Digital management system for a rubber extrusion production line

Abstract

This invention discloses a digital management system for a rubber extrusion production line, belonging to the field of digital management of rubber processing lines. It collects all data from the rubber extrusion production line, providing subsequent traceability and one-click distribution of production process parameters. The system is configured with different production processes corresponding to each rubber product, allowing customers to select the appropriate process for their product. This eliminates the need for complex debugging and is easy to implement. Specifically, it constructs a cross-stage data association mechanism using the spatial position of the rubber strip as a tracking index. Parameters collected from the molding, vulcanizing, and cooling stages are associated with the same tracking micro-element, and data from the plasticizing stage is indirectly associated through batch attribution. This provides a data foundation for cross-stage parameter fusion, aiming to ensure the accuracy and traceability of production data, saving production staff time spent setting and matching individual machine parameters, resulting in a low error rate and high accuracy.

Description

Technical Field

[0001] This invention relates to the field of digital management of rubber processing lines, and more specifically, to a digital management system for a rubber extrusion production line. Background Technology

[0002] The core task of a rubber extrusion production line is to process rubber compound (rubber raw material) into rubber products with a fixed cross-sectional shape through continuous processes such as heating, pressurizing, vulcanization, and cooling. Unlike plastic extrusion, which is mainly a physical melting process, rubber extrusion molding requires an irreversible chemical transformation from a viscous flow state to a cross-linked elastomer. In the plasticizing section, the rubber compound changes from an elastic state to a viscous flow state. After obtaining the cross-sectional shape through the die, a molecular chain cross-linking reaction occurs in the vulcanization channel. Finally, it is cooled and shaped into an elastomer product. In the entire production process, the traction speed acts simultaneously on three stages: expansion and stretching, vulcanization residence time, and cooling and shrinkage. Changes in a single control variable will simultaneously have a coupled effect on multiple physical effects.

[0003] According to the search results, such as the "A Method and Apparatus for Linked Production of Rubber Hose Extrusion" disclosed in Chinese Patent CN102729446A, the temperature of each section of the barrel is maintained at a set value by a temperature control system. The pressure of the die head is stabilized by a closed loop formed by a melt pressure transmitter and a PID controller. The diameter is measured online by a diameter gauge and then fed back to adjust the traction speed. The feeding speed is kept synchronized with the screw speed, and a constant tension device is provided to ensure the stable operation of the production line.

[0004] However, the problem with this solution is that temperature, pressure, and size each form an independent feedback loop, corresponding to different actuators such as heaters, screw motors, and traction motors. When a certain link encounters a working condition that requires adjustment of traction speed, such as when the plasticizing section has a risk of scorching and needs to speed up to vent, or when the temperature fluctuates in the vulcanizing section and needs to change the residence time by adjusting the traction speed, due to the lack of information transmission and action coordination between the loops, it is difficult to make a single traction speed respond to the control needs of multiple links at the same time.

[0005] In addition, each monitoring parameter is based on a timestamp. The head pressure data and diameter gauge size data collected at the same time will have correlation errors due to transmission delays, making it impossible to perform error-free correlation analysis between monitoring parameters and product quality. Summary of the Invention

[0006] The purpose of this invention is to address practical shortcomings, and a digital management system for a rubber extrusion production line is provided.

[0007] The objective of this invention can be achieved through the following technical solution: a digital management system for a rubber extrusion production line, comprising:

[0008] The rubber compound micro-element spatiotemporal tracking module is used to track the continuous rubber strip by using the real-time travel distance fed back by the extrusion traction encoder as the spatial coordinate marker. After the continuous rubber strip leaves the extruder die, it is divided into multiple tracking micro-elements according to a preset unit length. Melt pressure parameters, vulcanization channel temperature parameters, and cooling channel temperature parameters are collected along the forming section, vulcanization section, and cooling section, respectively. The measured values ​​of traction speed and product outer diameter are also collected. The extrusion shear parameters collected in the plasticizing section are associated with each tracking micro-element formed by the batch of rubber compound through batch attribution.

[0009] The heat accumulation monitoring module is used to calculate the cumulative value of the heat history that the rubber compound has undergone in the extruder barrel based on the extrusion shear parameters, and use it as a venting decision parameter.

[0010] The expansion prediction and monitoring module is used to calculate the forming expansion prediction coefficient when the current tracking micro-element leaves the extruder die based on the melt pressure parameters and their dynamic change trends, and to serve as a feedforward correction parameter.

[0011] The sulfurization monitoring module is used to calculate the cumulative equivalent sulfurization effect experienced by the micro-element in the sulfurization channel based on the temperature parameters and traction speed of the sulfurization channel, and to use it as a feedback correction parameter.

[0012] The shrinkage compensation monitoring module is used to calculate the cooling shrinkage compensation coefficient of the product corresponding to the currently tracked micro-element due to cooling shrinkage based on the cooling channel temperature parameters, traction speed and the measured value of the product outer diameter, as a limiting correction parameter.

[0013] The cascaded decision execution module receives all the above output parameters and performs fusion analysis in the cascaded order of first-level emptying decision, feedforward decision advance correction, feedback decision lag correction, and amplitude limiting decision boundary constraint correction, and issues speed commands to the traction roller frequency converter accordingly.

[0014] Furthermore, the process of calculating the cumulative value of the thermal history based on the extrusion shear parameters includes:

[0015] The moment when the rubber compound enters the extruder barrel is taken as the accumulation start time, and the currently calculated execution time is taken as the accumulation end time. The accumulation start time to the accumulation end time constitutes the plasticizing accumulation time interval.

[0016] First, obtain the extrusion shear parameters continuously collected within the plasticizing cumulative time interval according to the preset sampling period, including the instantaneous value of screw speed, the instantaneous value of screw drive current, and the temperature values ​​of each measuring point in the barrel;

[0017] Secondly, for each sampling moment, the product of the instantaneous screw speed and the instantaneous screw drive current is taken as the instantaneous shear mechanical power. The instantaneous shear mechanical power is continuously integrated and accumulated over the plasticizing accumulation time interval, and multiplied by a preset shear heat generation conversion coefficient to obtain the cumulative shear heat generation amount representing the contribution of shear heat generation. At the same time, the arithmetic mean of the temperature values ​​of each measuring point of the barrel is taken to obtain the instantaneous average temperature of the barrel. The instantaneous average temperature of the barrel is continuously integrated and accumulated over the plasticizing accumulation time interval, and multiplied by a preset external heating conduction coefficient to obtain the cumulative external heating amount representing the contribution of external heating.

[0018] Finally, the cumulative amount of heat generated by shear is added to the cumulative amount of external heating to obtain the cumulative value of the thermal history.

[0019] Furthermore, the process of calculating the molding expansion prediction coefficient based on melt pressure parameters includes:

[0020] Receive the melt pressure parameters of the forming section; the melt pressure parameters are the instantaneous values ​​of the melt pressure.

[0021] Using the currently calculated execution time as the end point of the window, extract the historical melt pressure data within the preset short time window duration, take the instantaneous melt pressure value at the end of the window, subtract the historical melt pressure value at the corresponding start time of the preset short time window from the historical melt pressure data, divide by the duration of the preset short time window, and obtain the first-order rate of change of melt pressure within the preset short time window.

[0022] The molding expansion prediction coefficient is obtained by multiplying the instantaneous value of the current melt pressure, the first-order rate of change, and the Mooney viscosity index of the batch of rubber by their respective preset weighting coefficients and then weighting them.

[0023] Furthermore, the process of calculating the accumulated equivalent vulcanization effect of the tracking micro-element based on the vulcanization channel temperature parameters and traction speed includes:

[0024] The accumulation start time is recorded when the tracking micro-element enters the vulcanization channel, and the accumulation end time is recorded when the current calculated execution time is recorded. The vulcanization accumulation time interval is determined, and the traction speed and vulcanization channel temperature parameters are obtained at each sampling time in the time interval. The vulcanization channel temperature parameters are the measured values ​​of the medium temperature at each temperature measuring point along the vulcanization channel.

[0025] Starting from the cumulative start time, the traction speed at each sampling time is continuously integrated over time to obtain the real-time tracking micro-element position at any time in the vulcanization channel. Based on the coordinates of each temperature measuring point and the measured value of the medium temperature, a mapping relationship between the channel position and the medium temperature is established. The real-time tracking micro-element position is substituted into the mapping relationship and the calculated value of the medium temperature at the real-time tracking micro-element position is obtained by interpolation.

[0026] Using the pre-calibrated frequency factor and vulcanization reaction activation energy of the batch of rubber compound as parameters, the estimated values ​​of the medium temperature obtained at each moment are used as reaction temperature parameters. The instantaneous vulcanization reaction rate at each moment is calculated according to the Arrhenius equation, and then the rate is accumulated by time integration within the vulcanization accumulation time interval to obtain the equivalent vulcanization effect accumulation value of the tracking micro-element, which is used as the engineering characterization parameter of the actual vulcanization degree of the tracking micro-element.

[0027] Furthermore, the cooling contraction compensation coefficient is calculated in the following manner:

[0028] The cooling channel temperature parameters, traction speed, and measured outer diameter of the product are obtained. The cooling channel temperature parameters are the real-time temperature gradient of the cooling medium along the length of the cooling channel.

[0029] Taking the material properties of this batch of rubber as the object, a mapping relationship table between the cooling medium temperature gradient, traction speed and shrinkage rate is established in advance through offline experiments. The shrinkage correction factor is obtained by looking up the table or interpolating based on the current real-time temperature gradient value and traction speed. The difference between the measured outer diameter of the product and the preset target outer diameter is calculated and divided by the preset target outer diameter to obtain the relative value of the outer diameter deviation. The relative value of the outer diameter deviation is multiplied by the shrinkage correction factor to obtain the cooling shrinkage compensation coefficient.

[0030] Furthermore, the cascading sequence content in the cascading decision execution module includes:

[0031] First-level venting decision: The venting decision parameter is compared with the preset scorch threshold value of the batch of rubber as the decision condition. If the decision condition is met, the venting speed is obtained by multiplying the current traction speed by the preset venting acceleration coefficient and output as the speed command, and subsequent corrections are terminated; otherwise, the current traction speed is maintained as the speed command and subsequent multi-level selective corrections are entered.

[0032] Subsequent multi-level selective correction: The feedforward correction parameter, feedback correction parameter, and limiting correction parameter are compared with the corresponding preset thresholds in sequence to determine whether the correction conditions are met. If the conditions are met, the correction parameter is converted into the corresponding speed correction amount and added to the current speed command; otherwise, the correction level is skipped.

[0033] Furthermore, the subsequent multi-level corrections are performed in the following order:

[0034] Feedforward judgment advance correction: The deviation between the forming expansion prediction coefficient and the preset target expansion ratio is used as the judgment basis. When the deviation value exceeds the preset expansion threshold, the deviation value is multiplied by the preset feedforward gain coefficient to obtain the feedforward acceleration correction amount, which is then added to the acceleration setpoint of the current traction speed.

[0035] Feedback judgment lag correction: The difference between the cumulative value of the equivalent vulcanization effect and the vulcanization target value of the process standard is used as the vulcanization deviation. When the absolute value of the deviation exceeds the preset vulcanization deviation threshold, the speed fine-tuning direction is determined according to the sign of the deviation, and the speed fine-tuning amplitude is determined by proportional-integral calculation based on the amplitude of the deviation. The speed fine-tuning amount is obtained by combining the direction and the amplitude and superimposed on the current speed command.

[0036] Limiting judgment boundary constraint correction: When the cooling contraction compensation coefficient is outside the preset effective range, the coefficient is added to the current speed command as a multiplication factor.

[0037] Compared with the prior art, the advantages of this invention are:

[0038] 1. This invention addresses rubber production lines by constructing a cross-stage data association mechanism using the spatial position of rubber strips as a tracking index. Parameters collected from the molding, vulcanizing, and cooling stages are associated with the same tracking micro-element, and data from the plasticizing stage is indirectly associated through batch attribution. This provides a data foundation for cross-stage parameter fusion, aiming to eliminate phase misalignment of monitoring parameters caused by transmission delays. Based on this, multiple original measurement values ​​from each stage are extracted a second time and transformed into judgment parameters with specific control orientations. These multiple physically characterized judgment parameters are then cascaded and adjudicated in a cascaded order, ultimately acting uniformly on the traction actuator. This solves the technical problem of a lack of unified coordination mechanism for multi-stage control needs in independent control modes of each production stage, and the inability of various parameters to respond collaboratively.

[0039] 2. This invention also transforms multiple original measurement values ​​at each stage into judgment parameters that can characterize the production status at each stage through secondary extraction. Specifically, this involves: constructing a cumulative thermal history value by combining temperature measurement values ​​with the dual integration of shear heat generation and external heating, which serves as the venting judgment parameter; calculating the forming expansion prediction coefficient when the current tracking micro-element leaves the die based on melt pressure parameters and their dynamic change trends, which serves as the feedforward correction parameter; calculating the cumulative equivalent vulcanization effect based on the position of the tracking micro-element in the vulcanization channel and the temperature field integration, which serves as the feedback correction parameter; and calculating the cooling shrinkage compensation coefficient caused by cooling shrinkage of the product corresponding to the current tracking micro-element based on the cooling channel temperature parameters, traction speed, and the measured outer diameter of the product, which serves as the amplitude limiting correction parameter.

[0040] Furthermore, a hierarchical execution sequence of venting decision → feedforward correction → feedback correction → amplitude limiting correction is constructed to participate in the hierarchical generation of speed commands, in order to solve the problem in the existing technology that each parameter aims to maintain the set value and lacks the ability to deeply represent the physical mechanism. Attached Figure Description

[0041] Figure 1 This is a schematic diagram illustrating the data flow between the modules of this invention;

[0042] Figure 2 This is a flowchart illustrating the emptying decision and multi-level correction logic of the cascaded decision execution module of the present invention. Detailed Implementation

[0043] 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. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0044] Example 1: This invention discloses a digital management system for a rubber extrusion production line. Please refer to [link / reference]. Figure 1 It includes a data acquisition layer, a monitoring layer, and a decision execution layer. The data acquisition layer is equipped with a rubber micro-element spatiotemporal tracking module. The monitoring layer is equipped with a heat accumulation monitoring module, an expansion prediction monitoring module, a vulcanization degree monitoring module, a shrinkage compensation monitoring module, and a CPK monitoring module. The execution layer is equipped with a cascaded decision execution module.

[0045] The rubber compound micro-element spatiotemporal tracking module uses the real-time travel distance fed back by the extrusion traction encoder as the spatial coordinate tracking identifier. After the continuous rubber strip leaves the extruder die, it is divided into multiple tracking micro-elements according to a preset unit length. Melt pressure parameters, vulcanization channel temperature parameters, and cooling channel temperature parameters are collected along the forming section, vulcanization section, and cooling section, respectively. The measured values ​​of traction speed and product outer diameter are also collected. The extrusion shear parameters collected in the plasticizing section are associated with each tracking micro-element formed by the batch of rubber compound through batch affiliation. A cross-stage data association mechanism with spatial coordinates as the tracking identifier is established, so that the data collected in each section can be associated with the same tracking micro-element, rather than relying on conventional monitoring methods based on timestamp alignment.

[0046] The heat accumulation monitoring module is used to calculate the cumulative heat history of the rubber compound within the extruder barrel based on the extrusion shear parameters of the plasticizing section, and uses this as a venting decision parameter. The specific process includes:

[0047] The moment when the rubber compound enters the extruder barrel is taken as the start time of accumulation, and the currently calculated execution time is taken as the end time of accumulation. The period from the start time of accumulation to the end time of accumulation constitutes the plasticizing accumulation time interval.

[0048] The extrusion shear parameters are continuously collected within the plasticizing cumulative time interval according to the preset sampling period, including the instantaneous value of screw speed, the instantaneous value of screw drive current, and the temperature values ​​of each measuring point in the barrel. The temperature values ​​of each measuring point in the barrel are the temperature values ​​of multiple heating sections such as the feeding section, compression section, and metering section that are divided along the length of the barrel. Each section is equipped with an independent temperature sensor.

[0049] For each sampling moment, the product of the instantaneous value of the screw speed and the instantaneous value of the screw drive current is taken as the instantaneous shear mechanical power. The instantaneous shear mechanical power is continuously integrated and accumulated within the plasticizing accumulation time interval, and multiplied by the preset shear heat generation conversion coefficient to obtain the cumulative amount of shear heat generation that characterizes the contribution of shear heat generation. This is the physical basis for estimating the heat accumulated by the rubber compound due to shear heat generation.

[0050] Simultaneously, the arithmetic mean of the temperature values ​​at each measuring point of the barrel is taken to obtain the instantaneous average temperature value of the barrel. This instantaneous average temperature value of the barrel is then continuously integrated and accumulated over the plasticizing cumulative time interval, and multiplied by a preset external heating conductivity coefficient to obtain the cumulative external heating amount that characterizes the contribution of external heating.

[0051] The cumulative shear heat generation is added to the cumulative external heating to obtain the cumulative thermal history value. The shear heat generation conversion coefficient and the external heating conductivity coefficient are corrected by the Mooney viscosity test value of this batch of rubber compound.

[0052] The cumulative thermal history value obtained by this module represents the total heat energy (shear heat generation + external heating) accumulated by the rubber compound in the barrel from the start of plasticization to the current moment. It reflects whether the rubber compound is close to the critical state of scorching. Unlike the instantaneous monitoring method that only reflects whether the current temperature exceeds the limit, it can characterize the true state of the heat accumulation of the rubber compound. When the heat accumulation is too high, it means that the vulcanization system in the rubber compound may cross-link prematurely, resulting in the inability to vulcanize normally or the formation of gel particles.

[0053] The swell prediction and monitoring module is used to calculate the swell prediction coefficient of the rubber compound after it leaves the extruder die based on the melt pressure parameters and their dynamic changes in the forming section. This coefficient serves as a feedforward correction parameter. The specific process includes:

[0054] Receive the melt pressure parameters of the forming section; the melt pressure parameters are the instantaneous values ​​of the melt pressure.

[0055] Using the currently calculated execution time as the end point of the window, extract the historical melt pressure data within the preset short time window duration, take the instantaneous melt pressure value at the end of the window, subtract the historical melt pressure value at the corresponding start time of the preset short time window from the historical melt pressure data, divide by the duration of the preset short time window, and obtain the first-order rate of change of melt pressure within the preset short time window.

[0056] The instantaneous value of the current melt pressure, the first-order rate of change, and the Mooney viscosity index of the batch of rubber are multiplied by their respective preset weighting coefficients and then weighted to obtain the molding expansion prediction coefficient. This coefficient is a dimensionless parameter that represents the predicted cross-sectional size expansion ratio of the rubber after it leaves the die due to the elastic memory effect. It takes into account the current pressure level, the pressure change trend, and the viscosity characteristics of the rubber itself. Unlike the steady-state pressure monitoring method, which only reflects whether the current pressure deviates from the set value, this coefficient reflects the extent of transient expansion of the rubber after extrusion under the current die head pressure and shear rate. It can characterize the dynamic change of the expansion trend. If the coefficient deviates from the target value, the traction speed needs to be adjusted in advance to offset the upcoming size fluctuation.

[0057] The sulfurization monitoring module is used to calculate the cumulative equivalent sulfurization effect of the micro-element in the sulfurization channel based on the temperature parameters and traction speed of the sulfurization channel in the sulfurization section, and to use it as a feedback correction parameter.

[0058] The calculation process for the cumulative equivalent sulfurization effect of the tracking micro-element is as follows:

[0059] The moment when the tracking micro-element enters the vulcanization channel, as recorded by the trigger sensor set at the entrance of the vulcanization channel, is taken as the accumulation start time, and the currently calculated execution time is taken as the accumulation end time. The vulcanization accumulation time interval is determined, and the traction speed and vulcanization channel temperature parameters are obtained at each sampling moment in the time interval. The vulcanization channel temperature parameters are the measured values ​​of the medium temperature at each temperature measuring point along the vulcanization channel.

[0060] Starting from the cumulative start time, the traction speed at each sampling time is continuously integrated over time to obtain the real-time tracking micro-element position at any time in the vulcanization channel. Based on the coordinates of each temperature measuring point and the measured value of the medium temperature, a mapping relationship between the channel position and the medium temperature is established. The real-time tracking micro-element position is substituted into the mapping relationship and the estimated value of the medium temperature at the real-time tracking micro-element position is obtained by interpolation.

[0061] Using the pre-calibrated frequency factor and vulcanization reaction activation energy of this batch of rubber compound as parameters, the estimated values ​​of the medium temperature obtained at each moment are used as reaction temperature parameters. The instantaneous vulcanization reaction rate at each moment is calculated according to the Arrhenius equation, which is the core formula in chemical kinetics that describes how temperature affects the reaction rate.

[0062] The instantaneous sulfidation reaction rate is then integrated over time within the sulfidation accumulation time interval to obtain the equivalent sulfidation effect accumulation value of the tracking micro-element, which serves as an engineering characterization parameter for the actual sulfidation degree of the tracking micro-element.

[0063] The cumulative equivalent vulcanization effect is calculated by tracking the actual position and temperature field distribution of the micro-element within the channel. Unlike simply monitoring whether the channel temperature is constant, this method can characterize the actual crosslinking progress of the tracking micro-element.

[0064] The shrinkage compensation monitoring module is used to calculate the cooling shrinkage compensation coefficient caused by cooling shrinkage based on the cooling channel temperature parameters, traction speed, and measured outer diameter of the product in the cooling section, as a limiting correction parameter.

[0065] The cooling shrinkage compensation coefficient is calculated as follows:

[0066] The cooling channel temperature parameters, traction speed, and measured outer diameter of the product are obtained. The cooling channel temperature parameters are the real-time temperature gradient of the cooling medium along the length of the cooling channel.

[0067] Taking the material properties of this batch of rubber as the object, a mapping relationship table between the cooling medium temperature gradient, traction speed and shrinkage rate is established in advance through offline experiments. The shrinkage correction factor is obtained by looking up the table or interpolating based on the current real-time temperature gradient value and traction speed. The difference between the measured outer diameter of the product and the preset target outer diameter is calculated and divided by the preset target outer diameter to obtain the relative value of the outer diameter deviation. The relative value of the outer diameter deviation is multiplied by the shrinkage correction factor to obtain the cooling shrinkage compensation coefficient, which reflects the degree of influence of the cooling section temperature gradient on the final product outer diameter. The larger the coefficient, the more significant the cooling shrinkage, and the traction speed command needs to be limited accordingly to prevent over-compensation.

[0068] The original measured values ​​at each stage are not directly used for closed-loop control. Instead, they are transformed into decision parameters with specific control orientations through secondary extraction processes such as integral accumulation, position mapping, and correction factor conversion. The thermal history cumulative value points to venting decision, the expansion prediction coefficient points to feedforward correction, the sulfidation deviation points to feedback correction, and the shrinkage compensation coefficient points to amplitude limiting correction.

[0069] Example 2: Please refer to Figures 1-2 The cascaded decision execution module is used to receive the above-mentioned decision parameters and correction parameters, and perform fusion analysis according to the cascaded sequence of first-level emptying decision, feedforward judgment advance correction, feedback judgment lag correction, and limit judgment boundary constraint correction. Based on this, it issues speed commands to the traction roller frequency converter. The cascaded sequence mainly includes the first-level emptying decision and subsequent multi-level selective correction.

[0070] First-level venting decision: The venting decision parameter is compared with the preset scorch critical value of the batch of rubber as the decision condition. It is determined whether the cumulative value of the thermal history is greater than or equal to the preset scorch critical value of the batch of rubber. If the cumulative value of the thermal history is greater than or equal to the preset scorch critical value of the batch of rubber, the decision condition is determined to be met. The venting speed is obtained by multiplying the current traction speed by the preset venting acceleration coefficient and is output as the speed command. The subsequent correction is terminated. Otherwise, the current traction speed is maintained as the speed command and the subsequent multi-level selective correction is entered.

[0071] Subsequent multi-level selective correction: The feedforward correction parameter, feedback correction parameter, and limiting correction parameter are compared with the corresponding preset thresholds in sequence to determine whether the correction conditions are met. If the conditions are met, the correction parameter is converted into the corresponding speed correction amount and added to the current speed command; otherwise, the correction level is skipped.

[0072] Specifically, the conversion rules for the parameters at each level of correction are as follows:

[0073] Feedforward judgment and advance correction: The forming expansion prediction coefficient is compared with the preset target expansion ratio to obtain the deviation value. If the absolute value of the deviation value is greater than or equal to the preset expansion threshold, it is determined that the correction condition is met. The deviation value is multiplied by the preset feedforward gain coefficient to obtain the feedforward acceleration correction amount. This feedforward acceleration correction amount is superimposed on the acceleration setpoint of the current traction speed, so that the traction speed dynamically changes from the current value towards the target correction direction.

[0074] Feedback judgment lag correction: The cumulative value of the equivalent vulcanization effect is compared with the preset process standard vulcanization target value to obtain the vulcanization deviation amount. The absolute value of the vulcanization deviation amount is compared with the preset vulcanization deviation threshold. If it is greater than or equal to the preset vulcanization deviation threshold, it is determined that the correction condition is met. The speed fine-tuning amplitude is determined by proportional-integral calculation based on the amplitude of the vulcanization deviation amount. Specifically, the proportional-integral calculation is as follows: the preset proportional gain coefficient is multiplied by the current vulcanization deviation amount to obtain the proportional compensation component. The preset integral gain coefficient is multiplied by the integral value of the vulcanization deviation amount over time to obtain the integral compensation component. The proportional compensation component and the integral compensation component are superimposed to obtain the speed fine-tuning amplitude.

[0075] The speed fine-tuning amount is obtained by combining the direction and amplitude and then superimposed on the current speed command to perform hysteresis correction. Among them, if the sign of the vulcanization deviation is positive, the speed fine-tuning direction is negative, and if the sign is negative, the speed fine-tuning direction is positive.

[0076] Limiting judgment boundary constraint correction: Calculate the difference between the cooling contraction compensation coefficient and the preset effective range. If the difference is greater than the preset effective deviation threshold, it is determined that the correction condition is met. Multiply the cooling contraction compensation coefficient as a multiplication factor with the current speed command and execute the boundary constraint.

[0077] After secondary extraction, multiple original measurement values ​​at each stage are transformed into decision parameters for specific control directions. The decision parameters of multiple physical representations are then cascaded and adjudicated in a cascaded order, and finally uniformly applied to the traction actuator. This effectively solves the technical problems of lack of unified coordination mechanism for multi-link control needs and inability of various parameters to respond in coordination in the existing independent closed-loop control mode at each stage.

[0078] Taking a rubber sealing strip manufacturer as an example, the company produces three sealing strip products with different cross-sectional shapes and vulcanization process requirements. For products with different production processes, customers only need to select the corresponding production process parameters according to the product's corresponding production process. The production process parameters are pre-stored in the system database in the form of process formulas. Operators only need to select the product model to be produced on the human-machine interface, and the system will automatically retrieve the corresponding preset process standard vulcanization target value, target expansion ratio, and threshold parameters for each stage, and send them to the corresponding monitoring module and cascaded adjudication execution module. Operators do not need to manually set individual machine parameters one by one, nor do they need to rely on personal experience to judge the matching relationship between parameters, and can complete product switching. This saves operators from setting and matching individual machine parameters, which results in a low fault tolerance rate.

[0079] Example 3: The system also includes a CPK monitoring module and an alarm module. This module is connected to the rubber micro-element spatiotemporal tracking module, the heat accumulation monitoring module, the expansion prediction monitoring module, the vulcanization monitoring module, and the shrinkage compensation monitoring module, respectively. It calculates the CPK process capability index based on the real-time sequence of the product outer diameter detection parameters, which is used as a quality monitoring judgment parameter. Based on this, it outputs quality monitoring information and quality alarm signals to the human-machine interface.

[0080] The CPK process capability index is calculated as follows: taking the measured outer diameter values ​​of n products continuously collected according to a preset sampling period within the current production batch as a sample sequence, n≥20, the arithmetic mean and sample standard deviation of the sample sequence are calculated; taking the preset target outer diameter as the specification center and the preset upper tolerance limit and lower tolerance limit as specification limits, the upper limit capability index and lower limit capability index are calculated respectively, and the smaller value of the two is taken as the CPK process capability index;

[0081] It also receives output parameters from each monitoring module and generates alarm signals for the alarm stage based on the comparison results between the output parameters and their respective safety thresholds.

[0082] It should be noted that this case involves comparisons of multiple preset or standard values. These preset or standard values ​​are obtained through offline experiments or statistical analysis of historical production data and are pre-stored in the process formula library before the system is put into use. When switching product specifications or rubber batches, the system calls the corresponding preset parameters from the formula library.

[0083] In summary, this application addresses rubber extrusion production lines by constructing a cross-stage data association mechanism based on the spatial position of the rubber strip as the tracking index. This mechanism links parameters collected from the molding, vulcanizing, and cooling stages to the same tracking micro-element and indirectly associates data from the plasticizing stage through batch attribution. This provides a data foundation for cross-stage parameter fusion, aiming to eliminate phase misalignment of monitoring parameters caused by transmission delays and ensure the accuracy and traceability of production data.

[0084] Based on this, multiple original measurement values ​​at each stage are extracted twice and transformed into judgment parameters for specific control directions. These parameters are then cascaded and corrected in a cascaded order, and finally uniformly applied to the traction actuator. This solves the technical problem of the lack of a unified coordination mechanism for the multi-stage control needs in the independent control mode of each production stage, and the inability of various parameters to respond in a coordinated manner, thereby reducing the fault tolerance rate.

[0085] The above description is merely a preferred embodiment of the present invention; however, the scope of protection of the present invention is not limited thereto; any equivalent substitutions or modifications made by those skilled in the art within the technical scope disclosed in the present invention, based on the technical solution and its improved concept, should be covered within the scope of protection of the present invention.

Claims

1. A digital management system for a rubber extrusion production line, characterized in that: include: The rubber compound micro-element spatiotemporal tracking module is used to track the continuous rubber strip by using the real-time travel distance fed back by the extrusion traction encoder as the spatial coordinate marker. After the continuous rubber strip leaves the extruder die, it is divided into multiple tracking micro-elements according to a preset unit length. Melt pressure parameters, vulcanization channel temperature parameters, and cooling channel temperature parameters are collected along the forming section, vulcanization section, and cooling section, respectively. The measured values ​​of traction speed and product outer diameter are also collected. The extrusion shear parameters collected in the plasticizing section are associated with each tracking micro-element formed by the batch of rubber compound through batch attribution. The heat accumulation monitoring module is used to calculate the cumulative value of the heat history that the rubber compound has undergone in the extruder barrel based on the extrusion shear parameters, and use it as a venting decision parameter. The expansion prediction and monitoring module is used to calculate the forming expansion prediction coefficient when the current tracking micro-element leaves the extruder die based on the melt pressure parameters and their dynamic change trends, and to serve as a feedforward correction parameter. The sulfurization monitoring module is used to calculate the cumulative equivalent sulfurization effect experienced by the micro-element in the sulfurization channel based on the temperature parameters and traction speed of the sulfurization channel, and to use it as a feedback correction parameter. The shrinkage compensation monitoring module is used to calculate the cooling shrinkage compensation coefficient of the product corresponding to the currently tracked micro-element due to cooling shrinkage based on the cooling channel temperature parameters, traction speed and the measured value of the product outer diameter, as a limiting correction parameter. The cascaded decision execution module receives the aforementioned decision parameters and correction parameters, performs fusion analysis in the cascaded order of first-level emptying decision, feedforward decision advance correction, feedback decision lag correction, and amplitude limit decision boundary constraint correction, and issues speed commands to the traction roller frequency converter accordingly.

2. The digital management system for a rubber extrusion production line according to claim 1, characterized in that: The process of calculating the cumulative value of the thermal history based on the extrusion shear parameters of the plasticizing section includes: The moment when the rubber compound enters the extruder barrel is taken as the accumulation start time, and the currently calculated execution time is taken as the accumulation end time. The accumulation start time to the accumulation end time constitutes the plasticizing accumulation time interval. First, obtain the extrusion shear parameters continuously collected within the plasticizing cumulative time interval according to the preset sampling period, including the instantaneous value of screw speed, the instantaneous value of screw drive current, and the temperature values ​​of each measuring point in the barrel; Secondly, for each sampling moment, the product of the instantaneous screw speed and the instantaneous screw drive current is taken as the instantaneous shear mechanical power. The instantaneous shear mechanical power is continuously integrated and accumulated over the plasticizing accumulation time interval, and multiplied by a preset shear heat generation conversion coefficient to obtain the cumulative shear heat generation amount representing the contribution of shear heat generation. At the same time, the arithmetic mean of the temperature values ​​of each measuring point of the barrel is taken to obtain the instantaneous average temperature of the barrel. The instantaneous average temperature of the barrel is continuously integrated and accumulated over the plasticizing accumulation time interval, and multiplied by a preset external heating conduction coefficient to obtain the cumulative external heating amount representing the contribution of external heating. Finally, the cumulative amount of heat generated by shear is added to the cumulative amount of external heating to obtain the cumulative value of the thermal history.

3. The digital management system for a rubber extrusion production line according to claim 2, characterized in that: The process of calculating the molding expansion prediction coefficient based on melt pressure parameters includes: Receive the melt pressure parameters of the forming section; the melt pressure parameters are the instantaneous values ​​of the melt pressure. Using the currently calculated execution time as the end point of the window, extract the historical melt pressure data within the preset short time window duration, take the instantaneous melt pressure value at the end of the window, subtract the historical melt pressure value at the corresponding start time of the preset short time window from the historical melt pressure data, divide by the duration of the preset short time window, and obtain the first-order rate of change of melt pressure within the preset short time window. The molding expansion prediction coefficient is obtained by multiplying the instantaneous value of the current melt pressure, the first-order rate of change, and the Mooney viscosity index of the batch of rubber by their respective preset weighting coefficients and then weighting them.

4. The digital management system for a rubber extrusion production line according to claim 3, characterized in that: The process of calculating and tracking the accumulated equivalent sulfurization effect of the micro-element based on the sulfurization channel temperature parameters and traction speed includes: The accumulation start time is recorded when the tracking micro-element enters the vulcanization channel, and the accumulation end time is recorded when the current calculated execution time is recorded. The vulcanization accumulation time interval is determined, and the traction speed and vulcanization channel temperature parameters are obtained at each sampling time in the time interval. The vulcanization channel temperature parameters are the measured values ​​of the medium temperature at each temperature measuring point along the vulcanization channel. Starting from the cumulative start time, the traction speed at each sampling time is continuously integrated over time to obtain the real-time tracking micro-element position at any time in the vulcanization channel. Based on the coordinates of each temperature measuring point and the measured value of the medium temperature, a mapping relationship between the channel position and the medium temperature is established. The real-time tracking micro-element position is substituted into the mapping relationship and the estimated value of the medium temperature at the real-time tracking micro-element position is obtained by interpolation. Using the pre-calibrated frequency factor and vulcanization reaction activation energy of the batch of rubber compound as parameters, the estimated values ​​of the medium temperature obtained at each moment are used as reaction temperature parameters. The instantaneous vulcanization reaction rate at each moment is calculated according to the Arrhenius equation, and then the rate is accumulated by time integration within the vulcanization accumulation time interval to obtain the equivalent vulcanization effect accumulation value of the tracking micro-element, which is used as the engineering characterization parameter of the actual vulcanization degree of the tracking micro-element.

5. A digital management system for a rubber extrusion line according to claim 4, characterized in that: The cooling contraction compensation coefficient is calculated in the following way: The cooling channel temperature parameters, traction speed, and measured outer diameter of the product are obtained. The cooling channel temperature parameters are the real-time temperature gradient of the cooling medium along the length of the cooling channel. Taking the material properties of this batch of rubber as the object, a mapping relationship table between the cooling medium temperature gradient, traction speed and shrinkage rate is established in advance through offline experiments. The shrinkage correction factor is obtained by looking up the table or interpolating based on the current real-time temperature gradient value and traction speed. The difference between the measured outer diameter of the product and the preset target outer diameter is calculated and divided by the preset target outer diameter to obtain the relative value of the outer diameter deviation. The relative value of the outer diameter deviation is multiplied by the shrinkage correction factor to obtain the cooling shrinkage compensation coefficient.

6. A digital management system for a rubber extrusion line according to claim 5, characterized in that: The cascading sequence in the cascading adjudication execution module includes: First-level venting decision: The venting decision parameter is compared with the preset scorch threshold value of the batch of rubber as the decision condition. If the decision condition is met, the venting speed is obtained by multiplying the current traction speed by the preset venting acceleration coefficient and output as the speed command, and subsequent corrections are terminated; otherwise, the current traction speed is maintained as the speed command and subsequent multi-level selective corrections are entered. Subsequent multi-level selective correction: The feedforward correction parameter, feedback correction parameter, and limiting correction parameter are compared with the corresponding preset thresholds in sequence to determine whether the correction conditions are met. If the conditions are met, the correction parameter is converted into the corresponding speed correction amount and added to the current speed command; otherwise, the correction level is skipped.

7. A digital management system for a rubber extrusion line according to claim 6, characterized in that: The subsequent multi-level corrections are performed in the following order: Feedforward judgment advance correction: The deviation between the forming expansion prediction coefficient and the preset target expansion ratio is used as the judgment basis. When the deviation value exceeds the preset expansion threshold, the deviation value is multiplied by the preset feedforward gain coefficient to obtain the feedforward acceleration correction amount, which is then added to the acceleration setpoint of the current traction speed. Feedback judgment lag correction: The difference between the cumulative value of the equivalent vulcanization effect and the vulcanization target value of the process standard is used as the vulcanization deviation. When the absolute value of the deviation exceeds the preset vulcanization deviation threshold, the speed fine-tuning direction is determined according to the sign of the deviation, and the speed fine-tuning amplitude is determined by proportional-integral calculation based on the amplitude of the deviation. The speed fine-tuning amount is obtained by combining the direction and the amplitude and superimposed on the current speed command. Limiting judgment boundary constraint correction: When the cooling contraction compensation coefficient is outside the preset effective range, the coefficient is added to the current speed command as a multiplication factor.

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