Self-adaptive control method and system for extrusion screw of plastic extruder

Abstract

The invention provides a self-adaptive control method and system for an extrusion screw of a plastic extruder, and relates to the technical field of plastic recovery and regeneration, and the method comprises the following steps: collecting operation data of the plastic extruder; calculating a change trend and an effective value according to the machine head melt pressure; a three-level partition model is constructed, a pressure deviation value is calculated based on the effective value and the target reference value, and a pressure control area is generated according to a comparison result of the pressure deviation value and a pressure threshold value; performing consistency judgment on the change trend and the pressure demand direction to generate an adjustment coefficient, and performing step length correction by combining a pressure control region and a motor load current to generate a rotating speed adjustment amount; the to-be-executed rotating speed of the screw is calculated in combination with the real-time rotating speed of the screw, acceleration limiting processing is carried out to generate the target rotating speed of the screw, and the target rotating speed is coded into a control instruction to be sent to the driving unit, so that the self-adaptive control effect of the extrusion screw can be achieved, and false pressure fluctuation caused by material hardness change is effectively prevented; the extrusion stability and the response speed are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of plastic recycling technology, and more particularly to an adaptive control method and system for extrusion screws in plastic extruders. Background Technology

[0002] Plastic extruders are the core equipment for granulating waste plastics. Their operational stability directly determines the quality and yield of recycled pellets, which is of great significance for promoting the large-scale and high-quality development of the plastic recycling industry.

[0003] Existing extrusion screw control technologies typically employ open-loop constant speed settings or PID closed-loop feedback modes based on a single pressure sensor. However, due to the extremely complex sources of waste plastics, encompassing physical properties such as melt flow index, bulk density, moisture content, and impurity content, significant non-uniformity and random fluctuations exist during the production process. The single control logic of existing technologies lacks deep perception of the material's rheological state, failing to effectively distinguish between pressure anomalies caused by "feed rate fluctuations" and "sudden changes in material viscosity." This leads to frequent lags in adjustment response, misinterpretation of control commands, or system oscillations when facing batch variations in recycled materials. Furthermore, existing technologies neglect the non-linear impact of screw speed increases on melt shear heat, easily causing overheating and degradation of recycled materials due to excessive shearing during the pursuit of pressure stability, resulting in poor dimensional uniformity and decreased physical properties of the final product. In addition, existing technologies heavily rely on real-time human intervention during the production process, making it difficult to meet the high-stability, automated closed-loop control requirements of modern recycling plants.

[0004] Therefore, it is necessary to provide an adaptive control method and system for the extrusion screw of a plastic extruder to solve the above-mentioned technical problems. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides an adaptive control method and system for extrusion screws in plastic extruders, which solves the problems of single adjustment strategy, lag response, system oscillation, and unstable product quality in existing extrusion screw control technologies.

[0006] The present invention provides an adaptive control method for an extrusion screw in a plastic extruder, the method comprising: The operation data of the plastic extruder is collected and updated to a data buffer pool based on a time sliding window. The operation data of the plastic extruder includes at least the die head melt pressure data, screw motor load current data, and screw real-time speed data. Based on the melt pressure data of the die head in the data buffer pool, calculate the pressure change trend and the effective pressure value; A three-level zoning evaluation model is constructed. The pressure deviation is calculated based on the effective pressure value and the preset target pressure benchmark value. Based on the comparison results of the pressure deviation with different preset pressure thresholds, a pressure control zone is generated. The consistency between the pressure change trend and the pressure adjustment demand direction of the pressure control area is judged to generate a dynamic adjustment coefficient. The step size is calculated and corrected by combining the pressure control area and the screw motor load current data to generate the target speed adjustment amount. Based on the real-time screw speed data and the target speed adjustment amount, the target screw speed to be executed is calculated, the target screw speed to be executed is subjected to acceleration limiting processing, the target screw speed is generated, and the target screw speed is encoded into a screw speed control command and sent to the screw drive unit.

[0007] Preferably, the step of calculating the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool specifically includes: The data buffer pool is a FIFO queue with a preset capacity of N, which synchronously collects the operating data of the plastic extruder and updates the FIFO queue at a preset sampling frequency f. The pressure change trend of the head melt pressure data in the FIFO queue was calculated using a linear regression algorithm. The corresponding calculation formula is as follows: In the formula, n represents the number of sets of melt pressure data at the die head. ; This represents the timestamp for the acquisition of the i-th set of melt pressure data from the die head; This represents the melt pressure data of the i-th group of the die head; Calculate the effective pressure value of the head melt pressure data in the FIFO queue. .

[0008] Preferably, the construction of the three-level zoning evaluation model, which calculates the pressure deviation based on the effective pressure value and the preset target pressure benchmark value, and generates pressure control zones based on the comparison results of the pressure deviation with different preset pressure thresholds, specifically includes: The pressure deviation is calculated based on the absolute difference between the effective pressure value and the target pressure reference value. The pressure deviation is compared with a preset first pressure threshold and a second pressure threshold, wherein the first pressure threshold is less than the second pressure threshold; If the pressure deviation is less than the first pressure threshold, then the generated pressure control region is determined to be a stable dead zone. If the pressure deviation is between the first pressure threshold and the second pressure threshold, then the generated pressure control area is determined to be a fine-tuning area. If the pressure deviation is greater than the second pressure threshold, the generated pressure control area is determined to be an emphasis area.

[0009] Preferably, the step of determining the consistency between the pressure change trend and the pressure adjustment demand direction of the pressure control area, and generating a dynamic adjustment coefficient, specifically includes: Based on the effective pressure value Compared with the target pressure reference value The difference relationship is used to generate the pressure regulation demand direction coefficient of the pressure control area. ,in, Represents a symbolic function; This indicates the need for pressure regulation; This indicates a need for stress reduction and adjustment; This indicates that there is no need for pressure adjustment. Based on the aforementioned pressure change trend Calculate the pressure change direction coefficient ,in, This indicates an upward trend in pressure; This indicates a downward trend in pressure; This indicates that the pressure shows no trend of change; like or If the pressure state is stable, the dynamic adjustment coefficient is generated. ,in, This indicates the preset threshold for a stable pressure change trend; like and If the trend of pressure change is determined to be consistent with the direction of pressure regulation demand, the dynamic regulation coefficient is generated. ,in, Indicates the suppression weight coefficient; This indicates the preset maximum pressure change trend threshold; like and If the trend of pressure change is determined to be opposite to the direction of pressure regulation demand, the dynamic regulation coefficient is generated. ,in, This represents the weighting coefficient.

[0010] Preferably, the step-size calculation and correction based on the pressure control region and the screw motor load current data to generate the target speed adjustment specifically includes: If the pressure control region is a stable dead zone, then the screw speed adjustment base step size is... If the pressure control region is a fine-tuning region, then the preset fine-tuning step size parameter is invoked. As the basic step size for adjusting the screw speed If the pressure control region is an emphasis region, then the preset emphasis step size parameter is invoked. As the basic step size for adjusting the screw speed ; The screw speed adjustment step size is determined by the dynamic adjustment coefficient K. Make corrections and generate screw speed adjustment correction step sizes. ; The screw motor load current volatility was calculated using a sliding window relative volatility algorithm. ,in, This represents the standard deviation of the screw motor load current data; This represents the average value of the screw motor load current data; If the load current fluctuation rate of the screw motor is greater than the preset load fluctuation threshold, it is determined that the screw motor load state has changed abruptly. The screw speed adjustment correction step size is attenuated by the resistance compensation factor to generate the target speed adjustment amount; otherwise, it is determined that the screw motor load state is stable, and the screw speed adjustment correction step size is the target speed adjustment amount.

[0011] Preferably, if the load current fluctuation rate of the screw motor is greater than a preset load fluctuation threshold, a sudden change in the load state of the screw motor is determined. The screw speed adjustment correction step size is then attenuated using a resistance compensation factor to generate the target speed adjustment amount. Specifically, this includes: Based on the screw motor load current fluctuation rate CV and the preset load fluctuation threshold The drag compensation factor is calculated using an exponential decay model. , ,in, Indicates the attenuation sensitivity coefficient; Through the resistance compensation factor Adjust the screw speed correction step size The target speed adjustment amount is generated by proportional attenuation. .

[0012] Preferably, the step of calculating the target screw speed based on the real-time screw speed data and the target speed adjustment amount, and performing acceleration limiting processing on the target screw speed to generate the target screw speed specifically includes: Based on the pressure regulation demand direction coefficient The direction of speed adjustment is determined by the real-time speed data of the screw. and the target speed adjustment amount Calculate the target rotational speed of the screw. ; Based on the real-time screw speed data and the target rotational speed of the screw to be executed Calculate the theoretical acceleration of the screw Where T represents the preset control cycle; The theoretical acceleration of the screw With the maximum allowable acceleration of the screw The target rotational speed of the screw is generated by comparison. The comparison process is as follows: like The target rotational speed of the screw is then ; like The target rotational speed of the screw is then .

[0013] An adaptive control system for an extrusion screw in a plastic extruder, the system comprising: The data acquisition module is used to collect the operating data of the plastic extruder and update it to the data buffer pool based on a time sliding window. The operating data of the plastic extruder includes at least the die head melt pressure data, screw motor load current data, and screw real-time speed data. The pressure calculation module is used to calculate the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool; The pressure zoning module is used to construct a three-level zoning evaluation model. It calculates the pressure deviation based on the effective pressure value and the preset target pressure benchmark value, and generates pressure control zones based on the comparison results of the pressure deviation with different preset pressure thresholds. The speed adjustment module is used to make a consistency judgment on the pressure change trend and the pressure adjustment demand direction of the pressure control area, generate a dynamic adjustment coefficient, and perform step size calculation and correction in combination with the pressure control area and screw motor load current data to generate the target speed adjustment amount. The instruction output module is used to calculate the target speed of the screw based on the real-time speed data of the screw and the target speed adjustment amount, perform acceleration limiting processing on the target speed of the screw, generate the target speed of the screw, and encode the target speed of the screw into a screw speed control instruction and send it to the screw drive unit.

[0014] An electronic device includes a memory and a processor, the memory storing a computer program, wherein when the processor runs the computer program stored in the memory, the processor performs the steps of the adaptive control method for an extrusion screw for a plastic extruder as described in any of the preceding claims.

[0015] A readable storage medium storing a computer program, which, when executed by a processor, is used to implement the steps of the adaptive control method for an extrusion screw for a plastic extruder as described in any of the preceding claims.

[0016] Compared with related technologies, the adaptive control method and system for extrusion screws in plastic extruders provided by this invention have the following advantages: This invention collects operating data from a plastic extruder and updates it to a data buffer pool based on a time-sliding window. The operating data includes at least die head melt pressure data, screw motor load current data, and real-time screw speed data. Based on the die head melt pressure data in the data buffer pool, the pressure change trend and effective pressure value are calculated. A three-level zoning evaluation model is constructed. Based on the effective pressure value and a preset target pressure benchmark value, the pressure deviation is calculated. Based on the comparison results of the pressure deviation with different preset pressure thresholds, a pressure control zone is generated. Consistency judgment is made between the pressure change trend and the pressure adjustment demand direction of the pressure control zone, generating a dynamic adjustment coefficient. Step size calculation and correction are performed using the pressure control zone and screw motor load current data to generate the target speed adjustment amount. Based on the real-time screw speed data and the target speed adjustment amount, the target screw speed to be executed is calculated. Acceleration limitation processing is applied to the target screw speed to be executed, generating the target screw speed. The target screw speed is encoded into a screw speed control command and sent to the screw drive unit. This achieves adaptive control of the extrusion screw, effectively preventing false pressure fluctuations caused by changes in material hardness, and significantly improving extrusion stability and response speed.

[0017] This invention constructs a data buffer pool based on a time-sliding window, simultaneously collecting multi-dimensional operational data such as melt pressure at the die head, screw motor load current, and real-time screw speed. It combines linear regression and arithmetic mean algorithms to calculate pressure change trends and effective pressure values, effectively filtering out data fluctuation interference and solving the problem of insufficient depth perception in existing single-data acquisition technologies. This invention designs a three-level partitioned evaluation model, dividing the pressure deviation into a stable dead zone, a fine-tuning zone, and an emphasis zone based on the comparison results between the pressure deviation and a preset pressure threshold. This achieves differentiated control characterized by "rapid convergence of large deviations, fine-tuning of small deviations, and no intervention in stable states," completely overcoming the limitations of traditional fixed-step adjustment strategies, significantly improving the accuracy and targeting of pressure regulation, and avoiding lag or over-adjustment. This invention generates a dynamic adjustment coefficient by judging the consistency between the pressure change trend and the direction of pressure regulation demand. When the directions are consistent, the adjustment amplitude is reduced to prevent overshoot; when the directions are opposite, the adjustment intensity is increased to reverse the trend, effectively suppressing system oscillations and ensuring the stability of the control process. This invention introduces screw motor load current fluctuation analysis and uses a resistance compensation factor to attenuate and correct the screw speed adjustment step size. This accurately distinguishes between pressure fluctuations caused by sudden changes in material properties and improper speed, avoiding excessive shearing and overheating degradation of materials due to misadjustment, and significantly improving the physical properties and size uniformity of recycled granules. Furthermore, this invention rationally controls the screw speed adjustment rate through acceleration limiting, preventing mechanical shocks to the equipment caused by sudden speed changes, and ensuring the safe operation and service life of the plastic extruder. Attached Figure Description

[0018] Figure 1 A flowchart of an adaptive control method for an extrusion screw in a plastic extruder, provided in an embodiment of the present invention; Figure 2 A system block diagram of an adaptive control system for an extrusion screw in a plastic extruder, provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] like Figure 1 The diagram shown is a flowchart of an adaptive control method for an extrusion screw in a plastic extruder, provided by an embodiment of the present invention. Figure 1 The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. User equipment can include, but is not limited to, computers, smartphones, personal digital assistants (PDAs), and the aforementioned electronic devices. Network equipment can include, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Cloud computing is a type of distributed computing, consisting of a super virtual computer composed of a group of loosely coupled computers. This embodiment does not limit this. Steps S1 to S5 are detailed as follows: S1. Collect the operating data of the plastic extruder and update it to the data buffer pool based on the time sliding window. The operating data of the plastic extruder includes at least the die head melt pressure data, screw motor load current data and screw real-time speed data. The time sliding window is a preset duration for continuous data acquisition. The data buffer pool uses a FIFO (First-In, First-Out) queue structure to cache continuously acquired data from the plastic extruder and filter out fluctuations. The die-head melt pressure data is the real-time pressure parameter of the melt at the die head of the plastic extruder, directly reflecting the stability of the extrusion operation. The screw motor load current data characterizes the motor drive load and indirectly reflects changes in physical properties such as material viscosity. The real-time screw speed data is the current operating rate parameter of the screw.

[0021] Understandably, collecting the above three types of data simultaneously and updating them in real time to the data buffer pool based on a time-sliding window ensures the continuity and relevance of the data.

[0022] S2, calculate the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool; The step of calculating the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool specifically includes: The data buffer pool is a FIFO queue with a preset capacity of N, which synchronously collects the operating data of the plastic extruder and updates the FIFO queue at a preset sampling frequency f. The pressure change trend of the head melt pressure data in the FIFO queue was calculated using a linear regression algorithm. The corresponding calculation formula is as follows: In the formula, n represents the number of sets of melt pressure data at the die head. ; This represents the timestamp for the acquisition of the i-th set of melt pressure data from the die head; This represents the melt pressure data of the i-th group of the die head; Calculate the effective pressure value of the head melt pressure data in the FIFO queue. .

[0023] The preset capacity N limits the maximum number of cached data sets, ensuring that only the most recently collected continuous data is retained and expired data is discarded to guarantee the timeliness of the analysis. The preset sampling frequency f is a fixed data acquisition interval used to achieve synchronous acquisition of three types of data: melt pressure at the die head, screw motor load current, and real-time screw speed, ensuring the temporal correlation of multi-dimensional data.

[0024] The linear regression algorithm accurately extracts the rate of pressure change over time, i.e., the pressure change trend, by fitting the linear relationship between the die melt pressure data in the queue and the corresponding collection timestamp. The arithmetic mean algorithm calculates the mean of multiple sets of die melt pressure data in the FIFO queue, smoothing out the errors caused by instantaneous data fluctuations, and obtaining an effective pressure value that truly reflects the current extrusion conditions.

[0025] By leveraging the caching characteristics and synchronous acquisition mechanism of the FIFO queue, the continuity and timeliness of the melt pressure data at the extrusion head are ensured. The linear regression algorithm accurately captures the pressure variation over time, while the arithmetic mean algorithm effectively smooths out instantaneous data fluctuations, yielding an effective pressure value that truly reflects the extrusion conditions. The synergy of these two algorithms and the data structure enables noise reduction of the raw data and extraction of key parameters.

[0026] S3, construct a three-level zoning evaluation model, calculate the pressure deviation based on the effective pressure value and the preset target pressure benchmark value, and generate a pressure control zone based on the comparison results of the pressure deviation with different preset pressure thresholds; The construction of a three-level zoning evaluation model involves calculating the pressure deviation based on the effective pressure value and a preset target pressure benchmark value, and generating pressure control zones based on the comparison results of the pressure deviation with different preset pressure thresholds. Specifically, this includes: The pressure deviation is calculated based on the absolute difference between the effective pressure value and the target pressure reference value. The pressure deviation is compared with a preset first pressure threshold and a second pressure threshold, wherein the first pressure threshold is less than the second pressure threshold; If the pressure deviation is less than the first pressure threshold, then the generated pressure control region is determined to be a stable dead zone. If the pressure deviation is between the first pressure threshold and the second pressure threshold, then the generated pressure control area is determined to be a fine-tuning area. If the pressure deviation is greater than the second pressure threshold, the generated pressure control area is determined to be an emphasis area.

[0027] The three-level zoning evaluation model is a model that divides control logic regions based on the degree of pressure deviation, used to match differentiated adjustment strategies. The target pressure benchmark value is a preset ideal pressure standard for the extrusion process, serving as an adjustment reference. The pressure deviation is calculated by the absolute difference between the effective pressure value and the target pressure benchmark value, intuitively reflecting the degree of deviation between the actual pressure and the ideal state.

[0028] The first pressure threshold, also known as the precision threshold, is the critical value that distinguishes between system stability and fine-tuning. The second pressure threshold, also known as the coarse-tuning threshold, is the critical value that distinguishes between fine-tuning and large-scale correction. Together, they form a tiered judgment standard. The stability dead zone is the system state when the pressure deviation is less than the first pressure threshold; at this point, pressure fluctuations are within the allowable range and no adjustment is needed. The fine-tuning zone corresponds to the state where the pressure deviation is between the two thresholds, requiring high-precision, small-scale compensation to correct the deviation. The emphasis zone is the state where the deviation exceeds the second pressure threshold; the system deviates significantly from the target and requires large-scale, rapid correction to quickly return the pressure to the baseline, achieving precise adaptive control under different deviation scenarios.

[0029] In practical applications, a preset target pressure benchmark value can be determined based on the requirements of the waste plastic granulation process. The first pressure threshold is set as the allowable small fluctuation range of the process, and the second pressure threshold is set as the critical fluctuation value for rapid correction. For example, when processing mixed recycled bottle flakes, the target pressure benchmark value is 15 MPa, the first pressure threshold is 0.5 MPa, and the second pressure threshold is 1.5 MPa. If the effective pressure value is 14.7 MPa, and the pressure deviation is 0.3 MPa, which is less than the first pressure threshold, it is determined to be a stable dead zone, and the speed is not adjusted. If the effective pressure value is 13.8 MPa, and the pressure deviation is 1.2 MPa, which is between the two thresholds, it is determined to be a fine-tuning zone, and small-step speed compensation is performed. If the effective pressure value is 12 MPa, and the pressure deviation is 3 MPa, which is greater than the second pressure threshold, it is determined to be an emphasis zone, and the speed is rapidly increased by large steps to quickly return the pressure to the benchmark and adapt to the fluctuations in the physical properties of the recycled material.

[0030] S4, make a consistency judgment on the pressure change trend and the pressure adjustment demand direction of the pressure control area, generate a dynamic adjustment coefficient, and perform step size calculation and correction in combination with the pressure control area and screw motor load current data to generate the target speed adjustment amount; The step of determining the consistency between the pressure change trend and the pressure regulation demand direction of the pressure control area, and generating a dynamic regulation coefficient, specifically includes: Based on the effective pressure value Compared with the target pressure reference value The difference relationship is used to generate the pressure regulation demand direction coefficient of the pressure control area. ,in, Represents a symbolic function; This indicates the need for pressure regulation; This indicates a need for stress reduction and adjustment; This indicates that there is no need for pressure adjustment. Based on the aforementioned pressure change trend Calculate the pressure change direction coefficient ,in, This indicates an upward trend in pressure; This indicates a downward trend in pressure; This indicates that the pressure shows no trend of change; like or If the pressure state is stable, the dynamic adjustment coefficient is generated. ,in, This indicates the preset threshold for a stable pressure change trend; like and If the trend of pressure change is determined to be consistent with the direction of pressure regulation demand, the dynamic regulation coefficient is generated. ,in, Indicates the suppression weight coefficient; This indicates the preset maximum pressure change trend threshold; like and If the trend of pressure change is determined to be opposite to the direction of pressure regulation demand, the dynamic regulation coefficient is generated. ,in, This represents the weighting coefficient.

[0031] The pressure regulation demand direction coefficient is a parameter used to clarify the adjustment direction of the current pressure relative to the target pressure reference value. The sign function is a mathematical function used to determine the positive or negative attribute of the input value; it outputs 1 when the input value is greater than 0, -1 when it is less than 0, and 0 when it is equal to 0. Pressure regulation demand occurs when the effective pressure value is lower than the target pressure reference value, requiring adjustment of the screw speed to increase the melt pressure to approach the target pressure reference value. Pressure reduction regulation demand occurs when the effective pressure value is higher than the target pressure reference value, requiring adjustment of the screw speed to decrease the melt pressure to approach the target pressure reference value. No pressure regulation demand occurs when the deviation between the effective pressure value and the target pressure reference value is within the allowable range, and no screw speed adjustment is needed to maintain process stability.

[0032] The pressure change direction coefficient is a parameter used to specify the exact direction of pressure change trends, corresponding to upward pressure, downward pressure, or no pressure change. The preset pressure change trend stability threshold is a critical value used to determine whether pressure changes are in a smooth state, distinguishing between minor pressure fluctuations and significant changes. It is preset based on equipment operating characteristics and process stability requirements. The dynamic adjustment coefficient is a parameter used to adapt the adjustment level to different pressure states and pressure change trends.

[0033] The suppression weighting coefficient is a weighted parameter used to reduce the adjustment amplitude when the pressure change trend is in the same direction as the pressure adjustment demand. It is preset based on the equipment's adjustment sensitivity and process accuracy requirements to avoid overshoot due to excessive adjustment. The preset maximum pressure change trend threshold is a standard value that limits the upper limit of the pressure change rate, used to quantify the intensity of the pressure change trend. It is preset based on the equipment's mechanical performance and material processing characteristics. The enhancement weighting coefficient is a weighted parameter used to increase the adjustment intensity when the pressure change trend is in the opposite direction to the pressure adjustment demand. It is preset based on the equipment's response capability and process correction requirements to ensure that unfavorable trends can be quickly reversed.

[0034] Understandably, when there is no pressure change trend (i.e., the pressure change trend is 0), the absolute value of the pressure change trend must be less than the preset pressure change trend stabilization threshold. Therefore, it will be included in the judgment category of stable pressure state. At this time, the dynamic adjustment coefficient is fixed at 1 to ensure that the system maintains the current stable control state without additional adjustment. The core of generating the differentiated dynamic adjustment coefficient under different scenarios is to adapt the relationship between pressure changes and adjustment needs, achieve precise matching between adjustment intensity and actual working conditions, and ensure the stability and timely response of the control process.

[0035] The step-size calculation and correction, which combines the pressure control area and the screw motor load current data, to generate the target speed adjustment amount, specifically includes: If the pressure control region is a stable dead zone, then the screw speed adjustment base step size is... If the pressure control region is a fine-tuning region, then the preset fine-tuning step size parameter is invoked. As the basic step size for adjusting the screw speed If the pressure control region is an emphasis region, then the preset emphasis step size parameter is invoked. As the basic step size for adjusting the screw speed ; The screw speed adjustment step size is determined by the dynamic adjustment coefficient K. Make corrections and generate screw speed adjustment correction step sizes. ; The screw motor load current volatility was calculated using a sliding window relative volatility algorithm. ,in, This represents the standard deviation of the screw motor load current data; This represents the average value of the screw motor load current data; If the load current fluctuation rate of the screw motor is greater than the preset load fluctuation threshold, it is determined that the screw motor load state has changed abruptly. The screw speed adjustment correction step size is attenuated by the resistance compensation factor to generate the target speed adjustment amount; otherwise, it is determined that the screw motor load state is stable, and the screw speed adjustment correction step size is the target speed adjustment amount.

[0036] The screw speed adjustment base step size is based on the initial speed adjustment amplitude parameter matched to the pressure control zone. Its value is adapted to different steady dead zones, fine-tuning zones, and emphasis zones to ensure that the adjustment strategy matches the degree of pressure deviation. The preset fine-tuning step size parameter is a small-amplitude speed adjustment parameter preset for the fine-tuning zone, and the preset emphasis step size parameter is a large-amplitude speed adjustment parameter preset for the emphasis zone. Both are preset according to the equipment's adjustment sensitivity and process accuracy requirements.

[0037] The screw speed adjustment correction step size is an intermediate speed adjustment range that initially adapts to the pressure change trend after the basic screw speed adjustment step size is corrected by a dynamic adjustment coefficient. The sliding window relative volatility algorithm is an algorithm that calculates the degree of volatility by analyzing the screw motor load current data within the sliding window. The standard deviation characterizes the dispersion of the screw motor load current data, and the arithmetic mean reflects the average level of the screw motor load current data. The combined result of these two metrics, the screw motor load current volatility, can accurately reflect the stability of the screw motor load.

[0038] The preset load fluctuation threshold is a critical value for determining whether the load is stable. Exceeding this threshold indicates a sudden change in the screw motor load state, representing a sudden change in the physical properties of the material, such as viscosity. If the threshold is not exceeded, the screw motor load state is stable. The resistance compensation factor is a parameter used to attenuate the screw speed adjustment correction step size when the screw motor load changes abruptly, avoiding excessive speed adjustment when material properties change abruptly. The target speed adjustment amount is a precise amplitude value used for screw speed adjustment, ensuring that the screw speed adjustment is adapted to the screw motor load state.

[0039] In practical applications, parameters are preset according to the granulation process requirements of waste plastic film recycling materials, such as a preset fine-tuning step size of 5 r / s, a preset stress step size of 15 r / s, and a preset load fluctuation threshold of 0.15. If the pressure control zone is determined to be the fine-tuning zone, and the dynamic adjustment coefficient is calculated to be 0.8, then the screw speed adjustment correction step size is 4 r / s. The screw motor load current fluctuation rate is calculated to be 0.12 using the sliding window relative fluctuation rate algorithm, which is less than the preset load fluctuation threshold, indicating that the load state is stable. This screw speed adjustment correction step size is the target speed adjustment amount. If the screw motor load current fluctuation rate suddenly changes to 0.2, which is greater than the preset load fluctuation threshold, it is determined that the material viscosity has changed abruptly.

[0040] If the load current fluctuation rate of the screw motor is greater than a preset load fluctuation threshold, a sudden change in the load state of the screw motor is determined. The screw speed adjustment correction step size is then attenuated using a resistance compensation factor to generate the target speed adjustment amount, specifically including: Based on the screw motor load current fluctuation rate CV and the preset load fluctuation threshold The drag compensation factor is calculated using an exponential decay model. , ,in, Indicates the attenuation sensitivity coefficient; Through the resistance compensation factor Adjust the screw speed correction step size The target speed adjustment amount is generated by proportional attenuation. .

[0041] The exponential decay model is a mathematical model adapted to load fluctuation characteristics. Its advantage lies in its ability to dynamically adjust the decay intensity based on the difference between the screw motor load current fluctuation rate and the preset load fluctuation threshold. The larger the difference, the more significant the decay, rather than using a fixed proportion decay. This achieves precise matching between the step decay and the degree of load abrupt change, avoiding the problem that a single decay logic cannot adapt to the fluctuations in material characteristics of different intensities. The resistance compensation factor is used to weaken the speed regulation amplitude when the screw motor load state changes abruptly, preventing excessive speed regulation due to sudden changes in the physical properties of materials such as viscosity, which could lead to a sudden increase in melt shear heat and cause overheating and degradation of recycled materials, thus ensuring the smoothness of the speed regulation process. The decay sensitivity coefficient is a parameter for adjusting the decay rate. Different values ​​are preset according to the physical properties of different recycled materials, enabling the system to adapt to diverse material processing scenarios and improving the control versatility and flexibility.

[0042] By employing the above method and utilizing an exponential decay model, the resistance compensation factor is dynamically adapted to the degree of sudden load changes in the screw motor. The larger the fluctuation difference, the more significant the decay effect, ensuring that the step decay accurately matches the actual working conditions. The proportional decay of the resistance compensation factor in the screw speed adjustment correction step effectively weakens the speed adjustment intensity during sudden load changes in the screw motor, avoiding excessive speed adjustment caused by sudden changes in the physical properties of materials such as viscosity, and preventing overheating and degradation of recycled materials due to a sudden increase in shear heat. At the same time, the decay sensitivity coefficient flexibly adapts to the processing requirements of different recycled materials, ensuring the stability of system operation under sudden load changes in the screw motor.

[0043] S5. Calculate the target speed of the screw based on the real-time screw speed data and the target speed adjustment amount, perform acceleration limiting processing on the target speed of the screw, generate the target screw speed, and encode the target screw speed into a screw speed control command and send it to the screw drive unit.

[0044] The process of calculating the target screw speed based on the real-time screw speed data and the target speed adjustment amount, and then applying acceleration limiting processing to the target screw speed to generate the target screw speed, specifically includes: Based on the pressure regulation demand direction coefficient The direction of speed adjustment is determined by the real-time speed data of the screw. and the target speed adjustment amount Calculate the target rotational speed of the screw. ; Based on the real-time screw speed data and the target rotational speed of the screw to be executed Calculate the theoretical acceleration of the screw Where T represents the preset control cycle; The theoretical acceleration of the screw With the maximum allowable acceleration of the screw The target rotational speed of the screw is generated by comparison. The comparison process is as follows: like The target rotational speed of the screw is then ; like The target rotational speed of the screw is then .

[0045] The real-time screw speed data represents the screw's current actual operating speed. The target screw speed to be executed is an ideal speed initially derived by combining the current real-time screw speed data with the target speed adjustment amount, without considering equipment mechanical limitations. The preset control cycle is a fixed control time interval to ensure the timeliness and consistency of the screw's theoretical acceleration calculation. The screw's theoretical acceleration is the theoretical rate of change of screw speed per unit time, directly reflecting the speed of screw speed adjustment.

[0046] The maximum allowable acceleration of the screw is a preset critical value based on the mechanical strength of the equipment and the load-bearing capacity of the transmission system, used to avoid mechanical shock caused by sudden changes in screw speed. The target screw speed is the final speed actually executed after acceleration limiting, which satisfies both process speed regulation requirements and ensures equipment operation safety, achieving a balance between speed regulation effect and mechanical protection.

[0047] Encoding converts the target screw speed, a process parameter, into an electrical signal format recognizable by the screw drive unit, eliminating compatibility issues between signal transmission and execution. The screw speed control command, carrying precise speed adjustment information, is sent to the screw drive unit. The screw drive unit then drives the screw to operate at the target speed according to the command, completing the closed-loop execution of adaptive control and ensuring the extrusion process proceeds stably according to preset parameters.

[0048] In practical applications, when processing recycled bottle flakes, if the pressure regulation requirement direction coefficient is 1, the real-time screw speed is 80 r / s, the target speed adjustment is 10 r / s, and the preset control cycle is 0.5 s, after calculating the target screw speed and the maximum allowable screw acceleration, it is further calculated that the theoretical screw acceleration exceeds the maximum allowable acceleration. In this case, the system does not directly use the target screw speed, but instead calculates the transition speed for the current control cycle based on the maximum allowable screw acceleration to generate the target screw speed. This method avoids the mechanical shock to the screw drive system caused by sudden speed changes, while ensuring the continuity of pressure regulation, effectively adapting to frequent operating condition fluctuations in recycled material processing, and balancing process stability and equipment safety.

[0049] like Figure 2 The diagram shown is a system block diagram of an adaptive control system for an extrusion screw in a plastic extruder, provided in an embodiment of the present invention. The system includes: The data acquisition module is used to collect the operating data of the plastic extruder and update it to the data buffer pool based on a time sliding window. The operating data of the plastic extruder includes at least the die head melt pressure data, screw motor load current data, and screw real-time speed data. The pressure calculation module is used to calculate the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool; The pressure zoning module is used to construct a three-level zoning evaluation model. It calculates the pressure deviation based on the effective pressure value and the preset target pressure benchmark value, and generates pressure control zones based on the comparison results of the pressure deviation with different preset pressure thresholds. The speed adjustment module is used to make a consistency judgment on the pressure change trend and the pressure adjustment demand direction of the pressure control area, generate a dynamic adjustment coefficient, and perform step size calculation and correction in combination with the pressure control area and screw motor load current data to generate the target speed adjustment amount. The instruction output module is used to calculate the target speed of the screw based on the real-time speed data of the screw and the target speed adjustment amount, perform acceleration limiting processing on the target speed of the screw, generate the target speed of the screw, and encode the target speed of the screw into a screw speed control instruction and send it to the screw drive unit.

[0050] Figure 2 The apparatus of the illustrated embodiment can be used to perform corresponding actions. Figure 1 The steps in the method embodiments shown are implemented in a similar manner and have similar technical effects, and will not be repeated here.

[0051] An electronic device includes a memory and a processor, the memory storing a computer program, wherein when the processor runs the computer program stored in the memory, the processor performs the steps of the adaptive control method for an extrusion screw for a plastic extruder as described in any of the preceding claims.

[0052] like Figure 3 The diagram shown is a hardware structure schematic of an electronic device according to an embodiment of the present invention. The electronic device 30 includes: a processor 31, a memory 32, and a computer program; wherein... The memory 32 is used to store the computer program, and the memory may also be flash memory. The computer program is, for example, an application program or functional module that implements the above method.

[0053] Processor 31 is configured to execute the computer program stored in the memory to implement the various steps performed by the device in the above method. For details, please refer to the relevant descriptions in the preceding method embodiments.

[0054] Alternatively, the memory 32 can be either standalone or integrated with the processor 31.

[0055] When the memory 32 is a device independent of the processor 31, the device may further include: Bus 33 is used to connect the memory 32 and the processor 31.

[0056] A readable storage medium storing a computer program, which, when executed by a processor, is used to implement the steps of the adaptive control method for an extrusion screw for a plastic extruder as described in any of the preceding claims.

[0057] The readable storage medium can be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of computer programs from one location to another. A computer storage medium can be any available medium accessible to a general-purpose or special-purpose computer. For example, a readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application-Specific Integrated Circuit (ASIC). Alternatively, the ASIC can be located in a user equipment. Of course, the processor and the readable storage medium can also exist as discrete components in a communication device. The readable storage medium can be a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0058] The present invention also provides a program product including executable instructions stored in a readable storage medium. At least one processor of the device can read the executable instructions from the readable storage medium, and the at least one processor executes the executable instructions to cause the device to implement the methods provided in the various embodiments described above.

[0059] In the embodiments of the above-described device, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0060] Through the above embodiments, this invention collects operating data of a plastic extruder and updates it to a data buffer pool based on a time-sliding window. The operating data of the plastic extruder includes at least die head melt pressure data, screw motor load current data, and screw real-time speed data. Based on the die head melt pressure data in the data buffer pool, the pressure change trend and effective pressure value are calculated. A three-level zoning evaluation model is constructed, and the pressure deviation is calculated based on the effective pressure value and a preset target pressure benchmark value. Based on the comparison results of the pressure deviation with different preset pressure thresholds, a pressure control zone is generated. The consistency of the pressure change trend and the pressure adjustment demand direction of the pressure control zone is judged to generate a dynamic adjustment coefficient. The step size is calculated and corrected in combination with the pressure control zone and screw motor load current data to generate the target speed adjustment amount. Based on the screw real-time speed data and the target speed adjustment amount, the target speed to be executed by the screw is calculated. The target speed to be executed by the screw is subjected to acceleration limitation processing to generate the screw target speed. The screw target speed is encoded into a screw speed control command and sent to the screw drive unit. This achieves the adaptive control effect of the extrusion screw, effectively preventing false pressure fluctuations caused by changes in material hardness, and significantly improving extrusion stability and response speed.

[0061] This invention constructs a data buffer pool based on a time-sliding window, simultaneously collecting multi-dimensional operational data such as melt pressure at the die head, screw motor load current, and real-time screw speed. It combines linear regression and arithmetic mean algorithms to calculate pressure change trends and effective pressure values, effectively filtering out data fluctuation interference and solving the problem of insufficient depth perception in existing single-data acquisition technologies. This invention designs a three-level partitioned evaluation model, dividing the pressure deviation into a stable dead zone, a fine-tuning zone, and an emphasis zone based on the comparison results between the pressure deviation and a preset pressure threshold. This achieves differentiated control characterized by "rapid convergence of large deviations, fine-tuning of small deviations, and no intervention in stable states," completely overcoming the limitations of traditional fixed-step adjustment strategies, significantly improving the accuracy and targeting of pressure regulation, and avoiding lag or over-adjustment. This invention generates a dynamic adjustment coefficient by judging the consistency between the pressure change trend and the direction of pressure regulation demand. When the directions are consistent, the adjustment amplitude is reduced to prevent overshoot; when the directions are opposite, the adjustment intensity is increased to reverse the trend, effectively suppressing system oscillations and ensuring the stability of the control process. This invention introduces screw motor load current fluctuation analysis and uses a resistance compensation factor to attenuate and correct the screw speed adjustment step size. This accurately distinguishes between pressure fluctuations caused by sudden changes in material properties and improper speed, avoiding excessive shearing and overheating degradation of materials due to misadjustment, and significantly improving the physical properties and size uniformity of recycled granules. Furthermore, this invention rationally controls the screw speed adjustment rate through acceleration limiting, preventing mechanical shocks to the equipment caused by sudden speed changes, and ensuring the safe operation and service life of the plastic extruder.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive control method for the extrusion screw of a plastic extruder, characterized in that, The method includes: The operation data of the plastic extruder is collected and updated to a data buffer pool based on a time sliding window. The operation data of the plastic extruder includes at least the die head melt pressure data, screw motor load current data, and screw real-time speed data. Based on the melt pressure data of the die head in the data buffer pool, calculate the pressure change trend and the effective pressure value; A three-level zoning evaluation model is constructed. The pressure deviation is calculated based on the effective pressure value and the preset target pressure benchmark value. Based on the comparison results of the pressure deviation with different preset pressure thresholds, a pressure control zone is generated. The consistency between the pressure change trend and the pressure adjustment demand direction of the pressure control area is judged to generate a dynamic adjustment coefficient. The step size is calculated and corrected by combining the pressure control area and the screw motor load current data to generate the target speed adjustment amount. Based on the real-time screw speed data and the target speed adjustment amount, the target screw speed to be executed is calculated, the target screw speed to be executed is subjected to acceleration limiting processing, the target screw speed is generated, and the target screw speed is encoded into a screw speed control command and sent to the screw drive unit.

2. The adaptive control method for the extrusion screw of a plastic extruder according to claim 1, characterized in that, The step of calculating the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool specifically includes: The data buffer pool is a FIFO queue with a preset capacity of N, which synchronously collects the operating data of the plastic extruder and updates the FIFO queue at a preset sampling frequency f. The pressure change trend of the head melt pressure data in the FIFO queue was calculated using a linear regression algorithm. The corresponding calculation formula is as follows: In the formula, n represents the number of sets of melt pressure data at the die head. ; This represents the timestamp for the acquisition of the i-th set of melt pressure data from the die head; This represents the melt pressure data of the i-th group of the die head; Calculate the effective pressure value of the head melt pressure data in the FIFO queue. .

3. The adaptive control method for the extrusion screw of a plastic extruder according to claim 1, characterized in that, The construction of a three-level zoning evaluation model involves calculating the pressure deviation based on the effective pressure value and a preset target pressure benchmark value, and generating pressure control zones based on the comparison results of the pressure deviation with different preset pressure thresholds. Specifically, this includes: The pressure deviation is calculated based on the absolute difference between the effective pressure value and the target pressure reference value. The pressure deviation is compared with a preset first pressure threshold and a second pressure threshold, wherein the first pressure threshold is less than the second pressure threshold; If the pressure deviation is less than the first pressure threshold, then the generated pressure control region is determined to be a stable dead zone. If the pressure deviation is between the first pressure threshold and the second pressure threshold, then the generated pressure control area is determined to be a fine-tuning area. If the pressure deviation is greater than the second pressure threshold, the generated pressure control area is determined to be an emphasis area.

4. The adaptive control method for the extrusion screw of a plastic extruder according to claim 1, characterized in that, The step of determining the consistency between the pressure change trend and the pressure regulation demand direction of the pressure control area, and generating a dynamic regulation coefficient, specifically includes: Based on the effective pressure value Compared with the target pressure reference value The difference relationship is used to generate the pressure regulation demand direction coefficient of the pressure control area. ,in, Represents a symbolic function; This indicates the need for pressure regulation; This indicates a need for stress reduction and adjustment; This indicates that there is no need for pressure adjustment. Based on the aforementioned pressure change trend Calculate the pressure change direction coefficient ,in, This indicates an upward trend in pressure; This indicates a downward trend in pressure; This indicates that the pressure shows no trend of change; like or If the pressure state is stable, the dynamic adjustment coefficient is generated. ,in, This indicates the preset threshold for a stable pressure change trend; like and If the trend of pressure change is determined to be consistent with the direction of pressure regulation demand, the dynamic regulation coefficient is generated. ,in, Indicates the suppression weight coefficient; This indicates the preset maximum pressure change trend threshold; like and If the trend of pressure change is determined to be opposite to the direction of pressure regulation demand, the dynamic regulation coefficient is generated. ,in, This represents the weighting coefficient.

5. The adaptive control method for the extrusion screw of a plastic extruder according to claim 1, characterized in that, The step-size calculation and correction, which combines the pressure control area and the screw motor load current data, to generate the target speed adjustment amount, specifically includes: If the pressure control region is a stable dead zone, then the screw speed adjustment base step size is... If the pressure control region is a fine-tuning region, then the preset fine-tuning step size parameter is invoked. As the basic step size for adjusting the screw speed If the pressure control region is an emphasis region, then the preset emphasis step size parameter is invoked. As the basic step size for adjusting the screw speed ; The screw speed adjustment step size is determined by the dynamic adjustment coefficient K. Make corrections and generate screw speed adjustment correction step sizes. ; The screw motor load current volatility was calculated using a sliding window relative volatility algorithm. ,in, This represents the standard deviation of the screw motor load current data; This represents the average value of the screw motor load current data; If the load current fluctuation rate of the screw motor is greater than the preset load fluctuation threshold, it is determined that the screw motor load state has changed abruptly. The screw speed adjustment correction step size is attenuated by the resistance compensation factor to generate the target speed adjustment amount; otherwise, it is determined that the screw motor load state is stable, and the screw speed adjustment correction step size is the target speed adjustment amount.

6. The adaptive control method for the extrusion screw of a plastic extruder according to claim 5, characterized in that, If the load current fluctuation rate of the screw motor is greater than a preset load fluctuation threshold, a sudden change in the load state of the screw motor is determined. The screw speed adjustment correction step size is then attenuated using a resistance compensation factor to generate the target speed adjustment amount, specifically including: Based on the screw motor load current fluctuation rate CV and the preset load fluctuation threshold The drag compensation factor is calculated using an exponential decay model. , ,in, Indicates the attenuation sensitivity coefficient; Through the resistance compensation factor Adjust the screw speed correction step size The target speed adjustment amount is generated by proportional attenuation. .

7. The adaptive control method for the extrusion screw of a plastic extruder according to claim 1, characterized in that, The process of calculating the target screw speed based on the real-time screw speed data and the target speed adjustment amount, and then applying acceleration limiting processing to the target screw speed to generate the target screw speed, specifically includes: Based on the pressure regulation demand direction coefficient The direction of speed adjustment is determined by the real-time speed data of the screw. and the target speed adjustment amount Calculate the target rotational speed of the screw. ; Based on the real-time screw speed data and the target rotational speed of the screw to be executed Calculate the theoretical acceleration of the screw Where T represents the preset control cycle; The theoretical acceleration of the screw With the maximum allowable acceleration of the screw The target rotational speed of the screw is generated by comparison. The comparison process is as follows: like The target rotational speed of the screw is then ; like The target rotational speed of the screw is then .

8. An adaptive control system for an extrusion screw of a plastic extruder, applied to the adaptive control method for an extrusion screw of a plastic extruder as described in any one of claims 1-7, characterized in that, The system includes: The data acquisition module is used to collect the operating data of the plastic extruder and update it to the data buffer pool based on a time sliding window. The operating data of the plastic extruder includes at least the die head melt pressure data, screw motor load current data, and screw real-time speed data. The pressure calculation module is used to calculate the pressure change trend and effective pressure value based on the melt pressure data of the die head in the data buffer pool; The pressure zoning module is used to construct a three-level zoning evaluation model. It calculates the pressure deviation based on the effective pressure value and the preset target pressure benchmark value, and generates pressure control zones based on the comparison results of the pressure deviation with different preset pressure thresholds. The speed adjustment module is used to make a consistency judgment on the pressure change trend and the pressure adjustment demand direction of the pressure control area, generate a dynamic adjustment coefficient, and perform step size calculation and correction in combination with the pressure control area and screw motor load current data to generate the target speed adjustment amount. The instruction output module is used to calculate the target speed of the screw based on the real-time speed data of the screw and the target speed adjustment amount, perform acceleration limiting processing on the target speed of the screw, generate the target speed of the screw, and encode the target speed of the screw into a screw speed control instruction and send it to the screw drive unit.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor runs the computer program stored in the memory, the processor performs the steps of the adaptive control method for the extrusion screw of a plastic extruder as described in any one of claims 1-7.

10. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it is used to implement the steps of the adaptive control method for the extrusion screw of a plastic extruder as described in any one of claims 1-7.

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