combining the characteristics of the objective function, the parameters are carefully selected to ensure that the genetic algorithm can capture approximate optimal solutions within a reasonable time, thereby improving the algorithm's efficiency and the reliability of the results. The setting of this configuration process is based on previous research on similar problems and analysis of experimental results to ensure that each parameter setting has sufficient experimental and theoretical support.

[0027] S213: Extract the initial population and operating parameters from the algorithm configuration and execute the genetic algorithm using the formula: ; Perform a new generation of path parameter calculation, calculate the new path parameters, and determine the optimized cutting path solution; in, Represents the new path parameter, which is the updated path value calculated according to the optimization algorithm and is used to guide the current path setting of the cutting machine. The path parameters of the previous generation represent the old setting values ​​of the cutting path before optimization, which are used as a reference. is the learning rate, which is a regulation factor used to control the step size of path parameter updates. is the path parameter with the best performance before, The path parameter used in the current iteration, that is, the real-time value of the current path configuration. as a scaling factor.

[0028] formula: ; The benefit of the formula is that it dynamically adjusts the path parameters and combines the learning rate and the scale factor The search path is optimized by adjusting the search path, effectively balancing the needs of global search and local search, which is crucial for genetic algorithms in multi-objective optimization problems and improves the convergence speed of the algorithm and the quality of the solution. , , , , ,but: ; ; ; ; The results show that with the currently set learning rate and scale factor, the path parameters of the new generation are updated from 100 to 101.5. This new parameter will be used for the next generation of search, showing that the algorithm has fine-tuned the path parameters to gradually approach the optimal solution. The application of this method in actual operation means that the cutting path can be adjusted more finely, reducing material waste and optimizing production efficiency.

[0029] See also Figure 4 , the specific steps for obtaining the real-time adjustment cutting path solution are: S311: collecting the current tension state data of the film material provided by the real-time monitoring system, integrating the data to analyze its influence on the optimization cutting path solution, and generating the current tension state analysis result; Through the data collected by the real-time monitoring system, the current tension state of the film material is the key variable. By monitoring the tension data continuously recorded by the equipment, the actual tension changes of the film material on the production line can be understood. These data are collected by sensors at differentiated positions on the film material. Each sensor can record data at a frequency of milliseconds. These recorded data are then sent to the central monitoring system via a wireless network. The central monitoring system summarizes and analyzes these data to generate tension state results, which are the basis for cutting path optimization.

[0030] S312: according to the current tension state analysis result, a mathematical model is used to quantify the influence of the tension distribution change on the cutting path, and the influence of the tension change on the cutting accuracy is determined by calculation to generate a tension influence evaluation result; The current tension status analysis results are obtained through real-time analysis of the tension data collected by the monitoring system. By analyzing the tension fluctuations of the film material in the differentiated production stage and combining with previous data comparison, the problem areas are predicted. Data analysis depends critically on data processing, which can process batch data in real time and predict the behavior patterns of the film material through algorithm optimization. The analysis results help analyze how the tension changes in the differentiated production stage and how these changes affect the selection of the cutting path.

[0031] S313: Using the tension impact evaluation result, adjust the cutting path to match the current tension state, using the formula: ; Perform path adjustment calculations and generate real-time adjustment cutting path solutions; in, Represents the adjusted clipping path, The original cutting path based on the preliminary optimization model, is the path adjustment coefficient, which is used to quantitatively adjust the effect of tension changes on the path. Indicates the recommended path deviation caused by tension.

[0032] formula: ; The benefit of the formula is that the cutting path is dynamically adjusted based on the tension changes monitored in real time, thereby optimizing the production process and reducing material waste.

[0033] Detailed explanation of the formula and the process of formula calculation and derivation: Set the initial clipping path Set to 1000mm, recommended path deviation due to tension 50mm, adjustment factor Through testing, it is found that it is set to 0.5 to maintain the stability of path adjustment. Substituting it into the formula, it is calculated as follows: ; The results show that the actual cutting path should be adjusted to 1025mm to match the current tension state. This adjustment helps reduce precision problems caused by abnormal tension and ensures cutting quality.

[0034] See also Figure 5 , the specific steps for obtaining the dynamic clipping path adjustment value are: S411: Analyze the current film material tension data and the preset cutting path in the real-time adjustment cutting path scheme, calculate the deviation between the tension data at each time point and the path setting value, and generate a deviation data set; Real-time adjustment of the cutting path plan requires reference to the real-time data of the film material tension. These data are monitored in real time by sensors and collected by the data acquisition system. These tension data show the tension state of the film material on the cutting machine. By comparing with the deviation of the preset cutting path, the system can capture any deviation in real time. The generation of the deviation data set depends on the calculation of the difference between the tension data and the path setting value at each time point, which requires sensors and a stable data transmission system to ensure the accuracy and real-time nature of the data. In this way, the operator can identify the path area that needs to be adjusted, thereby adjusting the cutting machine to ensure the cutting quality and maximum utilization of materials. In this way, the cutting path is optimized and adjusted, reducing material waste and improving product quality.

[0035] S412: comparing each data point in the deviation data set with a set threshold, screening deviation points exceeding the threshold, calculating the average value of the deviation points exceeding the threshold, and obtaining an average deviation value; During the film cutting process, the generation of deviation data sets provides basic data for subsequent operations. The system compares each data point in the deviation data set with the set threshold and screens out deviation points that exceed the threshold. This step is crucial because it directly affects whether the cutting path needs to be adjusted to match the actual tension change. The average value of the deviation points exceeding the threshold is calculated through statistical methods. This average value provides a quantitative reference to determine the adjustment range of the cutting path. This method ensures the efficiency and accuracy of the cutting process. Through the analysis of the deviation points exceeding the threshold, the cutting strategy can be iteratively optimized, thereby reducing non-critical material loss and improving overall production efficiency. Through data analysis, the stable operation of the production line and the consistency of product quality are ensured.

[0036] S413: Use the average deviation value and the real-time tension data of the membrane material, through normalization processing, and use the formula: ; Calculate and obtain the dynamic clipping path adjustment value; in, Indicates the dynamic clipping path adjustment value. represents the weight of each data point, For real-time tension data, For preset path data, is the adjustment coefficient, used to enhance the sensitivity of the adjustment. Represents the total number of data points.

[0037] formula: ; The benefit of the formula is that by introducing the weight factor and adjustment coefficient , which enhances the flexibility and matching of deviation data processing, and can adjust the cutting path to match the real-time tension changes of the film material, thereby optimizing the cutting efficiency and material utilization.

[0038] Detailed explanation of the formula and the process of formula calculation and derivation: Set to collect the following tension data and preset path data during the monitoring period: , , the weight factor is assumed to be , the adjustment coefficient is . First, calculate the weighted sum of the deviation values: ; Then, calculate the total tension value: ; Next, substitute the above results into the formula to calculate : ; The results show that based on the current data and parameter settings, the adjustment value of the dynamic cutting path is 0.01, which means that the cutting path needs to be adjusted to match the tension changes of the material to ensure the accuracy of the cutting process and the optimal use of the material.

[0039] See also Figure 6 , the specific steps for recording the cutting results are: S511: Based on the dynamic cutting path adjustment value, the real-time monitored tension distribution and deformation data are called to evaluate the influence of tension on the cutting path, and the cutting adjustment parameters are obtained by collectively comparing the difference between the current cutting path and the tension state; The tension data used in this process comes from the real-time monitoring system. These data are obtained directly from the film material on the production line through sensors. The signals are converted into electronic data through data collection equipment and stored in the database. During the analysis process, the data analyst reads the data, calculates the average tension value, and compares it with the tension parameters set by the standard cutting path to evaluate whether the cutting path needs to be adjusted to match the current tension state. This judgment is based on the difference analysis between the real-time data and the preset standard, and the result will directly affect the path adjustment decision of the cutting machine.

[0040] S512: According to the cutting adjustment parameters, the cutting path is corrected by applying the dynamic model, using the formula: ; The cutting path correction is completed to obtain the corrected cutting path; in, is the corrected clipping path, Adjust the value for the original dynamic clipping path. is the tension adjustment coefficient, which is used to adjust the correction effect of tension changes on the cutting path. is the current tension change measured in real time. is the reference tension value, used to compare the deviation of the current tension. is the deformation correction coefficient, referring to the influence of deformation on the cutting path. The difference in path length is used to correct path adjustment; formula: ; The benefit of the formula is the ability to adjust the cutting path in real time to match instant changes in tension, which helps optimize cut quality and reduce material waste.

[0041] Detailed explanation of the formula and the process of formula calculation and derivation: The settings have the following values: mm is the original dynamic adjustment path, is the tension adjustment coefficient, N is the current tension change, N is the reference tension value, N / mm is the deformation correction coefficient, mm is the path length difference. The calculation formula is as follows: ; ; ; ; The results show that through dynamic adjustment, the cutting path is fine-tuned by 0.35mm and the actual tension changes, which ensures cutting accuracy and reduces material defects caused by abnormal tension.

[0042] S513: executing the corrected cutting path to cut the film material, recording key data and film material status during the cutting process, completing the cutting operation, and recording the cutting completion result.

[0043] During this process, the machine operator adjusts the settings of the cutting machine based on the feedback from the control system to ensure that the cutting path meets the current parameter settings. During the adjustment process, the operator monitors the cutting progress and quality, detects the cutting quality through the real-time feedback system, and makes fine adjustments as needed. These adjustments are based on real-time data provided by the cutting machine's performance monitoring system, including cutting speed, tool wear and material movement speed. All this information is summarized to form the cutting completion result, which is recorded in the production log for quality management and subsequent production adjustments.

[0044] An automatic film material cutting control system, which is used to execute the above-mentioned automatic film material cutting control method, comprises: The physical property analysis module sets the physical properties of the membrane material based on the elastic modulus and Poisson's ratio of the membrane material, selects finite element analysis to calculate the deformation of the membrane material under the state of differential tension, analyzes the influence of tension distribution on the deformation of the membrane material in combination with the cutting position, obtains the deformation amount of the membrane material under the condition of differential tension distribution, and generates tension-deformation distribution data; The optimization path planning module sets the objective function based on the tension-deformation distribution data, builds an optimization model that minimizes tension fluctuation, deformation error and material waste, executes the optimization process, and obtains the optimized cutting path solution; The real-time monitoring and adjustment module obtains the current tension state of the film material based on real-time monitoring, combines it with the optimized cutting path plan, calculates the impact of the tension distribution change on the cutting path, adjusts the cutting path to match the current tension state, and generates a real-time adjustment cutting path plan; The cutting execution module adjusts the cutting path plan in real time, sets a dynamic path adjustment mechanism during the cutting process, compares the current tension fluctuation and the deviation of the cutting path in real time, adjusts the cutting path to match the tension change of the film material, generates a dynamic cutting path adjustment value, and combines the actual tension distribution and deformation data to execute the cutting path adjustment, complete the cutting of the film material, and record the cutting completion results.

[0045] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An automated film cutting control method, characterized in that: The following steps are involved: According to the elastic modulus and Poisson's ratio parameters of the membrane material, finite element analysis is selected to calculate the deformation of the membrane material under the state of differential tension. Combined with the cutting position, the influence of tension distribution on the deformation of the membrane material is analyzed, the deformation of the membrane material under the condition of differential tension distribution is obtained, and the tension-deformation distribution data is generated; According to the tension-deformation distribution data, an objective function is set, an optimization model for minimizing tension fluctuation, deformation error and material waste is constructed, a genetic algorithm is selected to solve the objective function, an optimization process is executed and the objective function is weighed to obtain an optimized cutting path solution; The current tension state of the film material is obtained by real-time monitoring, and combined with the optimized cutting path scheme, the influence of the tension distribution change on the cutting path is calculated, the cutting path is adjusted to match the current tension state, and a real-time adjustment cutting path scheme is generated; Based on the real-time adjustment of the cutting path scheme, a dynamic path adjustment mechanism is set during the cutting process, the deviation between the current tension fluctuation and the cutting path is compared in real time, the cutting path is adjusted to match the film material tension change, and a dynamic cutting path adjustment value is generated; According to the dynamic cutting path adjustment value, combined with the actual tension distribution and deformation data, the cutting path adjustment is performed to complete the cutting of the film material, and the cutting completion result is recorded.

2. The automatic film material cutting control method according to claim 1, characterized in that: The tension-deformation distribution data includes film material deformation, tension distribution, and cutting position; the optimization model includes objective function, deformation error, and material waste; the real-time adjustment of the cutting path plan includes current tension state, optimized cutting path plan, and tension distribution change; the dynamic cutting path adjustment value includes tension fluctuation, cutting path deviation, and film material tension change; the cutting completion result includes actual tension distribution, deformation data, and cutting path adjustment.

3. The automatic film material cutting control method according to claim 2, characterized in that: The steps for obtaining the tension-deformation distribution data are specifically as follows: Set the physical properties of the membrane material, including elastic modulus and Poisson's ratio, use the parameters to initialize the finite element model, and obtain preliminary deformation response data by simulating the response of the membrane material under differentiated tension conditions; The preliminary deformation response data is analyzed to identify the deformation characteristics of the film material at multiple cutting positions, using the formula: ； Calculate the stress distribution of the membrane under differential tension and obtain stress analysis data ; Where E represents the elastic modulus, ν represents the Poisson's ratio, Represents the shape variable; Based on the stress analysis data, the model parameters are iteratively adjusted to optimize the simulation of the tension distribution. Through multiple iterations, the optimal tension settings for multiple cutting positions are determined to obtain the tension-deformation distribution data.

4. The automatic film material cutting control method according to claim 3, characterized in that: The steps for obtaining the optimized cutting path solution are specifically as follows: Based on the tension-deformation distribution data, define the objective function to minimize tension fluctuation, deformation error and material waste, and set the objective function parameters by comprehensively referring to all key factors; Selecting a genetic algorithm as a solution strategy, inputting the objective function parameters, and configuring key operating parameters of the genetic algorithm, including population size, crossover rate, and mutation rate, performing algorithm initialization, and obtaining algorithm configuration; Extract the initial population and operating parameters from the algorithm configuration and execute the genetic algorithm using the formula: ； Perform a new generation of path parameter calculation, calculate the new path parameters, and determine the optimized cutting path solution; in, Represents the new path parameter, which is the updated path value calculated according to the optimization algorithm and is used to guide the current path setting of the cutting machine. The path parameters of the previous generation represent the old setting values ​​of the cutting path before optimization, which are used as a reference. is the learning rate, which is a regulation factor used to control the step size of path parameter updates. is the path parameter with the best performance before, The path parameter used in the current iteration, that is, the real-time value of the current path configuration. as a scaling factor.

5. The automatic film cutting control method according to claim 4, characterized in that: The steps for obtaining the real-time adjustment cutting path solution are specifically as follows: Collect the current tension state data of the film material provided by the real-time monitoring system, integrate the data to analyze its influence on the optimized cutting path scheme, and generate the current tension state analysis result; According to the current tension state analysis result, a mathematical model is used to quantify the influence of tension distribution change on the cutting path, and the influence of tension change on cutting accuracy is determined by calculation to generate a tension influence evaluation result; Using the tension impact assessment results, the cutting path is adjusted to match the current tension state using the formula: ； Perform path adjustment calculations and generate real-time adjustment cutting path solutions; in, Represents the adjusted clipping path, The original cutting path based on the preliminary optimization model, is the path adjustment coefficient, which is used to quantitatively adjust the effect of tension changes on the path. Indicates the recommended path deviation caused by tension.

6. The automatic film material cutting control method according to claim 5, characterized in that: The steps for obtaining the dynamic cutting path adjustment value are specifically as follows: Analyze the current film material tension data and the preset cutting path in the real-time adjustment cutting path scheme, calculate the deviation between the tension data at each time point and the path setting value, and generate a deviation data set; According to each data point in the deviation data set, compare it with a set threshold, filter the deviation points exceeding the threshold, calculate the average value of the deviation points exceeding the threshold, and obtain the average deviation value; Using the average deviation value and the real-time tension data of the film material, through normalization processing, the formula is adopted: ； Calculate and obtain the dynamic clipping path adjustment value; in, Indicates the dynamic clipping path adjustment value. represents the weight of each data point, For real-time tension data, For preset path data, is the adjustment coefficient, used to enhance the sensitivity of the adjustment. Represents the total number of data points.

7. The automatic film material cutting control method according to claim 6, characterized in that: The steps of recording the cutting completion result are specifically as follows: Based on the dynamic cutting path adjustment value, the real-time monitored tension distribution and deformation data are called to evaluate the influence of tension on the cutting path, and the cutting adjustment parameters are obtained by collectively comparing the difference between the current cutting path and the tension state; According to the cutting adjustment parameters, the dynamic model is applied to correct the cutting path, using the formula: ； The cutting path correction is completed to obtain the corrected cutting path; in, is the corrected clipping path, Adjust the value for the original dynamic clipping path. is the tension adjustment coefficient, which is used to adjust the correction effect of tension change on the cutting path. is the current tension change measured in real time. is the reference tension value, used to compare the deviation of the current tension. is the deformation correction coefficient, referring to the influence of deformation on the cutting path. The difference in path length is used to correct path adjustment; The corrected cutting path is executed to cut the film material, key data and film material status during the cutting process are recorded, the cutting operation is completed, and the cutting completion result is recorded.

8. An automated film cutting control system, characterized in that: According to the automatic film material cutting control method according to any one of claims 1 to 7, the system comprises: The physical property analysis module sets the physical properties of the membrane material based on the elastic modulus and Poisson's ratio of the membrane material, selects finite element analysis to calculate the deformation of the membrane material under the state of differential tension, analyzes the influence of tension distribution on the deformation of the membrane material in combination with the cutting position, obtains the deformation amount of the membrane material under the condition of differential tension distribution, and generates tension-deformation distribution data; The optimization path planning module sets the objective function based on the tension-deformation distribution data, constructs an optimization model that minimizes tension fluctuation, deformation error and material waste, executes the optimization process, and obtains an optimized cutting path solution; The real-time monitoring and adjustment module obtains the current tension state of the film material based on real-time monitoring, calculates the influence of the tension distribution change on the cutting path in combination with the optimized cutting path plan, adjusts the cutting path to match the current tension state, and generates a real-time adjustment cutting path plan; The cutting execution module sets a dynamic path adjustment mechanism during the cutting process based on the real-time adjustment of the cutting path scheme, compares the deviation between the current tension fluctuation and the cutting path in real time, adjusts the cutting path to match the tension change of the film material, generates a dynamic cutting path adjustment value, and executes the cutting path adjustment in combination with the actual tension distribution and deformation data, completes the cutting of the film material, and records the cutting completion results.

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