Engineering plastic extrusion control system

Abstract

The invention discloses an engineering plastic extrusion control system, and relates to the technical field of plastic processing, and the engineering plastic extrusion control system comprises the following steps: obtaining basic configuration information and a denaturation threshold value of target engineering plastic; determining a second constraint condition based on basic configuration information by taking a denaturation threshold as a first constraint condition, and supervising and training an optimization control module in combination with the basic configuration of the extruder; an extrusion task is read, extrusion full-cycle control analysis under constraint condition limitation is carried out in combination with an optimization control module, and a dynamic extrusion scheme is determined; executing a dynamic extrusion scheme, and determining a feedback regulation threshold value; carrying out extrusion state evaluation on an extrusion channel of an extruder, and positioning a feedback regulation point by combining with a feedback regulation threshold value with mold-based molding and curing state evaluation; and based on the feedback regulation point, performing feedback extrusion regulation based on the extrusion control system. The technical problems of low control precision, poor stability and low intelligent degree in the prior art are solved, and the technical effect of improving the engineering plastic extrusion quality and efficiency is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of plastic processing, and in particular to an engineering plastic extrusion control system. Background Art

[0002] With the rapid development of modern engineering technology, engineering plastics, as important industrial raw materials, have been widely used in many fields such as automobiles, electronics, and medical treatment. Engineering plastic extrusion technology, as a key link in plastic processing, the performance of its control system directly affects the quality and production efficiency of the product.

[0003] However, traditional engineering plastic extrusion control systems often have problems such as low control accuracy, poor stability, and low intelligence. As a result, during the extrusion process, due to fluctuations in key parameters such as temperature, pressure, and speed, the extruded products may have dimensional deviations and poor surface quality. Summary of the invention

[0004] The present application provides an engineering plastic extrusion control system, which is used to solve the technical problems of low control accuracy, poor stability and low intelligence in the prior art.

[0005] In view of the above problems, the present application provides an engineering plastic extrusion control system.

[0006] In a first aspect of the present application, there is provided an engineering plastic extrusion control system, the system comprising: A basic configuration information and degeneration threshold acquisition unit, the basic configuration information and degeneration threshold acquisition unit acquires the basic configuration information and degeneration threshold of the target engineering plastic, wherein the degeneration threshold includes a threshold multi-group corresponding to each performance index; an optimization control module training unit, the optimization control module training unit uses the degeneration threshold as a first constraint condition, and determines a second constraint condition based on the basic configuration information, combines the basic configuration of the extruder, and supervises the training of the optimization control module, the optimization control module is communicatively connected with the extrusion control system; a first dynamic extrusion scheme determination unit, the first dynamic extrusion scheme determination unit reads the extrusion task, and combines the optimization control module to perform a full cycle of extrusion under the constraint condition Control analysis, determine the dynamic extrusion plan and transmit it to the extrusion control system; a dynamic extrusion plan execution unit, the dynamic extrusion plan execution unit executes the dynamic extrusion plan and determines the feedback control threshold; a feedback control point positioning unit, the feedback control point positioning unit synchronously performs extrusion real-time monitoring, performs extrusion state evaluation on the extrusion channel of the extruder, and evaluates the molding and curing state based on the mold, and locates the feedback control point in combination with the feedback control threshold, wherein the evaluation dimensions include single-point evaluation and global evaluation, and the extrusion channel is equipped with a distributed sensing device; a feedback extrusion control unit, the feedback extrusion control unit performs feedback extrusion control based on the extrusion control system based on the feedback control point.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application obtains the basic configuration information and denaturation threshold of the target engineering plastic, wherein the denaturation threshold includes a threshold multi-group corresponding to each performance index; takes the denaturation threshold as the first constraint condition, and determines the second constraint condition based on the basic configuration information, combines the basic configuration of the extruder, supervises the training of the optimization control module, and the optimization control module is connected to the extrusion control system; reads the extrusion task, combines the optimization control module to perform the full cycle control analysis of the extrusion under the constraint condition, determines the dynamic extrusion scheme and transmits it to the extrusion control system; executes the dynamic extrusion scheme, and determines the feedback control threshold; synchronously performs extrusion real-time monitoring, evaluates the extrusion state of the extruder channel, and evaluates the molding and curing state based on the mold, combines the feedback control threshold, and locates the feedback control point, wherein the evaluation dimension includes single point evaluation and global evaluation, and the extrusion channel is equipped with a distributed sensing device; based on the feedback control point, feedback extrusion control based on the extrusion control system is performed. The present invention solves the technical problems of low control accuracy, poor stability, and low intelligence in the prior art, and realizes precise control and intelligent management by real-time monitoring of key parameters in the extrusion process, so as to achieve the technical effect of improving the quality and efficiency of engineering plastic extrusion. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic diagram of the structure of an engineering plastic extrusion control system provided in an embodiment of the present application; Figure 2 A schematic flow chart of an engineering plastic extrusion control system provided in an embodiment of the present application.

[0010] Explanation of the reference numerals: basic configuration information and variability threshold acquisition unit 11 , optimization control module training unit 12 , first dynamic extrusion scheme determination unit 13 , dynamic extrusion scheme execution unit 14 , feedback control point positioning unit 15 , feedback extrusion control unit 16 . DETAILED DESCRIPTION

[0011] The present application provides an engineering plastic extrusion control system to solve the technical problems of low control accuracy, poor stability and low intelligence in the prior art. By real-time monitoring of key parameters in the extrusion process, precise control and intelligent management are achieved, thereby achieving the technical effect of improving the quality and efficiency of engineering plastic extrusion.

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0013] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0014] Embodiment 1 like Figure 1As shown, the present application provides an engineering plastic extrusion control system for executing Figure 2 A method for controlling extrusion of engineering plastics is shown, the system comprising: A basic configuration information and denaturation threshold acquisition unit 11, wherein the basic configuration information and denaturation threshold acquisition unit 11 acquires basic configuration information and a denaturation threshold of a target engineering plastic, wherein the denaturation threshold includes a threshold multi-tuple corresponding to each performance index; In the embodiment of the present application, for obtaining basic configuration information, the basic configuration information and denaturation threshold acquisition unit accesses a database or related documents of engineering plastics, which contain detailed information about raw material types, additive components, impurity content, etc. The basic configuration information and denaturation threshold acquisition unit extracts data related to the target engineering plastic from these data sources and uses it as part of the basic configuration information.

[0015] In addition, the basic configuration information and denaturation threshold acquisition unit communicate with other related devices or sensors to obtain real-time physical and chemical property data of engineering plastics. For example, by connecting with raw material detection equipment, real-time component analysis data of raw materials can be obtained; by connecting with environmental sensors such as temperature and humidity, relevant information about storage and processing environments can be obtained.

[0016] Through the above process, basic configuration information is obtained.

[0017] Next, for obtaining the denaturation threshold, the basic configuration information and denaturation threshold obtaining unit obtains the denaturation threshold according to expert experience and industry specifications. The denaturation threshold includes threshold ranges for different performance indicators, including threshold ranges for key performance indicators such as melting temperature, viscosity, and fluidity.

[0018] An optimization control module training unit 12, wherein the optimization control module training unit 12 takes the variability threshold as a first constraint condition, determines a second constraint condition based on the basic configuration information, and supervises and trains an optimization control module in combination with the basic configuration of the extruder, wherein the optimization control module is communicatively connected with the extrusion control system; In the embodiment of the present application, the optimization control module training unit first uses the denaturation threshold as the first constraint condition of the training process. The denaturation threshold contains the acceptable range of various performance indicators of engineering plastics, such as tensile strength, elongation, impact strength, etc. These performance indicators must be met during the training process. The optimization control module training unit uses these performance indicator thresholds as constraints to ensure that the trained optimization control module does not exceed the allowable range of these performances when optimizing the extrusion process.

[0019] In addition to the denaturation threshold, the optimization control module training unit determines the second constraint condition based on the basic configuration information. The basic configuration information includes the type of raw materials, the type and proportion of additives, the production process requirements, etc. These factors will affect the optimization of the extrusion process. The optimization control module training unit converts these basic configuration information into specific constraints, such as the melting temperature range of the raw materials, the effect of additives on the extrusion temperature, etc., to ensure that the trained optimization control module is feasible in practical applications.

[0020] Before starting training, the optimization control module training unit collects a large amount of historical extrusion data, including successful and failed extrusion cases, and uses this data to train the optimization control module so that it can learn the optimal extrusion parameters under different configurations and constraints.

[0021] The optimization control module training unit will use machine learning algorithms, such as neural networks and genetic algorithms, to train the optimization control module. During the training process, the optimization control module training unit will continuously adjust the parameters of the module so that it can find the optimal extrusion solution while satisfying the constraints. Cross-validation and model evaluation are performed during the training process to ensure that the trained optimization control module has good generalization ability and robustness.

[0022] Finally, a communication connection is established between the trained optimization control module and the extrusion control system.

[0023] Furthermore, the optimization control module training unit 12 is also used for: Identify the basic configuration information, and obtain plastic raw material characteristics, additive characteristics, and impurity characteristics, wherein the number of additive types and impurity types is greater than or equal to 0; Based on the impurity characteristics, determining a condition threshold standard for impurity precipitation as a constraint condition; Based on the characteristics of the additives and the requirements for modifying the properties of the plastic raw materials, the condition threshold standard for the modification to a worse trend is determined as a binary constraint condition; Based on the characteristics of the plastic raw material, a first implicit relationship is mined, wherein the first implicit relationship is determined based on the melting state trend of the target engineering plastic under a unit parameter control variable; The first constraint condition, the two constraints conditions and the first implicit relationship are combined to determine the second constraint condition.

[0024] In the embodiment of the present application, the characteristics of the plastic raw material, the characteristics of the additives and the characteristics of the possible impurities are first identified and obtained. This information is the basis for formulating the constraint conditions in the subsequent extrusion process.

[0025] The characteristics of plastic raw materials include the melting temperature, viscosity, thermal stability, etc. of the raw materials, which directly affect the temperature setting and screw speed parameters during the extrusion process. Additives include plasticizers, stabilizers, pigments, etc. Each additive has its specific functions and properties, such as changing the processing properties of plastics, improving heat resistance or changing color. Impurities are mixed in during the production or storage of raw materials, and they have an adverse effect on the extrusion process, such as reducing product quality or damaging equipment.

[0026] Carry out detailed characteristic analysis of impurities to obtain their chemical composition, physical state, melting point, boiling point, solubility in plastics and other properties. Use thermal analysis techniques such as differential thermal analysis and thermogravimetric analysis to determine the precipitation of impurities under different temperature, pressure and time conditions. At the same time, use mathematical modeling methods, such as establishing a phase equilibrium model, to predict the conditions for impurity precipitation. Based on data and model predictions, determine the condition threshold standard for impurity precipitation. Condition threshold standards include specific temperature ranges, pressure ranges or processing times. For example, if it is found that a certain impurity begins to precipitate when the temperature exceeds a certain threshold, then use this temperature as an important constraint condition. Finally, set the determined impurity precipitation condition threshold standard as a constraint condition in the extrusion process.

[0027] Collect data on additive concentration, processing conditions, and plastic raw material properties from past production records, databases, and other sources. These data include different types of plastics, different additives, and different processing parameters. Then, clean and organize the data to ensure accuracy and consistency.

[0028] Statistical methods and data analysis tools are used to conduct in-depth analysis of the collected data, calculate statistical quantities such as the performance average and standard deviation under different conditions, and draw trend charts of performance changes with additive concentration and processing conditions. Through these analyses, the influence of additive concentration and processing conditions on the performance of plastic raw materials is identified. For example, it is found that a certain additive can effectively improve the flexibility of plastics within a specific concentration range, while exceeding this range may lead to performance degradation. Based on the performance analysis, the modification deterioration trend caused by the additive is further identified. This includes adverse changes such as a decrease in mechanical properties and a decrease in thermal stability. By analyzing the conditions under which these deterioration trends occur, the additive concentration range and processing temperature range that cause these changes are preliminarily determined.

[0029] Then, combined with more historical data, these initially determined thresholds are verified and optimized. By comparing the threshold results under different data sets, more accurate and reliable conditional threshold standards are obtained. Finally, these verified conditional threshold standards are set as binary constraints in the extrusion process. These conditions will serve as an important basis for controlling and optimizing the properties of plastic raw materials in actual production. For example, the maximum amount of additives is set to a certain value to ensure the stability and reliability of plastic performance; at the same time, the range of processing temperature and pressure is set to avoid adverse effects of excessively high or low temperatures and pressures on plastic performance.

[0030] When mining the first implicit relationship, the first thing to do is to determine the characteristics of the plastic raw materials, including its chemical composition, molecular weight distribution, melt index, crystallinity, etc. These characteristics directly affect the flow behavior, viscosity change, and thermal stability of the plastic in the molten state. Then select the unit control variables, which include temperature, pressure, shear rate, etc., and obtain the property changes of the molten plastic by changing the unit control variables one by one. For example, gradually increase the temperature while recording the changes in parameters such as viscosity and fluidity of the molten plastic. Design a series of control variable analyses to determine the property changes of the molten plastic. Through control variable analysis, the molten state behavior, rheological parameters, etc. under different conditions are obtained.

[0031] Data mining techniques, such as association rule mining and cluster analysis, are used to analyze data. Through data analysis, the implicit relationship between the change in the properties of molten plastics and the unit parameter control variable is identified, and the first implicit relationship is determined. The first implicit relationship refers to the law of changes in a certain property of molten plastics, such as viscosity and fluidity, when the unit parameter control variable changes. For example, as the temperature increases, the viscosity of molten plastics gradually decreases and the fluidity increases.

[0032] The first constraint, the second constraint and the first implicit relationship are jointly analyzed to further determine other key constraints in the preparation process, namely the second constraint. This process includes comprehensive consideration and trade-offs of multiple factors to ensure the stability of the preparation process and product quality. For example, by analyzing the conditions for impurity precipitation and modification deterioration, the range of process parameters that should be avoided in the preparation process is determined. At the same time, combined with the relationship of molten state trend, the process parameters are further optimized to achieve precise control of plastic properties.

[0033] A first dynamic extrusion scheme determining unit 13, which reads the extrusion task, performs full-cycle extrusion control analysis under constraint conditions in combination with the optimization control module, determines a dynamic extrusion scheme and transmits it to the extrusion control system; In the embodiment of the present application, the first dynamic extrusion scheme determination unit receives extrusion tasks. These tasks include key information such as production goals, raw material types, additive requirements, product performance requirements, etc. This information is the basis for formulating extrusion schemes and is crucial to ensuring product quality and the stability of the preparation process.

[0034] Next, the first dynamic extrusion scheme determination unit interacts with the optimization control module. The optimization control module selects the best one from multiple possible extrusion schemes based on the preset constraints and optimization goals. These constraints include the previously mentioned conditional threshold standards for impurity precipitation, conditional threshold standards for modified deterioration trends, and implicit relationships such as molten state trends. Under the constraints, the first dynamic extrusion scheme determination unit performs full-cycle extrusion control analysis, including analysis of multiple aspects such as the mixing of raw materials, the addition of additives, the temperature and pressure control of the extruder, and the extrusion speed. By comprehensively analyzing these factors, the stability of the entire extrusion process and product quality are ensured.

[0035] After analysis, the first dynamic extrusion scheme determination unit determines a dynamic extrusion scheme, which includes specific extrusion parameters, process steps, and operation sequence, etc. Finally, the first dynamic extrusion scheme determination unit transmits the determined dynamic extrusion scheme to the extrusion control system.

[0036] Furthermore, the first dynamic extrusion scheme determining unit 13 is further used for: Read the extrusion control parameters of the extruder, take the extrusion cycle as the main axis and each extrusion control parameter as the slave axis, and build the control coordinate space; Combining the first constraint condition and the second constraint condition, performing boundary constraints on the parameter control coordinate space, and determining the parameter control optimization space; Based on the parameter control optimization space, a dynamic parameter control analysis of the entire extrusion cycle of the target engineering plastic is performed.

[0037] In the embodiment of the present application, first, the extrusion control parameters of the extruder are read. These parameters include but are not limited to temperature, pressure, speed, extrusion volume, etc., which directly affect the stability of the extrusion process and the final quality of the product. With the extrusion cycle as the main axis and each extrusion control parameter as the secondary axis, a parameter control coordinate space is built. This coordinate space provides an intuitive way to understand and analyze the relationship and changes between various parameters in the extrusion process.

[0038] Next, the first and second constraints determined previously are combined to impose boundary constraints on the parameter control coordinate space. These constraints set a safe and effective operating range for the extrusion process based on control variable analysis, material properties, and process requirements. By applying these constraints to the parameter control coordinate space, the parameter control optimization space is determined. This space is the range of parameter combinations that meet all constraints, providing a basis for subsequent optimization analysis.

[0039] Finally, based on the parameter control optimization space, dynamic parameter control is performed for the entire extrusion cycle of the target engineering plastic, that is, how each control parameter is adjusted over time and process steps during the entire extrusion cycle. Through dynamic analysis, the interaction and influence between parameters are determined, and the optimal parameter combination is found to achieve the best extrusion effect and product quality.

[0040] Furthermore, the system is also used for: Reading initial parameter control data based on the extrusion task; Combine the finite element analysis principle to determine the optimization rules; Taking the initial parameter control data as a baseline, an iterative optimization analysis based on the optimization rule is performed until a convergence condition is met, and the dynamic extrusion scheme is determined.

[0041] In the present application embodiment, according to the actual physical conditions of the plastic extrusion process, an accurate finite element model is established. This model can take into account factors such as the physical properties of the material, the geometry of the extruder, boundary conditions, and possible external forces. The model is simulated using finite element analysis software to predict key phenomena such as material flow and stress distribution during extrusion. According to the analysis and simulation results, the key factors and parameters affecting the extrusion effect are identified. The key factors and parameters include the elastic modulus, viscosity, extrusion speed, temperature distribution, etc. of the material. By comparing the simulation results under different parameter combinations, it is determined which parameters have the most significant effect on the extrusion effect. According to the analysis results, a suitable intelligent optimization algorithm is selected, such as a genetic algorithm, a particle swarm optimization algorithm, etc., and the optimal parameter combination is automatically searched according to the objective function, such as extrusion efficiency, product quality, etc. The results of the finite element analysis are used as input, and iterative optimization is performed using the intelligent optimization algorithm to find the optimal extrusion parameters.

[0042] Based on the output of the intelligent optimization algorithm, a set of optimization rules for extrusion tasks is formulated. These rules guide how to adjust the extrusion parameters to optimize the extrusion effect. The rules include qualitative guidelines, such as appropriately reducing the extrusion speed under high viscosity materials, and quantitative parameter adjustment suggestions, such as increasing the flow rate of cooling water when the temperature exceeds a certain value.

[0043] Then, with the initial control data as the baseline, perform iterative optimization analysis based on optimization rules. This step continuously adjusts and optimizes the extrusion parameters to find the best extrusion solution that meets the constraints and optimization goals. In each iteration, the current extrusion parameters are adjusted according to the optimization rules, and the adjusted extrusion effect is evaluated. Through continuous iteration and optimization, the optimal extrusion solution can be gradually approached.

[0044] Finally, when the iterative optimization analysis meets the convergence conditions, the dynamic extrusion solution can be determined. The convergence conditions include reaching the preset accuracy requirements, the number of iterations reaching the upper limit, etc. When these conditions are met, it is considered that the best extrusion solution that meets the requirements has been found.

[0045] Furthermore, the system is also used for: The optimization rules include target random rules and iterative rules; Based on the extrusion control parameter, randomly determining a preset number of pre-adjustment parameters, wherein the preset number is a positive integer greater than or equal to 1, and the pre-adjustment parameters in the preset number are different; Traversing the initial parameter control data, performing parameter control adjustment based on the pre-adjustment parameters based on multiple adjustment methods, and determining N pre-adjustment schemes, wherein the adjustment method is randomly determined based on multiple objectives, multiple directions, and multiple steps; Traversing the N pre-adjustment schemes, screening out the better adjustment schemes of the preset proportion, and adding the adjustment method of the best adjustment scheme into the optimization taboo table; Iterative optimization is performed on the basis of the better adjustment scheme until the convergence condition is met, and the global optimal scheme is selected as the dynamic extrusion scheme.

[0046] In the embodiment of the present application, the optimization rule includes a target random rule and an iteration rule, which work together to achieve accurate optimization of the extrusion parameters.

[0047] When optimizing the extrusion parameters, firstly, a preset number of pre-adjustment parameters are randomly determined based on the extrusion control parameters. This preset number is a positive integer greater than or equal to 1, which represents the number of different parameter adjustment combinations to try. Each pre-adjustment parameter is different, exploring multiple potential optimization points in the parameter space.

[0048] Next, the initial parameter control data is traversed, and the parameter control adjustment based on the pre-adjusted parameters is performed based on the multi-adjustment method. The multi-adjustment method refers to the use of a variety of different adjustment strategies, such as multi-objective, multi-directional, multi-step random determination, etc. In this way, the parameter space is fully explored to find more possible optimization directions. Through this step, N pre-adjustment schemes are determined.

[0049] Then, traverse these N pre-adjustment schemes and select the better adjustment schemes with a preset ratio. The preset ratio is set according to the actual problem and requirements, and is used to control the number of schemes entering the next round of iteration. Through screening, those adjustment schemes with better performance are retained, while those with poor performance are excluded. At the same time, the adjustment method of the optimal adjustment scheme is added to the optimization taboo table. The purpose of the taboo table is to record the adjustment methods that have been tried to avoid repeated attempts in subsequent iterations, thereby improving search efficiency.

[0050] Finally, based on the better adjustment scheme, iterative optimization is performed to gradually approach the optimal solution by continuously adjusting parameters and evaluating the adjusted effects. During the iteration process, the convergence condition is used to determine whether the termination condition has been met. When the convergence condition is met, the global optimal solution is selected as the dynamic extrusion solution.

[0051] Furthermore, the system is also used for: Acquire the distribution structure of the extrusion channel and determine special structural points, wherein the special structural points are marked with structural features; In combination with the structural features, an extrusion retention analysis is performed to determine a molten state that meets the retention standard, wherein the molten state corresponds one-to-one to the special structural points; Based on the melt state, the dynamic extrusion scheme is compensated.

[0052] In the embodiment of the present application, the distribution structure of the extrusion channel is first obtained through relevant technical documents and design drawings. The distribution structure of the extrusion channel includes the geometric shape, size, length, and possible structural features such as bends and branches of the channel.

[0053] Next, identify the special structural points in the extrusion channel. These special structural points are set due to design requirements or process requirements, such as narrow areas, flared areas, variable diameter sections, etc. These areas cause material flow restrictions or retention due to changes in geometry or size restrictions. Identify these special structural points and record their structural features, such as size, angle, curvature, etc.

[0054] Then, combined with the structural characteristics of special structural points, extrusion retention analysis is performed. Retention analysis aims to determine the changes in the melting state of the material caused by special structural points during the extrusion process. Through simulation or data analysis, the flow behavior, temperature distribution and melting state of the material at these special structural points are analyzed. The focus is on the melting state that meets the retention standard, that is, the material reaches a suitable melting degree in these areas, neither too much melting to cause degradation, nor too little melting to cause extrusion difficulties.

[0055] Finally, based on the analysis results of the melting state, the dynamic extrusion scheme is compensated. Compensation measures include adjusting the extruder speed, temperature setting or material supply rate to ensure that the material reaches the ideal melting state at a special structural point.

[0056] A dynamic extrusion scheme execution unit 14, wherein the dynamic extrusion scheme execution unit executes the dynamic extrusion scheme and determines a feedback control threshold; In the embodiment of the present application, first, the dynamic extrusion scheme execution unit receives the dynamic extrusion scheme from the first dynamic extrusion scheme determination unit. This scheme contains information such as extrusion parameters, process steps, and operation sequence that are optimized and constrained. The dynamic extrusion scheme execution unit accurately controls the operation of the extruder based on this information to ensure that the extrusion process is carried out according to the predetermined scheme.

[0057] During the execution of the dynamic extrusion scheme, the dynamic extrusion scheme execution unit closely monitors the various parameters and indicators of the extrusion process. These parameters and indicators include the temperature, pressure, speed, extrusion volume, etc. of the extruder, as well as the performance and quality indicators of the product. The dynamic extrusion scheme execution unit collects and analyzes these data in real time to promptly detect and handle possible abnormal situations.

[0058] In order to ensure the stability of the extrusion process and product quality, the dynamic extrusion scheme execution unit determines the feedback control thresholds. These thresholds are determined based on the actual data of the extrusion process and the preset quality standards. When a parameter or indicator exceeds or falls below the preset threshold, the execution unit will immediately take corresponding control measures, such as adjusting the extruder parameters, changing the process steps, etc., to correct the deviation and restore the stability of the extrusion process.

[0059] By executing the dynamic extrusion scheme and determining the feedback control threshold, the dynamic extrusion scheme execution unit realizes precise control and optimization of the extrusion process.

[0060] A feedback control point positioning unit 15, wherein the feedback control point positioning unit synchronously performs extrusion real-time monitoring, performs extrusion state evaluation on the extrusion channel of the extruder, and evaluates the molding and curing state based on the mold, and locates the feedback control point in combination with the feedback control threshold, wherein the evaluation dimensions include single-point evaluation and global evaluation, and the extrusion channel is equipped with a distributed sensing device; In the embodiment of the present application, first, the feedback control point positioning unit synchronously monitors the extrusion status through the distributed sensor devices installed on the extrusion channel. These sensor devices collect data of key points in the extrusion channel in real time, such as temperature, pressure, flow rate, etc.

[0061] Next, the feedback control point positioning unit evaluates the extrusion state of the extrusion channel. This evaluation is based on the data collected by the distributed sensing device. The evaluation content includes but is not limited to the temperature distribution, pressure change, flow rate stability, etc. of each point in the extrusion channel. For each key point in the extrusion channel, such as the entrance, exit, inflection point, etc., the feedback control point positioning unit will analyze the data of the point separately. For example, for temperature distribution, check whether the temperature of the point is within the preset safety range, and whether there is abnormal temperature rise or temperature drop. For pressure change, analyze whether the pressure is stable, whether there is a sudden pressure fluctuation or drop. For flow rate stability, check whether the flow rate remains constant, and whether the flow rate is too fast or too slow. Based on these analyses, the status of each key point is determined, such as normal, warning, or abnormal. After completing the single-point evaluation, the feedback control point positioning unit will perform a global evaluation to understand the overall status of the entire extrusion channel. This usually involves a comprehensive analysis of the single-point evaluation results, such as counting the number, location, and type of abnormal points, and judging whether there are global problems or trends.

[0062] Through single-point evaluation, the status of each key point is determined; through global evaluation, the overall status of the entire extrusion channel is determined.

[0063] At the same time, the feedback control point positioning unit evaluates the molding and curing state based on the mold. The mold is another key link in the preparation process of plastic materials, which determines the final shape and quality of the product. By evaluating the temperature distribution, curing speed, molding accuracy, etc. of the mold, it is judged whether the molding and curing state of the product is good, and whether there are defects or undesirable phenomena.

[0064] When evaluating the temperature distribution, the temperature data of each area of ​​the mold is collected in real time through the temperature sensor network built into the mold. The collected temperature data is converted into a visual temperature distribution diagram using data analysis software, so that the temperature distribution inside the mold can be observed intuitively. According to the preset temperature range, it is determined whether the temperature of each area of ​​the mold is within the normal range. If the temperature of a certain area is too high or too low, it indicates that there is a problem with the heating or cooling system of the mold and it needs to be adjusted.

[0065] When evaluating the curing speed, the time from the injection of the plastic material into the mold to its complete curing is recorded through the timer and sensor built into the mold. The actual curing speed is compared with the preset curing speed standard to analyze whether it meets the standard. If the curing speed is too slow, the production efficiency will be low; if the curing speed is too fast, the curing quality and strength of the product will be affected.

[0066] When evaluating molding accuracy, use high-precision measuring tools, such as three-dimensional coordinate measuring machines, optical projectors, etc. to measure the dimensions of the molded plastic products. Compare the measurement results with the dimensional requirements in the product design drawings and calculate the deviation value. Analyze the causes of the deviation, such as mold wear, inaccurate positioning, etc.

[0067] After completing the above evaluation, the feedback control point positioning unit will locate the feedback control point in combination with the preset feedback control threshold. The feedback control threshold is set according to the process requirements and product quality standards, and it represents the normal range and allowable fluctuation range of each parameter in the extrusion process. When the evaluation result exceeds or falls below a certain threshold, it means that feedback control is required, and this point is used as the feedback control point.

[0068] Furthermore, the system is also used for: The extrusion state evaluation dimension includes radial trend stability and tangential uniformity based on the extrusion channel, and the evaluation characteristics include at least temperature, extrusion speed and extrusion pressure.

[0069] In the embodiments of the present application, radial trend stability refers to the flow stability of the material in the extrusion channel in the radial direction during the extrusion process. This involves the uniformity of the distribution of the material on the channel cross section and whether there are obvious flow rate differences or fluctuations. If the radial trend stability is poor, it may cause uneven flow of the material during extrusion, thereby affecting the quality and performance of the product.

[0070] Secondly, tangential uniformity refers to the uniformity of the material flow along the tangential direction in the extrusion channel. This is related to the continuity and stability of the material during the extrusion process. If the tangential flow is uneven, it may cause defects in the extruded product, such as bubbles, breakage, etc.

[0071] Temperature is a key parameter in evaluating characteristics. Temperature affects the melting state, flow properties and extrusion effect of the material. Therefore, it is necessary to monitor the temperature distribution in the extrusion channel in real time and adjust it as needed to ensure that the material is extruded at a suitable temperature.

[0072] Extrusion speed is also an important indicator for evaluating the extrusion state. Extrusion speed that is too fast or too slow may affect product quality and production efficiency. Therefore, it is necessary to reasonably set and adjust the extrusion speed according to the properties of the material and the requirements of the product.

[0073] In addition, extrusion pressure is also an important factor in evaluating the extrusion state. The size of the extrusion pressure directly affects the fluidity and extrusion effect of the material. Appropriate extrusion pressure can make the material flow stably in the extrusion channel, thereby obtaining high-quality extruded products.

[0074] Furthermore, the system is also used for: The molding and curing state evaluation dimensions include surface quality and mechanical properties, and the curing characteristics include at least crystallinity, shrinkage and stress concentration deformation.

[0075] In the embodiments of the present application, surface quality is one of the important dimensions for evaluating the molding and curing state. It is directly related to the appearance and practicality of the product. High-quality surface quality should be flat, smooth, flawless, and uniform in color. During the evaluation process, the surface condition of the product is observed to check for defects such as bubbles, cracks, scratches, etc., and quantitative analysis is performed.

[0076] Mechanical properties are another important evaluation dimension. It involves key indicators such as product strength, toughness, and hardness, which directly determine the product's performance and safety. When evaluating mechanical properties, the mechanical parameters of the product are measured through tensile tests, bending tests, impact tests, etc., and compared with preset standards to determine whether it meets the requirements.

[0077] In terms of curing characteristics, crystallinity is an important parameter. It reflects the degree of crystallization of plastic materials during the curing process and has an important impact on the physical properties and chemical stability of the product. By measuring the crystallinity, we can understand the changes in the microstructure of the material and then predict its macroscopic performance.

[0078] In addition, shrinkage is one of the characteristics that need to be paid attention to during the curing process. The size of the shrinkage directly affects the dimensional accuracy and shape stability of the product. If the shrinkage is too large, it will cause the product to deform or crack; while if the shrinkage is too small, it will affect the filling and density of the product. Therefore, the shrinkage needs to be accurately measured and controlled.

[0079] Finally, stress concentration deformation is also a curing feature that needs to be paid attention to when evaluating the curing state of molding. Stress concentration deformation is caused by uneven stress on the material during the curing process. This deformation causes problems such as local warping, distortion or cracking of the product, which seriously affects the quality and appearance of the product. Therefore, special attention should be paid to stress concentration deformation during the evaluation process, and effective measures should be taken to prevent and control it.

[0080] A feedback extrusion control unit 16 performs feedback extrusion control based on the extrusion control system based on the feedback control point.

[0081] In the embodiment of the present application, the feedback extrusion control unit first obtains detailed feedback control point data from the feedback control point positioning unit. These data include not only the parameter values ​​exceeding the threshold, but also the change trend and fluctuation range of these parameter values ​​over time.

[0082] Next, the feedback extrusion control unit will analyze the data in depth and formulate specific control strategies based on the current extrusion control system status, raw material properties, product requirements and other factors. For example, if the temperature in a certain area is too high, it will decide to reduce the heating power of the area or increase cooling measures; if the flow rate is unstable, adjust the speed of the extruder.

[0083] After determining the control strategy, the feedback extrusion control unit generates specific control instructions and sends these instructions to the corresponding actuators through the communication interface with the extrusion control system. The actuators include motor drivers, temperature controllers, valves, etc., which adjust the operating parameters of the extruder according to the received instructions.

[0084] After the control command is sent, the feedback extrusion control unit does not stop working immediately, but collects data from sensors, quality inspection equipment, etc., continuously monitors the operating status and product quality of the extruder, and compares them with the expected control target to evaluate the control effect.

[0085] If the control effect is not satisfactory, that is, the expected improvement is not achieved or there are still problems, the feedback extrusion control unit will re-analyze the data, adjust the control strategy, and send new control instructions again. This process will be repeated many times until a satisfactory control effect is achieved.

[0086] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects: The present application obtains the basic configuration information and denaturation threshold of the target engineering plastic, wherein the denaturation threshold includes a threshold multi-group corresponding to each performance index; takes the denaturation threshold as the first constraint condition, and determines the second constraint condition based on the basic configuration information, combines the basic configuration of the extruder, supervises the training of the optimization control module, and the optimization control module is connected to the extrusion control system; reads the extrusion task, combines the optimization control module to perform the full cycle control analysis of the extrusion under the constraint condition, determines the dynamic extrusion scheme and transmits it to the extrusion control system; executes the dynamic extrusion scheme, and determines the feedback control threshold; synchronously performs extrusion real-time monitoring, evaluates the extrusion state of the extruder channel, and evaluates the molding and curing state based on the mold, combines the feedback control threshold, and locates the feedback control point, wherein the evaluation dimension includes single point evaluation and global evaluation, and the extrusion channel is equipped with a distributed sensing device; based on the feedback control point, feedback extrusion control based on the extrusion control system is performed. The present invention solves the technical problems of low control accuracy, poor stability, and low intelligence in the prior art, and realizes precise control and intelligent management by real-time monitoring of key parameters in the extrusion process, so as to achieve the technical effect of improving the quality and efficiency of engineering plastic extrusion.

[0087] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. Other embodiments are within the scope of the attached claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0089] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An engineering plastic extrusion control system, characterized in that: The system comprises: A basic configuration information and denaturation threshold acquisition unit, wherein the basic configuration information and denaturation threshold acquisition unit acquires basic configuration information and a denaturation threshold of a target engineering plastic, wherein the denaturation threshold includes a threshold multi-group corresponding to each performance index; An optimization control module training unit, wherein the optimization control module training unit uses the variability threshold as a first constraint condition, determines a second constraint condition based on the basic configuration information, and supervises the training of an optimization control module in combination with the basic configuration of the extruder, wherein the optimization control module is communicatively connected with the extrusion control system; a first dynamic extrusion scheme determination unit, which reads the extrusion task, performs full-cycle extrusion control analysis under constraint conditions in combination with the optimization control module, determines a dynamic extrusion scheme and transmits it to the extrusion control system; A dynamic extrusion scheme execution unit, wherein the dynamic extrusion scheme execution unit executes the dynamic extrusion scheme and determines a feedback control threshold; A feedback control point positioning unit, wherein the feedback control point positioning unit synchronously performs extrusion real-time monitoring, performs extrusion state evaluation on the extrusion channel of the extruder, and evaluates the molding and curing state based on the mold, and locates the feedback control point in combination with the feedback control threshold, wherein the evaluation dimensions include single-point evaluation and global evaluation, and the extrusion channel is equipped with a distributed sensing device; A feedback extrusion control unit is configured to perform feedback extrusion control based on the extrusion control system based on the feedback control point.

2. The system according to claim 1, characterized in that The determining of a second constraint condition based on the basic configuration information includes: Identify the basic configuration information, and obtain plastic raw material characteristics, additive characteristics, and impurity characteristics, wherein the number of additive types and impurity types is greater than or equal to 0; Based on the impurity characteristics, determining a condition threshold standard for impurity precipitation as a constraint condition; Based on the characteristics of the additives and the requirements for modifying the properties of the plastic raw materials, the condition threshold standard for the modification to a worse trend is determined as a binary constraint condition; Based on the characteristics of the plastic raw material, a first implicit relationship is mined, wherein the first implicit relationship is determined based on the melting state trend of the target engineering plastic under a unit parameter control variable; The first constraint condition, the two constraints conditions and the first implicit relationship are combined to determine the second constraint condition.

3. The system according to claim 1, characterized in that Combined with the optimization control module, the full cycle control analysis of extrusion under constraint conditions is carried out, including: Read the extrusion control parameters of the extruder, take the extrusion cycle as the main axis and each extrusion control parameter as the slave axis, and build the control coordinate space; Combining the first constraint condition and the second constraint condition, performing boundary constraints on the parameter control coordinate space, and determining the parameter control optimization space; Based on the parameter control optimization space, a dynamic parameter control analysis of the entire extrusion cycle of the target engineering plastic is performed.

4. The system according to claim 3, characterized in that The dynamic parameter control analysis of the entire extrusion cycle of the target engineering plastic includes: Reading initial parameter control data based on the extrusion task; Combine the finite element analysis principle to determine the optimization rules; Taking the initial parameter control data as a baseline, an iterative optimization analysis based on the optimization rule is performed until a convergence condition is met, and the dynamic extrusion scheme is determined.

5. The system according to claim 4, characterized in that The optimization rules include target random rules and iterative rules; Based on the extrusion control parameter, randomly determining a preset number of pre-adjustment parameters, wherein the preset number is a positive integer greater than or equal to 1, and the pre-adjustment parameters in the preset number are different; Traversing the initial parameter control data, performing parameter control adjustment based on the pre-adjustment parameters based on multiple adjustment methods, and determining N pre-adjustment schemes, wherein the adjustment method is randomly determined based on multiple objectives, multiple directions, and multiple steps; Traversing the N pre-adjustment schemes, screening out the better adjustment schemes of the preset proportion, and adding the adjustment method of the best adjustment scheme into the optimization taboo table; Iterative optimization is performed on the basis of the better adjustment scheme until the convergence condition is met, and the global optimal scheme is selected as the dynamic extrusion scheme.

6. The system according to claim 1, characterized in that After determining the dynamic extrusion solution, it includes: Acquire the distribution structure of the extrusion channel and determine special structural points, wherein the special structural points are marked with structural features; In combination with the structural features, an extrusion retention analysis is performed to determine a molten state that meets the retention standard, wherein the molten state corresponds one-to-one to the special structural points; Based on the melt state, the dynamic extrusion scheme is compensated.

7. The system according to claim 1, characterized in that The extrusion state evaluation dimension includes radial trend stability and tangential uniformity based on the extrusion channel, and the evaluation characteristics include at least temperature, extrusion speed and extrusion pressure.

8. The system of claim 1, wherein: The molding and curing state evaluation dimensions include surface quality and mechanical properties, and the curing characteristics include at least crystallinity, shrinkage and stress concentration deformation.

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