Method and apparatus for controlling heat seal pressure of polyethylene hot melt film

Abstract

The application discloses a polyethylene hot melt film heat sealing pressure control method and device, relates to the related field of heat sealing pressure control, and solves the technical problems that a traditional heat sealing pressure control system relies on artificial experience or fixed set values, is difficult to adjust the pressure in real time, influences sealing quality, increases material waste, and reduces the overall efficiency of a production line, achieves automatic monitoring and adjustment of heat sealing pressure, realizes improvement of sealing quality, enhances the self-adaptive capacity to environmental changes, and improves the production efficiency.

Description

Technical Field

[0001] This application relates to the field of heat-sealing pressure control, and in particular to a method and apparatus for controlling the heat-sealing pressure of polyethylene hot melt film. Background Technology

[0002] Polyethylene hot-melt film is widely used in the packaging industry, especially in food, pharmaceutical, and consumer product packaging, due to its excellent sealing performance and cost-effectiveness. Heat sealing, as the core technology in polyethylene film processing, involves heating the film edges to their melting point and applying pressure to achieve a seal. Despite the widespread use of heat sealing technology, current heat sealing pressure control systems often rely on operator experience or fixed setpoints, leading to inconsistencies in pressure control across different production batches or environmental conditions. Furthermore, the heat-sealing performance of polyethylene film is extremely sensitive to environmental conditions, such as changes in temperature and humidity; existing systems often lack the ability to adjust pressure in real time, affecting sealing quality. These technical limitations not only increase material waste but also reduce the overall efficiency of the production line. Summary of the Invention

[0003] This application provides a heat-sealing pressure control method and apparatus for polyethylene hot melt film, which solves the technical problems of traditional heat-sealing pressure control systems that rely on manual experience or fixed set values, resulting in inconsistent pressure control under different production batches or environmental conditions. At the same time, it lacks the ability to adjust the pressure in real time, affecting sealing quality, increasing material waste, and reducing the overall efficiency of the production line. It achieves the technical effect of using sensing technology and control algorithms to automatically monitor and adjust the heat-sealing pressure, thereby improving sealing quality, enhancing adaptability to environmental changes, and improving production efficiency.

[0004] This application provides a method for controlling the heat-sealing pressure of polyethylene hot-melt film. The method is applied to a device for controlling the heat-sealing pressure of polyethylene hot-melt film, comprising: acquiring multiple film parameters of the polyethylene hot-melt film; determining a heat-sealing pressure value based on the multiple film parameters; constructing a control prediction model; synchronizing the multiple film parameters with the heat-sealing pressure value to the control prediction model; outputting a first control signal; performing simulated heat-sealing pressure control on the polyethylene hot-melt film based on the first control signal; generating a first simulated control effect; performing backtracking feedback based on the first simulated control effect; generating control feedback parameters; dynamically adjusting the first control signal based on the control feedback parameters; and generating a second control signal; and sending the second control signal to a control terminal for intelligent control of the heat-sealing pressure of the polyethylene hot-melt film.

[0005] In a possible implementation, multiple film parameters of the polyethylene hot-melt film are collected, and a heat-sealing pressure value is determined based on these parameters. The following processing is then performed: a sensor network is constructed, and data is collected from the polyethylene hot-melt film according to a sensing cycle to obtain multiple film parameters; the multiple film parameters are standardized, and multiple parameter features are extracted based on these standard film parameters; a historical heat-sealing pressure dataset is retrieved, and the multiple film standard parameters are iterated and associated with the historical heat-sealing pressure dataset to construct a pressure value database; the multiple parameter features are used as input variables and synchronized to the pressure value database to determine the heat-sealing pressure value, wherein there is a correspondence between the heat-sealing pressure value and the multiple film parameters.

[0006] In a possible implementation, the historical heat-sealing pressure dataset is retrieved, and the multiple film standard parameters are iterated and associated with the historical heat-sealing pressure dataset to construct a pressure value database. The following processes are then performed: retrieving the historical heat-sealing pressure dataset, which consists of heat-sealing pressure values ​​from multiple production batches; iterating through the multiple film standard parameters and controlling the matching with the heat-sealing pressure values ​​from the multiple production batches, and formulating association rules based on the matching results; associating the multiple film standard parameters with the heat-sealing pressure values ​​from the multiple production batches according to the association rules to construct a parameter-pressure lookup table; and integrating the parameter-pressure lookup table and importing the integration result into the pressure value database.

[0007] In a possible implementation, a control prediction model is constructed, and the multiple film parameters are synchronized to the control prediction model in conjunction with the heat sealing pressure value. A first control signal is output, and the following processing is performed: the changes of the multiple film parameters are predicted using time series analysis to determine the changing trend of the film parameters; a target heat sealing pressure value is set according to the changing trend of the film parameters and the parameter-pressure reference table; an error is calculated based on the target heat sealing pressure value and the heat sealing pressure value to generate a heat sealing pressure error value; an objective function is constructed based on the heat sealing pressure error value; the objective function is integrated into the control prediction model for prediction to generate a pressure control prediction result, and the first control signal is output.

[0008] In a possible implementation, backtracking feedback is performed based on the first simulated control effect to generate control feedback parameters. The first control signal is then dynamically adjusted according to these parameters to generate a second control signal. The following processes are performed: a feedback mechanism is established to synchronize the first simulated control effect to the feedback mechanism for backtracking feedback, generating control feedback parameters; a control optimization module is activated based on the control feedback parameters, and the first control signal is analyzed by the control optimization module to generate multiple control influence information, including external control influence information and internal control influence information; a weight analysis is performed on the external and internal control influence information to determine multiple weight coefficients; the external and internal control influence information are sorted in descending order based on the multiple weight coefficients to generate an influence control sequence; the first control signal is dynamically adjusted by the control optimization module according to the influence control sequence and the external and internal control influence information to generate the second control signal.

[0009] In a possible implementation, the first simulated control effect is synchronized to the feedback mechanism for backtracking feedback, generating control feedback parameters, and the following processing is performed: error analysis is performed through the feedback mechanism, and based on the first simulated control effect, it is determined whether the heat sealing pressure error value of the first control signal is greater than or equal to a preset error index; if the heat sealing pressure error value of the first control signal is greater than or equal to the preset error index, an anomaly tag is generated, and the heat sealing pressure value is identified based on the anomaly tag, generating a heat sealing pressure identification result; the multiple film parameters are traversed according to the heat sealing pressure identification result for backtracking extraction, generating a film anomaly parameter set; the film anomaly parameter set is added to the control feedback parameters.

[0010] In a possible implementation, the control optimization module dynamically adjusts the first control signal according to the influence control sequence, combined with the external control influence information and the internal control influence information, to generate the second control signal, and performs the following processing: the control optimization module parses the first control signal and calculates the deviation trend of the first control signal; calculates a first optimization step size based on the deviation trend and the external control influence information; calculates a second optimization step size based on the deviation trend and the internal control influence information; fuses the first optimization step size and the second optimization step size according to the influence control sequence to determine a third optimization step size; and dynamically adjusts the first control signal based on the third optimization step size to generate the second control signal.

[0011] This application also provides a heat-sealing pressure control device for polyethylene hot-melt film, comprising: a numerical determination module, which is used to collect multiple film parameters of the polyethylene hot-melt film and determine a heat-sealing pressure value based on the multiple film parameters; a first signal output module, which is used to construct a control prediction model, synchronize the multiple film parameters with the heat-sealing pressure value to the control prediction model, and output a first control signal; a simulation control module, which is used to perform simulated control of the heat-sealing pressure of the polyethylene hot-melt film based on the first control signal and generate a first simulated control effect; a dynamic adjustment module, which is used to perform backtracking feedback based on the first simulated control effect, generate control feedback parameters, and dynamically adjust the first control signal based on the control feedback parameters to generate a second control signal; and an intelligent control module, which is used to send the second control signal to a control terminal to intelligently control the heat-sealing pressure of the polyethylene hot-melt film.

[0012] One or more technical solutions provided in this application have at least the following technical effects or advantages: The heat-sealing pressure control method and apparatus for polyethylene hot melt film provided in this application relate to the field of heat-sealing pressure control technology. It solves the technical problems of traditional heat-sealing pressure control systems that rely on manual experience or fixed set values, resulting in inconsistent pressure control under different production batches or environmental conditions. At the same time, they lack the ability to adjust pressure in real time, affecting sealing quality, increasing material waste, and reducing the overall efficiency of the production line. The method and apparatus achieve the technical effect of automatically monitoring and adjusting heat-sealing pressure by using sensing technology and control algorithms, thereby improving sealing quality, enhancing adaptability to environmental changes, and improving production efficiency. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings of the embodiments of this application will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the apparatus according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0014] Figure 1 A schematic flowchart illustrating the heat-sealing pressure control method for polyethylene hot melt film provided in this application embodiment; Figure 2 This is a schematic diagram of the heat-sealing pressure control device for polyethylene hot melt film provided in an embodiment of this application. Detailed Implementation

[0015] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or apparatuses. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0018] This application provides a method for controlling the heat-sealing pressure of polyethylene hot-melt film, which is applied to a device for controlling the heat-sealing pressure of polyethylene hot-melt film, such as... Figure 1 As shown, the method includes: Step A100 involves collecting multiple film parameters of the polyethylene hot melt film and determining the heat-sealing pressure value based on these parameters. In one possible implementation, step A100 further includes step A110, constructing a sensor network to collect data from the polyethylene hot melt film according to a sensing cycle, thereby obtaining multiple film parameters. Step A120 involves standardizing the multiple film parameters and extracting multiple parameter features based on these standard parameters. Firstly, a sensor network for monitoring the heat-sealing process of the polyethylene hot melt film is constructed. The aim is to determine the optimal heat-sealing pressure value through precise data acquisition and analysis. This involves selecting sensors capable of accurately measuring key parameters of the polyethylene hot melt film during the heat-sealing process, such as temperature, thickness, tension, and conductivity. These sensors need to have high precision, high stability and fast response capabilities. Therefore, data acquisition devices with timed acquisition functions can be used to ensure that data is collected according to the preset sensing cycle (such as per second, per millisecond, etc.). Further, multiple sensor nodes can be deployed to cover the entire production line or key heat-sealing areas. Each node is responsible for collecting film parameters in a specific area and aggregating the data to the central controller or cloud server. According to the set sensing cycle, various parameters of the film, such as temperature, thickness and tension, are captured in real time.

[0019] Furthermore, the multiple film parameters are standardized, and multiple parameter features are extracted based on these standard parameters. This involves using appropriate standardization methods (such as Z-score standardization, minimum-maximum standardization, etc.) to transform data of different dimensions to the same scale. From the standardized data, parameter features that significantly affect the heat-sealing pressure are extracted, such as temperature fluctuation range, thickness uniformity, and tension stability. Then, statistical analysis, machine learning feature selection algorithms, and other methods are used to further screen and optimize the extracted parameter features that significantly affect the heat-sealing pressure. Finally, multiple parameter features are extracted based on the multiple film standard parameters to achieve precise control of the heat-sealing process of polyethylene hot melt film in the later stages.

[0020] Execute step A130, retrieve the historical heat sealing pressure dataset, iterate through the multiple thin film standard parameters and associate them with the historical heat sealing pressure dataset to construct a pressure value database; In one possible implementation, step A130 further includes step A131, retrieving the historical heat-sealing pressure dataset, which consists of heat-sealing pressure values ​​from multiple production batches; executing step A132, iterating through the multiple film standard parameters and controlling the matching with the heat-sealing pressure values ​​from the multiple production batches, and formulating association rules based on the matching results; executing step A133, associating the multiple film standard parameters with the heat-sealing pressure values ​​from the multiple production batches according to the association rules, and constructing a parameter-pressure lookup table; executing step A134, integrating based on the parameter-pressure lookup table, and importing the integration result into the pressure value database.

[0021] First, retrieve the historical heat sealing pressure dataset containing heat sealing pressure values ​​of multiple production batches. The historical heat sealing pressure dataset contains heat sealing pressure values ​​of multiple production batches and may include heat sealing pressure records for each production batch, as well as metadata information such as production conditions, film type, and production time.

[0022] Furthermore, the process involves iterating through multiple standard film parameters one by one and matching them with the heat-sealing pressure values ​​of multiple production batches. This means matching the heat-sealing pressure value of each production batch in the historical heat-sealing pressure dataset with the corresponding film parameter or a similar film parameter. Since the film parameters in the historical data may not be completely consistent with the current standard parameters, some fuzzy matching or range matching is required. Simultaneously, based on the matching results, the relationship between heat-sealing pressure and film parameters is analyzed, and association rules are formulated. These association rules can be set using statistical methods such as regression analysis and cluster analysis, or through expert experience. The association rules should clearly specify which film parameters have a significant impact on heat-sealing pressure and how these parameters affect the heat-sealing pressure. Further, according to the manufacturing process... The system establishes association rules to link multiple film standard parameters with the heat-sealing pressure values ​​of multiple production batches. This involves sequentially mapping each standard parameter combination to the heat-sealing pressure values ​​of multiple production batches, determining one or more corresponding heat-sealing pressure ranges or specific values ​​for each standard parameter combination, and compiling the association results into a parameter-pressure lookup table. This table lists recommended heat-sealing pressure values ​​or ranges for different film parameter combinations and can be in multidimensional table format, where rows represent different film parameter combinations and columns represent heat-sealing pressure values ​​or ranges. Finally, the parameter-pressure lookup table is further integrated by removing duplicates and invalid entries, optimizing the data structure to improve query efficiency, and importing the integrated results into a pressure value database for application.

[0023] In step A140, the multiple parameter features are used as input variables and synchronized to the pressure value database to determine the heat sealing pressure value. The heat sealing pressure value corresponds to the multiple film parameters.

[0024] Using multiple parameter features as input variables and the corresponding historical heat-sealing pressure values ​​as target variables, and retrieving them from a pressure value database, means using these multiple parameter features as query conditions to search the pressure value database. This can be done by traversing or indexing the parameter-pressure lookup table in the database. The purpose of the query is to find the historical heat-sealing pressure value record that best matches or is closest to the current parameter features. Further, based on the query results, the heat-sealing pressure value corresponding to the current multiple parameter features is determined. If a record in the pressure value database completely matches the current multiple parameter features, the heat-sealing pressure value in that record is directly used. If no record completely matches the current multiple parameter features is found in the pressure value database, the nearest neighbor method can be used. That is, the record in the database closest to the current parameter features is selected, and the heat-sealing pressure value in that record is used as an approximation of the current heat-sealing pressure value, thereby determining the heat-sealing pressure value. Furthermore, the heat-sealing pressure value has a correspondence with the multiple film parameters.

[0025] Execute step A200, construct a control prediction model, synchronize the multiple film parameters with the heat sealing pressure value to the control prediction model, and output the first control signal; In one possible implementation, step A200 further includes step A210, which uses time series analysis to predict the changes in the multiple thin film parameters and determine the trend of thin film parameter changes; step A220, which sets a target heat-sealing pressure value based on the trend of thin film parameter changes and the parameter-pressure comparison table; step A230, which calculates the error between the target heat-sealing pressure value and the heat-sealing pressure value to generate a heat-sealing pressure error value, and constructs an objective function based on the heat-sealing pressure error value; and step A240, which integrates the objective function into the control prediction model for prediction, generates a pressure control prediction result, and outputs the first control signal.

[0026] Before using time series analysis to predict the changes of multiple thin film parameters, it is first necessary to collect a historical set of thin film parameters, including timestamps and corresponding parameter values ​​such as thickness, width, and temperature. Based on the characteristics of the thin film parameters in the historical set and the prediction requirements, a time series analysis model is constructed. The time series analysis model can be ARIMA, LSTM (Long Short-Term Memory Network), etc. Then, multiple thin film parameters are synchronized to the time series analysis model for trend prediction to determine the changing trends of multiple thin film parameters.

[0027] Furthermore, by consulting a parameter-pressure lookup table based on the changing trends of the thin film parameters, the corresponding heat-sealing pressure range or specific value is determined. If the parameter-pressure lookup table provides a specific value, it is directly set as the target heat-sealing pressure value. If the table provides a range, other factors such as production experience and material properties are needed to determine the specific target heat-sealing pressure value. The determined heat-sealing pressure value is compared with the target heat-sealing pressure value, and the error between them is calculated. This error can be an absolute error, a relative error, or a squared error, etc. Simultaneously, an objective function is constructed based on the error value. This objective function reflects the magnitude of the error and guides the control system to adjust in the direction of reducing the error. For example, the mean square error (MSE) can be used as the objective function. Finally, the constructed objective function is integrated into the control prediction model. This control prediction model can be a complex model combining time series prediction, error feedback, and control algorithms. The integrated control prediction model is used for prediction and control. The control prediction model can generate pressure control prediction results based on the predicted values ​​of the thin film parameters, the target heat-sealing pressure value, and the error between the actual heat-sealing pressure value. Based on the pressure control prediction results, a corresponding first control signal is generated. The first control signal is used to adjust the pressure setting of the heat sealing equipment to achieve the target heat sealing effect, thereby improving production efficiency and product quality.

[0028] Execute step A300, perform heat sealing pressure simulation control on the polyethylene hot melt film according to the first control signal, and generate the first simulation control effect; A simulation environment is constructed using simulation software or a physical model. Based on the actual heat-sealing equipment and film characteristics, corresponding parameters are set in the simulation environment, such as film thickness, width, initial temperature, heat-sealing temperature, and heat-sealing time. The parsed first control signal is converted into executable instructions in the simulation environment, such as adjusting the pressure output of the simulated heat-sealing machine. The heat-sealing process in the simulation environment can be performed by dynamically adjusting the heat-sealing pressure according to the control instructions, simulating the deformation, melting, and bonding processes of the film under pressure. Simultaneously, during the simulation, changes in key parameters, such as film temperature distribution, pressure changes, and melting state, are monitored and recorded in real time. The heat-sealing effect of the first control signal on the polyethylene hot-melt film is evaluated based on the simulation results, including heat-sealing strength, sealing performance, and appearance quality. This evaluation process can be performed by comparing the simulation results with standard samples or expected targets. Based on the evaluation results, the first simulation control effect corresponding to the simulation results of the first control signal is output.

[0029] Execute step A400, perform backtracking feedback based on the first simulated control effect, generate control feedback parameters, dynamically adjust the first control signal according to the control feedback parameters, and generate a second control signal; In one possible implementation, step A400 further includes step A410, establishing a feedback mechanism to synchronize the first simulated control effect to the feedback mechanism for backtracking feedback, generating control feedback parameters; in another possible implementation, step A410 further includes step A411, performing error analysis through the feedback mechanism, determining whether the heat sealing pressure error value of the first control signal is greater than or equal to a preset error index based on the first simulated control effect; executing step A412, if the heat sealing pressure error value of the first control signal is greater than or equal to the preset error index, generating an anomaly tag, identifying the heat sealing pressure value based on the anomaly tag, generating a heat sealing pressure identification result; executing step A413, traversing the multiple film parameters for backtracking extraction according to the heat sealing pressure identification result, generating a film anomaly parameter set; executing step A414, adding the film anomaly parameter set to the control feedback parameters.

[0030] Error analysis through a feedback mechanism involves comparing the heat-sealing pressure value in the first simulated control effect with the actual target heat-sealing pressure value, calculating the difference or percentage error between the two, determining the heat-sealing pressure error value of the first control signal, and judging whether the heat-sealing pressure error value of the first control signal is greater than or equal to a preset error index based on the first simulated control effect. This means comparing the calculated error value with a preset error index, which is pre-set based on factors such as production needs, product standards, and equipment capabilities, and is used to determine whether the heat-sealing pressure control meets the requirements. If the heat-sealing pressure error value of the first control signal is greater than or equal to the preset error index, it is considered that the current control signal is abnormal, and an abnormality label is generated to identify the abnormal state. Based on the abnormality label, the heat-sealing pressure value is identified, generating a heat-sealing pressure identification result. The heat-sealing pressure identification result is used for rapid identification and location of problems in subsequent processing and analysis of abnormal parameters. Further, based on the heat-sealing pressure identification result, multiple film parameters stored in the above-mentioned records are traversed. These multiple film parameters may include film thickness, width, material, temperature, etc., and all of them affect the heat-sealing pressure. Backtracking extraction is performed on these multiple film parameters according to the heat-sealing pressure identification result. This means that during the traversal process, the correlation between each film parameter and the heat-sealing pressure error value is analyzed. Methods such as statistical analysis, machine learning, or expert experience can be used to identify film parameters that are abnormally related to the current heat-sealing pressure error value, thereby generating a set of abnormal film parameters. Finally, this set of abnormal film parameters is added to the control feedback parameters. These control feedback parameters are used for subsequent control strategy adjustment and optimization to improve the control accuracy and stability of the heat-sealing pressure.

[0031] Step A420 involves activating the control optimization module based on the control feedback parameters, performing control analysis on the first control signal through the control optimization module, and generating multiple control influence information, including external control influence information and internal control influence information; Step A430 involves performing weight analysis on the external control influence information and the internal control influence information to determine multiple weight coefficients; Step A440 involves arranging the external control influence information and the internal control influence information in descending order based on the multiple weight coefficients to generate an influence control sequence. Activating the control optimization module according to the control feedback parameters involves initializing the control optimization module using the control feedback parameters, setting initial conditions and algorithm parameters, and then performing control analysis on the first control signal through the control optimization module. This means conducting in-depth analysis of the first control signal to identify its potential impact on the heat sealing pressure control process, and dividing the control impact into external control impact information and internal control impact information. The external control impact information includes changes in the external environment and external interference, while the internal control impact information includes changes in internal system parameters and equipment wear.

[0032] Further considering the importance, urgency, and controllability of multiple control influence information on the first control signal, a weight analysis is performed on external and internal control influence information. Based on this, the weight coefficients of external and internal control influence information are determined. The greater the importance, urgency, and controllability of the first control signal, the higher the corresponding weight coefficient. Then, according to the weight coefficients, the external and internal control influence information are arranged in descending order, that is, the one with the largest weight coefficient is considered to have the greatest influence on the first control signal and is placed in first order. This process is iteratively sorted to generate an influence control sequence, and factors with high weights are processed first, thereby improving the stability and efficiency of the system.

[0033] In step A450, the control optimization module dynamically adjusts the first control signal according to the influence control sequence, combined with the external control influence information and the internal control influence information, to generate the second control signal.

[0034] In one possible implementation, step A450 further includes step A451, parsing the first control signal through the control optimization module and calculating the deviation trend of the first control signal; executing step A452, calculating a first optimization step size based on the deviation trend and the external control influence information; executing step A453, calculating a second optimization step size based on the deviation trend and the internal control influence information; executing step A454, fusing the first optimization step size and the second optimization step size according to the influence control sequence to determine a third optimization step size; and executing step A455, dynamically adjusting the first control signal based on the third optimization step size to generate the second control signal.

[0035] First, the control optimization module receives and parses the first control signal. Then, based on the control optimization module, it analyzes the difference between the current state and the desired state of the first control signal, i.e., the deviation value, and calculates the trend of the deviation value, i.e. the deviation trend. The deviation trend is used to characterize whether the control signal is approaching or moving away from the target value.

[0036] Further, the first optimization step size is calculated based on the deviation trend and external control influence information. This means recording the degree of influence of the deviation trend and external control influence information on the control effect. The external control influence information may include environmental factors such as temperature and humidity, as well as external interference such as noise and vibration, or other external system states. The first optimization step size is calculated based on the recorded degree of influence. The first optimization step size can be used to offset the influence generated by the external factors.

[0037] Further, the second optimization step size is calculated based on the deviation trend and the internal control influence information. This means recording the degree of influence of the deviation trend and the internal control influence information on the control effect. The internal control influence information is usually related to the internal state, performance parameters or historical data of the system. The second optimization step size is calculated based on the recorded degree of influence. The second optimization step size can be used to optimize the internal operation of the system to improve control accuracy and stability.

[0038] Finally, the first and second optimized step sizes are fused according to the influence control sequence. This means that the step size with the highest priority is selected as the benchmark according to the influence control sequence, and then the priority and size of other step sizes are adjusted appropriately. The first and second optimized step sizes are weighted and summed according to the weight coefficient of each step size to obtain the third optimized step size. The data fusion of the first and second optimized step sizes is completed to generate the third optimized step size. The third optimization step size of Su Sohu combines the comprehensive influence of external and internal factors to achieve the optimal control effect. Dynamic adjustment of the first control signal according to the third optimization step size involves selecting appropriate adjustment algorithms and parameters after obtaining the third optimization step size and applying them to the dynamic adjustment of the first control signal. This involves determining the adjustment strategy and executing the adjustment strategy on the first control signal, including changing the signal's amplitude, frequency, phase, or other parameters to make it closer to the target control state. During the adjustment process, the control effect, such as changes in heat sealing pressure, can be continuously monitored, and real-time feedback data can be collected. Based on the monitoring feedback data, the system may need to perform multiple iterations of optimization to gradually approach the optimal control state. Each iteration may involve recalculating the optimization step size, adjusting the adjustment strategy, or fine-tuning the control parameters. When the system reaches a stable control state, i.e., the control effect remains within the expected range with minimal fluctuations, a second control signal is generated. This second control signal is more accurate and adaptable to the current system state and environmental conditions, thereby improving the performance and stability of the control system.

[0039] Next, step A500 is executed, in which the second control signal is sent to the control terminal to intelligently control the heat-sealing pressure of the polyethylene hot melt film.

[0040] The second control signal is sent to the control terminal through an appropriate communication protocol and interface. Upon receiving the second control signal, the control terminal performs necessary verification and parsing to ensure signal integrity and accuracy. The control terminal can have a built-in intelligent control algorithm to calculate corresponding control parameters such as voltage, current, and heating time based on the received second control signal. These control parameters directly affect the heating element of the heat sealing machine, thereby controlling the heat sealing pressure of the polyethylene hot melt film. The control terminal outputs the calculated control parameters to the actuators of the heat sealing machine (such as heating plates and cylinders) to achieve precise control of the heat sealing pressure. During the heat sealing process, the control terminal can... The control terminal continuously receives real-time feedback data from the heat sealing machine (such as temperature and pressure sensor readings) and adjusts the control parameters in real time based on this data to ensure the stability and consistency of heat sealing quality. At the same time, the control terminal also monitors the entire heat sealing process and records key data (such as heat sealing time, temperature curve, pressure changes, etc.) for subsequent analysis and optimization. Finally, when the heat sealing process is completed, the control terminal sends a completion signal and prepares to receive the next heat sealing task. This achieves intelligent control of the heat sealing pressure of polyethylene hot melt film, which not only reduces the interference of human factors, but also improves the accuracy and stability of control, making it an important component of modern industrial automated production.

[0041] This application's embodiments solve the technical problems of traditional heat-sealing pressure control systems that rely on manual experience or fixed set values, resulting in inconsistent pressure control under different production batches or environmental conditions. Furthermore, they lack the ability to adjust pressure in real time, affecting sealing quality, increasing material waste, and reducing the overall efficiency of the production line. The embodiments achieve the technical effect of using sensing technology and control algorithms to automatically monitor and adjust heat-sealing pressure, thereby improving sealing quality, enhancing adaptability to environmental changes, and increasing production efficiency.

[0042] In the above text, refer to Figure 1 A method for controlling the heat-sealing pressure of a polyethylene hot-melt film according to embodiments of this application is described in detail. Next, reference will be made to... Figure 2 This application describes a heat-sealing pressure control device for a polyethylene hot melt film according to an embodiment of the present application.

[0043] The heat-sealing pressure control device for polyethylene hot-melt film according to embodiments of this application solves the technical problems of traditional heat-sealing pressure control systems that rely on manual experience or fixed set values, leading to inconsistencies in pressure control under different production batches or environmental conditions. Furthermore, these systems lack the ability to adjust pressure in real time, affecting sealing quality, increasing material waste, and reducing the overall efficiency of the production line. The device achieves the technical effect of automatically monitoring and adjusting heat-sealing pressure using sensing technology and control algorithms, thereby improving sealing quality, enhancing adaptability to environmental changes, and increasing production efficiency. The heat-sealing pressure control device for polyethylene hot-melt film includes: a numerical determination module 10, a first signal output module 20, an analog control module 30, a dynamic adjustment module 40, and an intelligent control module 50.

[0044] The numerical determination module 10 is used to collect multiple film parameters of polyethylene hot melt film and determine the heat sealing pressure value based on the multiple film parameters. First signal output module 20, the first signal output module 20 is used to construct a control prediction model, synchronize the multiple film parameters with the heat sealing pressure value to the control prediction model, and output a first control signal; Simulation control module 30 is used to simulate and control the heat sealing pressure of polyethylene hot melt film according to the first control signal, and generate a first simulation control effect. The dynamic adjustment module 40 is used to perform backtracking feedback based on the first simulated control effect, generate control feedback parameters, and dynamically adjust the first control signal according to the control feedback parameters to generate a second control signal. The intelligent control module 50 is used to send the second control signal to the control terminal to intelligently control the heat sealing pressure of the polyethylene hot melt film.

[0045] The specific configuration of the numerical determination module 10 will be described in detail below. As mentioned above, multiple film parameters of the polyethylene hot melt film are collected, and the heat sealing pressure value is determined based on the multiple film parameters. The numerical determination module 10 may further include: a sensing acquisition unit for constructing a sensing network, which performs data sensing and acquisition on the polyethylene hot melt film according to the sensing cycle to obtain multiple film parameters; a standardization processing unit for standardizing the multiple film parameters and extracting multiple parameter features based on the multiple film standard parameters; a first association unit for retrieving a historical heat sealing pressure dataset, traversing the multiple film standard parameters and associating them with the historical heat sealing pressure dataset to construct a pressure value database; and a pressure value determination unit for using the multiple parameter features as input variables and synchronizing them to the pressure value database to determine the heat sealing pressure value, wherein the heat sealing pressure value corresponds to the multiple film parameters.

[0046] The specific configuration of the first association unit will be described in detail below. As mentioned above, the historical heat-sealing pressure dataset is retrieved, and the multiple film standard parameters are associated with the historical heat-sealing pressure dataset to construct a pressure value database. The first association unit may further include: a first retrieval unit for retrieving the historical heat-sealing pressure dataset, which consists of heat-sealing pressure values ​​from multiple production batches; a first traversal unit for controlling and matching the multiple film standard parameters with the heat-sealing pressure values ​​from the multiple production batches, and formulating association rules based on the matching results; a second association unit for associating the multiple film standard parameters with the heat-sealing pressure values ​​from the multiple production batches according to the association rules, and constructing a parameter-pressure lookup table; and a data integration unit for integrating the data based on the parameter-pressure lookup table and importing the integration results into the pressure value database.

[0047] The specific configuration of the first signal output module 20 will be described in detail below. As mentioned above, a control prediction model is constructed, and the multiple film parameters are synchronized to the control prediction model in conjunction with the heat sealing pressure value to output a first control signal. The first signal output module 20 may further include: a change prediction unit for predicting the changes of the multiple film parameters using time series analysis to determine the change trend of the film parameters; a target setting unit for setting a target heat sealing pressure value based on the change trend of the film parameters in conjunction with the parameter-pressure reference table; a first calculation unit for calculating the error between the target heat sealing pressure value and the heat sealing pressure value to generate a heat sealing pressure error value, and constructing an objective function based on the heat sealing pressure error value; and a prediction unit for integrating the objective function into the control prediction model for prediction, generating a pressure control prediction result, and outputting the first control signal.

[0048] The specific configuration of the dynamic adjustment module 40 will be described in detail below. As mentioned above, based on the first simulated control effect, backtracking feedback is performed to generate control feedback parameters. The first control signal is dynamically adjusted according to the control feedback parameters to generate a second control signal. The dynamic adjustment module 40 may further include: a first backtracking unit for establishing a feedback mechanism, synchronizing the first simulated control effect to the feedback mechanism for backtracking feedback, and generating control feedback parameters; a control analysis unit for activating a control optimization module based on the control feedback parameters, performing control analysis on the first control signal through the control optimization module, and generating multiple control influence information, including external control influence information and internal control influence information; a weight analysis unit for performing weight analysis based on the external control influence information and the internal control influence information to determine multiple weight coefficients; a sequence generation unit for arranging the external control influence information and the internal control influence information in descending order based on the multiple weight coefficients to generate an influence control sequence; and a first adjustment unit for dynamically adjusting the first control signal according to the influence control sequence and the external control influence information and the internal control influence information through the control optimization module to generate the second control signal.

[0049] The specific configuration of the dynamic adjustment module 40 will be described in detail below. As mentioned above, the first simulated control effect is synchronized to the feedback mechanism for backtracking feedback to generate control feedback parameters. The dynamic adjustment module 40 may further include: an error analysis unit for performing error analysis through the feedback mechanism, and determining whether the heat sealing pressure error value of the first control signal is greater than or equal to a preset error index based on the first simulated control effect; an identification unit for generating an anomaly tag if the heat sealing pressure error value of the first control signal is greater than or equal to the preset error index, and identifying the heat sealing pressure value based on the anomaly tag to generate a heat sealing pressure identification result; a second backtracking unit for traversing the multiple film parameters according to the heat sealing pressure identification result to perform backtracking extraction and generate a film anomaly parameter set; and an adding unit for adding the film anomaly parameter set to the control feedback parameters.

[0050] The specific configuration of the dynamic adjustment module 40 will be described in detail below. As mentioned above, the control optimization module dynamically adjusts the first control signal according to the influence control sequence, combined with the external control influence information and the internal control influence information, to generate the second control signal. The dynamic adjustment module 40 may further include: a parsing unit for parsing the first control signal through the control optimization module and calculating the deviation trend of the first control signal; a second calculation unit for calculating a first optimization step size based on the deviation trend and the external control influence information; a third calculation unit for calculating a second optimization step size based on the deviation trend and the internal control influence information; a fourth calculation unit for fusing the first optimization step size and the second optimization step size according to the influence control sequence to determine a third optimization step size; and a second adjustment unit for dynamically adjusting the first control signal based on the third optimization step size to generate the second control signal.

[0051] The heat-sealing pressure control device for polyethylene hot melt film provided in this application embodiment can execute the heat-sealing pressure control method for polyethylene hot melt film provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method.

[0052] Although this application makes various references to certain modules in the apparatus according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. 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 each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this application.

[0053] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand 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 within the scope of protection of this application.

Claims

1. A method for controlling the heat-sealing pressure of polyethylene hot-melt film, characterized in that, The method includes: Multiple film parameters of polyethylene hot melt film are collected, and the heat sealing pressure value is determined based on the multiple film parameters; A control prediction model is constructed, and the multiple film parameters are synchronized to the control prediction model in combination with the heat sealing pressure value, and a first control signal is output. Based on the first control signal, the heat sealing pressure of the polyethylene hot melt film is simulated and controlled to generate the first simulated control effect. Based on the first simulated control effect, backtracking feedback is performed to generate control feedback parameters. The first control signal is then dynamically adjusted according to the control feedback parameters to generate a second control signal. The second control signal is sent to the control terminal to intelligently control the heat sealing pressure of the polyethylene hot melt film.

2. The method for controlling the heat-sealing pressure of polyethylene hot-melt film as described in claim 1, characterized in that, The method involves collecting multiple film parameters of a polyethylene hot-melt film and determining the heat-sealing pressure value based on these parameters. A sensor network is constructed, and data is collected from the polyethylene hot melt film according to the sensing cycle through the sensor network to obtain multiple film parameters; The multiple thin film parameters are standardized, and multiple parameter features are extracted based on the multiple thin film standard parameters; Retrieve historical heat-sealing pressure datasets, iterate through the multiple thin film standard parameters and associate them with the historical heat-sealing pressure datasets to construct a pressure value database; The multiple parameter features are used as input variables and synchronized to the pressure value database to determine the heat sealing pressure value. The heat sealing pressure value has a corresponding relationship with the multiple film parameters.

3. The method for controlling the heat-sealing pressure of polyethylene hot-melt film as described in claim 2, characterized in that, The method involves retrieving historical heat-sealing pressure datasets, iterating through multiple thin-film standard parameters, and associating them with the historical heat-sealing pressure datasets to construct a pressure value database. Retrieve the historical heat sealing pressure dataset, which consists of heat sealing pressure values ​​from multiple production batches; The multiple film standard parameters are iterated and matched with the heat sealing pressure values ​​of the multiple production batches, and association rules are formulated based on the matching results. According to the association rules, the multiple film standard parameters are associated with the heat sealing pressure values ​​of the multiple production batches to construct a parameter-pressure lookup table; The parameters and pressures are integrated based on the parameter-pressure comparison table, and the integration results are imported into the pressure value database.

4. The method for controlling the heat-sealing pressure of polyethylene hot-melt film as described in claim 3, characterized in that, Constructing a control prediction model, synchronizing the multiple film parameters with the heat sealing pressure value to the control prediction model, and outputting a first control signal, the method includes: Time series analysis was used to predict the changes in the multiple thin film parameters and determine the changing trends of the thin film parameters. The target heat sealing pressure value is set based on the changing trend of the film parameters and the parameter-pressure comparison table; Based on the target heat sealing pressure value and the heat sealing pressure value, an error value for heat sealing pressure is calculated to generate a heat sealing pressure error value, and a target function is constructed based on the heat sealing pressure error value. The objective function is integrated into the control prediction model for prediction, generating a pressure control prediction result, and the first control signal is output.

5. The method for controlling the heat-sealing pressure of polyethylene hot-melt film as described in claim 1, characterized in that, Based on the first simulated control effect, backtracking feedback is performed to generate control feedback parameters. The first control signal is then dynamically adjusted according to the control feedback parameters to generate a second control signal. The method includes: Establish a feedback mechanism to synchronize the first simulated control effect to the feedback mechanism for backtracking feedback and generate control feedback parameters; Based on the control feedback parameters, the control optimization module is activated, and the control optimization module performs control analysis on the first control signal to generate multiple control influence information, which includes external control influence information and internal control influence information. Based on the external control impact information and the internal control impact information, a weight analysis is performed to determine multiple weight coefficients; Based on the multiple weighting coefficients, the external control influence information and the internal control influence information are sorted in descending order to generate an influence control sequence. The control optimization module dynamically adjusts the first control signal according to the influence control sequence, combined with the external control influence information and the internal control influence information, to generate the second control signal.

6. The method for controlling the heat-sealing pressure of polyethylene hot-melt film as described in claim 5, characterized in that, The method of synchronizing the first simulated control effect to the feedback mechanism for backtracking feedback and generating control feedback parameters includes: Error analysis is performed through the feedback mechanism, and the heat sealing pressure error value of the first control signal is determined to be greater than or equal to the preset error index based on the first simulation control effect. If the heat sealing pressure error value of the first control signal is greater than or equal to the preset error index, an anomaly tag is generated, and the heat sealing pressure value is identified based on the anomaly tag to generate a heat sealing pressure identification result. Based on the heat sealing pressure identification result, the multiple film parameters are backtracked and extracted to generate a set of abnormal film parameters; The set of abnormal thin film parameters is added to the control feedback parameters.

7. The method for controlling the heat-sealing pressure of polyethylene hot-melt film as described in claim 5, characterized in that, The control optimization module dynamically adjusts the first control signal according to the influence control sequence, combined with the external control influence information and the internal control influence information, to generate the second control signal. The method includes: The control optimization module analyzes the first control signal and calculates the deviation trend of the first control signal. The first optimization step size is calculated based on the deviation trend and the external control influence information. The second optimization step size is calculated based on the deviation trend and the internal control impact information. The first optimization step size and the second optimization step size are fused according to the influence control sequence to determine the third optimization step size; The first control signal is dynamically adjusted based on the third optimization step size to generate the second control signal.

8. A heat-sealing pressure control system for polyethylene hot-melt film, characterized in that, The system is used to implement the heat-sealing pressure control method for polyethylene hot melt film according to any one of claims 1-7, the system comprising: A numerical determination module is used to collect multiple film parameters of polyethylene hot melt film and determine the heat sealing pressure value based on the multiple film parameters. The first signal output module is used to construct a control prediction model, synchronize the multiple film parameters with the heat sealing pressure value to the control prediction model, and output a first control signal. A simulation control module is used to simulate and control the heat sealing pressure of the polyethylene hot melt film according to the first control signal, and generate a first simulation control effect. A dynamic adjustment module is used to perform backtracking feedback based on the first simulated control effect, generate control feedback parameters, and dynamically adjust the first control signal according to the control feedback parameters to generate a second control signal. The intelligent control module is used to send the second control signal to the control terminal to intelligently control the heat sealing pressure of the polyethylene hot melt film.

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