Vulcanizing pressure control method and system of vulcanizing machine

Abstract

The invention relates to the technical field of vulcanization pressure control, in particular to a vulcanization pressure control method and system for a vulcanizing machine, and the method comprises the steps: determining a pressure response index by analyzing the cross correlation between all mixing proportion data and all pressure data in each time period and combining the confusion degree of all pressure data in a frequency domain; analyzing the average level difference between all the dynamic response indexes and the pressure response indexes in all the time periods, and integrating all mixing proportion data, all pressure data and all temperature data within a preset duration before the current moment to determine the pressure compensation urgency degree, correcting the proportion coefficient at the current moment, and obtaining the pressure compensation urgency degree. And controlling the pressure of the vulcanizing machine at the current moment. According to the method, the problem of prediction failure of a traditional linear extrapolation model in a continuous change scene is solved, and the timeliness and accuracy of pressure compensation are improved.

Description

Technical Field

[0001] This application relates to the technical field of vulcanization pressure control, and particularly to a vulcanization pressure control method and system for a vulcanizer. Background Art

[0002] The vulcanization pressure control of a vulcanizer is a core technology in the rubber industry to ensure product quality. During the vulcanization process, pressure directly affects the crosslinking density of rubber molecular chains and the physical properties of products. In vulcanization pressure control, the real-time fluctuation of the mixing ratio of natural rubber and synthetic rubber will significantly change the rheological properties of the rubber compound, resulting in the failure of the static compression modulus parameter on which the traditional pressure setting model depends, and causing the pressure-deformation relationship curve to deviate from the preset trajectory.

[0003] Existing solutions mainly perform feedback correction by integrating an on-line rheometer. However, it is difficult for the rheometer to detect and respond to the rapid change of the mixing ratio in a timely manner, resulting in a lag in pressure control compensation. The existing model only performs linear extrapolation correction based on the rheological data at discrete time points and cannot accurately fit the non-linear modulus response when the mixing ratio changes continuously, making it difficult to accurately characterize the time-varying characteristics of the modulus parameter under non-steady-state heat transfer conditions, exacerbating the lag of pressure compensation and reducing the pressure control accuracy. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a vulcanization pressure control method and system for a vulcanizer, and the specific technical solutions adopted are as follows: In the first aspect, an embodiment of this application provides a vulcanization pressure control method for a vulcanizer, and the method includes the following steps: Collect the mixing ratio, pressure and temperature data of the vulcanizer in real time; Divide the preset time period before the current moment into multiple time periods, and determine the pressure index of the vulcanizer in each time period by analyzing the cross-correlation between all the mixing ratio data and all the pressure data in each time period, and determine the pressure response index of the vulcanizer in each time period in combination with the degree of chaos of all the pressure data in the frequency domain; Predict the dynamic response index of the vulcanizer in a preset number of time periods after the current moment by analyzing the trend of the pressure response index in all the time periods before the current moment, analyze the difference in the average level between all the dynamic response indexes and the pressure response index in all the time periods, and determine the pressure deviation at the current moment; comprehensively determine the pressure expectation at the current moment based on all the mixing ratio data, all the pressure data and all the temperature data within the preset time period before the current moment, and determine the urgency of pressure compensation of the vulcanizer at the current moment in combination with the pressure deviation; Based on the urgency of pressure compensation, correct the proportional coefficient at the current moment to control the pressure of the vulcanizer at the current moment.

[0005] Preferably, the method for determining the pressure index of the vulcanizer in each time period is as follows: Taking all the mixing ratio data and all the pressure data in each time period as the input of the cross-correlation algorithm, outputting the maximum cross-correlation value and its corresponding lag time, and taking the ratio of the maximum cross-correlation value to the lag time as the pressure index of the vulcanizer in each time period.

[0006] Preferably, the method for determining the pressure response index of the vulcanizer in each time period is as follows: Converting all the pressure data in each time period to the frequency domain to obtain a frequency-domain signal, performing modal decomposition on the frequency-domain signal, calculating the energy entropy of each of the first preset number of modal components arranged in descending order of frequency among all the modal components, and taking the mean value of the preset number of energy entropies as the pressure chaos degree of the vulcanizer in each time period; Taking the result of positively fusing the pressure index and the pressure chaos degree of the vulcanizer in each time period as the pressure response index of the vulcanizer in each time period.

[0007] Preferably, the process of predicting the dynamic response index of the vulcanizer in a preset number of time periods after the current moment is as follows: Taking the pressure response indexes of the vulcanizer in all time periods within a preset time duration before the current moment as the input of the time series prediction algorithm, and outputting the pressure response indexes of each of the preset number of time periods after the current moment, denoted as the dynamic response index.

[0008] Preferably, the pressure deviation degree at the current moment is the ratio of the mean value of the dynamic response indexes of a preset number of time periods after the current moment to the mean value of the pressure response indexes of all time periods before the current moment.

[0009] Preferably, the method for determining the pressure expectation at the current moment is as follows: Taking all the mixing ratio data, all the pressure data, and all the temperature data within a preset time duration before the current moment as the input of the kernel method, and taking the output expectation as the pressure expectation at the current moment.

[0010] Preferably, the expression for the pressure compensation urgency of the vulcanizer at the current moment is: ; where represents the pressure compensation urgency of the vulcanizer at the current moment; represents the pressure deviation degree at the current moment; represents the pressure expectation at the current moment.

[0011] Preferably, the modification of the proportional coefficient at the current moment includes: The expression for the proportional coefficient correction value at the current moment is: ; where represents the preset proportional coefficient; It represents the urgency of pressure compensation of the vulcanizer at the current moment; norm( ) represents the normalization function.

[0012] Preferably, the control of the pressure of the vulcanizer at the current moment includes: Taking the deviation between the pressure data of the vulcanizer at the current moment and the preset pressure value as the input of the PID controller, where the correction value of the proportional coefficient at the current moment is used as the current proportional coefficient of the PID controller, and outputting a pressure control signal to control the pressure of the vulcanizer at the current moment.

[0013] In a second aspect, an embodiment of the present application further provides a vulcanization pressure control system for a vulcanizer, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the vulcanization pressure control method for a vulcanizer described in any one of the above are implemented.

[0014] The present application has at least the following beneficial effects: In view of the problem that the traditional static compression modulus parameter fails due to the real-time fluctuation of the mixing ratio, resulting in the deviation of the pressure change from the preset trajectory, the present application uses cross-correlation analysis to analyze the intensity and response delay of the change in the mixing ratio on the pressure, constructs a pressure response index, which helps to reduce the problem of pressure compensation lag caused by the fluctuation of the mixing ratio, accurately characterize the dynamic relationship between the mixing ratio and the pressure, and improve the timeliness of pressure compensation and the accuracy of pressure control; further, in view of the problem that the rapid change of the mixing ratio causes non-linear time-varying coupling and the traditional linear extrapolation correction method cannot accurately model, the present application uses the autoregressive integrated smoothing algorithm to quantify the stability of pressure control, combines the Gaussian process regression to reflect the pressure compensation demand, constructs a pressure compensation urgency, solves the problem of prediction failure of the traditional linear extrapolation model in the continuous change scenario, and further improves the timeliness and accuracy of pressure control; further, the present application dynamically adjusts the proportional coefficient based on the pressure compensation urgency, so that when the pressure compensation demand increases, the proportional coefficient increases accordingly, thereby increasing the rate of response to errors and effectively improving the timeliness and accuracy of pressure compensation. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1The flowchart of steps of a vulcanization pressure control method for a vulcanizer provided by an embodiment of the present application; Figure 2 The schematic diagram of the pressure compensation urgency extraction process provided by an embodiment of the present application. Detailed implementation manners

[0017] In order to further elaborate on the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following combines the accompanying drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of a vulcanization pressure control method and system according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs.

[0019] The following specifically describes the specific solutions of a vulcanization pressure control method and system provided by the present application with reference to the accompanying drawings.

[0020] Please refer to Figure 1 , which shows the flowchart of steps of a vulcanization pressure control method for a vulcanizer provided by an embodiment of the present application. The method includes the following steps: Step S1: Real-time collect the mixing ratio, pressure and temperature data of the vulcanizer.

[0021] Embed a ring capacitance probe, a high-frequency pressure sensor and a temperature sensor on the surface of the vulcanizer to collect the mixing ratio data of natural rubber and synthetic rubber, the pressure and temperature data of the vulcanization cavity in real time at a frequency f; further, in order to eliminate the influence of data dimensions on subsequent analysis, all the collected data is normalized. In this embodiment, the z-score normalization method is used to normalize the data. In actual application, as other implementation manners, the implementer can also use the maximum-minimum normalization method to normalize the data. Regarding the selection of the normalization method, this embodiment does not make special restrictions.

[0022] It should be supplemented that the specific method for obtaining the mixing ratio data is: through the rubber compound dielectric constant formula , inversely deduce the proportion x of natural rubber, where is the dielectric constant of natural rubber, with a value of 2.9, is the dielectric constant of synthetic rubber. The dielectric constant of synthetic rubber can be queried through the production formula or material database. For example, the dielectric constant of styrene-butadiene rubber is 2.6. The proportion of natural rubber obtained by inverse deduction is used as the mixing ratio data.

[0023] In addition, it should be understood that the value of the data acquisition frequency f is set artificially. In this embodiment, the value of the data acquisition frequency f is 10 Hz. The implementer can also set it according to the specific situation by himself / herself, and this embodiment does not make special restrictions.

[0024] Among them, the z-score normalization method is a well-known technology, and its specific principle will not be elaborated here.

[0025] The mixing ratio data is used to characterize the real-time fluctuation characteristics of the rubber compound composition, the pressure data is used to analyze the deformation response lag effect during the vulcanization process, and the temperature data is used to correct the influence of the pressure-temperature coupling effect on the modulus calculation. The three work together to support the optimization of pressure control in the scenario of sudden change in the mixing ratio.

[0026] Step S2: Divide the preset time period before the current moment into multiple time segments. By analyzing the cross-correlation between all the mixing ratio data and all the pressure data within each time segment, determine the pressure index of the vulcanizer within each time segment, and combine the degree of chaos of all the pressure data in the frequency domain to determine the pressure response index of the vulcanizer within each time segment.

[0027] Since the real-time fluctuation of the mixing ratio of natural rubber and synthetic rubber will significantly change the rheological properties of the rubber compound, resulting in the failure of the static compression modulus parameters on which the traditional vulcanization pressure control model depends, causing the pressure-deformation relationship curve to deviate from the preset trajectory, leading to the mismatch between the key parameters of the pressure control model and the actual rubber compound properties, triggering parameter failure, and further causing problems such as lag in vulcanization pressure compensation and decline in product uniformity.

[0028] Therefore, based on the above analysis, divide the preset time period before the current moment into multiple time segments. By analyzing the cross-correlation between all the mixing ratio data and all the pressure data within each time segment, determine the pressure index of the vulcanizer within each time segment, and combine the degree of chaos of all the pressure data in the frequency domain to determine the pressure response index of the vulcanizer within each time segment. The specific process is as follows: (1) In this embodiment, the preset time period before the current moment is divided into W time segments. Among them, the values of the preset time period and W are both set artificially. In this embodiment, the value of the preset time period is 30 min, and the value of W is 30, that is, the length of each time segment is 1 min. The implementer can also set it according to the specific situation by himself / herself, and this embodiment does not make special restrictions.

[0029] (2) Further, in this embodiment, by analyzing the cross-correlation between all the mixing ratio data and all the pressure data within each time segment, determine the pressure index of the vulcanizer within each time segment, specifically: In this embodiment, all the mixing ratio data and all the pressure data within each time period are used as the input of the cross-correlation algorithm, and the maximum cross-correlation value and its corresponding lag time are output. The ratio of the maximum cross-correlation value to the lag time is used as the pressure index of the vulcanizer within each time period to characterize the correlation degree between the mixing ratio and the pressure index.

[0030] It can be understood from the pressure index of the vulcanizer within each time period that the maximum cross-correlation value reflects the correlation strength of the fluctuations between the mixing ratio data and the pressure data, and the lag time reflects the dynamic lag effect between the mixing ratio and the pressure data. The larger the maximum cross-correlation value, the stronger the correlation degree between the mixing ratio and the pressure data. The smaller the lag time, the faster the pressure response, and the larger the corresponding pressure index, indicating the greater the correlation strength between the mixing ratio and the pressure data. On the contrary, if the maximum cross-correlation value is smaller and the lag time is larger, it indicates that the pressure response is more lagged, and the corresponding pressure index is smaller, indicating the smaller the correlation strength between the mixing ratio and the pressure data.

[0031] Among them, the cross-correlation algorithm is a well-known technology, and the specific process of using the cross-correlation algorithm to obtain the maximum cross-correlation value and its corresponding lag time will not be elaborated here.

[0032] (3) Further, based on the pressure index of the vulcanizer within each time period and combined with the degree of chaos of all the pressure data in the frequency domain, this embodiment determines the pressure response index of the vulcanizer within each time period, specifically: In this embodiment, all the pressure data within each time period are transformed into the frequency domain to obtain a frequency domain signal. The frequency domain signal is subjected to modal decomposition, and the energy entropy of each of the first preset number of modal components arranged in descending order of frequency among all the modal components is calculated. The mean value of the preset number of energy entropies is used as the pressure chaos degree of the vulcanizer within each time period to characterize the non-stationarity of the rubber compound compression modulus. If the pressure chaos degree is larger, it means that the energy entropy of each modal component is higher, indicating that the rheological characteristics are more complex, that is, the pressure control difficulty is greater; on the contrary, if the pressure chaos degree is smaller, it means that the energy entropy of each modal component is lower, indicating that the rheological characteristics are more single, that is, the pressure control difficulty is smaller.

[0033] It should be noted that there are many methods to transform a time domain signal into a frequency domain signal. In this embodiment, the fast Fourier transform is used to transform the time domain signal into the frequency domain. In the actual application process, the implementer can also use other methods such as wavelet transform. Regarding the selection of the method for transforming the time domain signal into the frequency domain signal, this embodiment does not make special restrictions.

[0034] Among them, the fast Fourier transform is a well-known technology, and its specific principle will not be elaborated here.

[0035] In addition, it should be understood that there are many common modal decomposition algorithms. In this embodiment, the empirical mode decomposition algorithm is used to decompose the frequency-domain signal. In actual application processes, as other implementation manners, implementers can also use other modal decomposition algorithms such as variational mode decomposition. Regarding the selection of modal decomposition algorithms, no special restrictions are made in this embodiment.

[0036] Among them, empirical mode decomposition is a well-known technology, and its specific principle will not be elaborated here.

[0037] Furthermore, in this embodiment, the result of the positive fusion of the pressure index and the pressure chaos degree of the vulcanizer in each time period is used as the pressure response index of the vulcanizer in each time period, which reflects the difficulty of vulcanization pressure control. If the pressure response index is larger, it indicates that the marked mixing ratio is more unstable, that is, the pressure chaos degree is larger, and the response of the pressure to the change of the mixing ratio is faster, that is, the pressure index is larger, and the deviation of the pressure control from the steady-state characteristic is more significant, and the difficulty of vulcanization pressure control is greater; on the contrary, if the pressure response index is smaller, it indicates that the marked mixing ratio is more stable, that is, the pressure chaos degree is smaller, and the response of the pressure to the change of the mixing ratio is more lagged, that is, the pressure index is smaller, and the deviation of the pressure control from the steady-state characteristic is less significant, and the difficulty of vulcanization pressure control is smaller.

[0038] It should be understood that positive fusion means combining two or more indicators through addition, multiplication or other methods in order to obtain a comprehensive indicator, so as to more comprehensively and accurately evaluate a certain phenomenon or problem. This fusion method is not limited to simple arithmetic operations, and can also include more complex statistical models and analysis methods. Implementers can choose according to specific situations, and no special restrictions are made in this embodiment.

[0039] Preferably, in this embodiment, the product of the pressure index and the pressure chaos degree of the vulcanizer in each time period is used as the pressure response index of the vulcanizer in each time period.

[0040] So far, by analyzing the cross-correlation between the mixing ratio and the pressure, as well as the frequency-domain characteristics of the pressure data, the pressure response index of the vulcanizer is obtained, which helps to reduce the problem of pressure compensation lag caused by the fluctuation of the mixing ratio, accurately characterize the dynamic relationship between the mixing ratio and the pressure, and improve the accuracy of pressure control.

[0041] Step S3: By analyzing the trend of the pressure response indexes of all time periods before the current moment, predict the dynamic response indexes of the vulcanizer in a preset number of time periods after the current moment, analyze the difference in the average level between all the dynamic response indexes and the pressure response indexes of all time periods, and determine the pressure deviation degree at the current moment; comprehensively determine all the mixing ratio data, all the pressure data and all the temperature data within a preset duration before the current moment, determine the pressure expectation at the current moment, and combine the pressure deviation degree to determine the urgency of pressure compensation of the vulcanizer at the current moment.

[0042] In the actual working conditions of the vulcanizer, the vulcanization pressure control is significantly affected by the dynamic coupling of multiple physical fields. The real-time fluctuation of the mixing ratio changes the entanglement degree and cross-linking activity of the rubber molecular chains, triggering the nonlinear time-variation of the rheological properties of the rubber compound, such as viscoelasticity, etc. At the same time, the temperature gradient distribution in the vulcanization cavity of the vulcanizer leads to the reconstruction of the flow resistance field of the rubber compound, and the non-uniformity of the pressure distribution caused by the superposition of the die deformation. The combined action of the three makes the relationship curve between pressure and deformation show time-varying hysteresis characteristics. When the proportion of natural rubber suddenly increases, the high elastic entropy of natural rubber competes with the viscous dissipation characteristics of synthetic rubber, resulting in the drift of the compression modulus parameter during the vulcanization cycle. The theoretical pressure setting value calculated by the traditional static model based on fixed modulus parameters is mismatched with the actual dynamic rheological process, ultimately resulting in a phase lag in pressure compensation.

[0043] Therefore, in the scenario of dynamic control of vulcanization pressure, in view of the problem of sudden change in the rheological properties of the rubber compound caused by random disturbance of the mixing ratio, this embodiment determines the pressure deviation degree at the current moment by analyzing the trend of the pressure response index in all time periods before the current moment and analyzing the difference in the average level between all the dynamic response indexes and the pressure response indexes in all time periods. By comprehensively considering all the mixing ratio data, all the pressure data, and all the temperature data within a preset time period before the current moment, and combining the pressure deviation degree, this embodiment determines the urgency of pressure compensation of the vulcanizer at the current moment to improve the timeliness and accuracy of pressure compensation. The specific process is as follows: (1) This embodiment predicts the dynamic response index of the vulcanizer within a preset number of time periods after the current moment by analyzing the trend of the pressure response index in all time periods before the current moment, specifically: In this embodiment, the pressure response index of the vulcanizer in all time periods within a preset time period before the current moment is used as the input of the time series prediction algorithm, and the pressure response index of each of the preset number of time periods after the current moment is output, denoted as the dynamic response index.

[0044] It should be noted that there are many commonly used time series prediction algorithms. In this embodiment, the autoregressive integrated moving average algorithm is used to predict the dynamic response index of the vulcanizer within a preset number of time periods after the current moment. In actual application processes, as other implementation manners, implementers can also use other time series prediction methods such as the exponential smoothing method. Regarding the selection of the time series decomposition algorithm, this embodiment does not make special restrictions.

[0045] Among them, the autoregressive integrated moving average algorithm is a well-known technology, and its specific principle will not be elaborated here.

[0046] It should be added that the value of the preset number is set manually. In this embodiment, the value of the preset number is 3. Implementers can also set it according to specific situations. This embodiment does not make special restrictions.

[0047] (2) Further, in this embodiment, the pressure deviation at the current moment is determined by analyzing the ratio of the average level between all the dynamic response indices and the pressure response indices of all time periods, specifically as follows: In this embodiment, the difference between the mean of the dynamic response indices of a preset number of time periods after the current moment and the mean of the pressure response indices of all time periods before the current moment is taken as the pressure deviation at the current moment, which is used to characterize the risk of pressure response instability caused by sudden changes in the mixing ratio. The larger the pressure deviation, the greater the difference between the predicted dynamic response index and the historical pressure response index, and the greater the risk of pressure response instability caused by sudden changes in the mixing ratio. On the contrary, the smaller the pressure deviation, the smaller the difference between the predicted dynamic response index and the historical pressure response index, and the smaller the risk of pressure response instability caused by sudden changes in the mixing ratio.

[0048] It should be noted that the value of the preset number is set artificially. In this embodiment, the value of the preset number is 3. In actual application, the implementer can also set it according to the specific situation, and this embodiment does not make special restrictions.

[0049] (3) Further, in this embodiment, the pressure expectation at the current moment is determined by comprehensively considering all the mixing ratio data, all the pressure data, and all the temperature data within a preset duration before the current moment, specifically: In this embodiment, all the mixing ratio data, all the pressure data, and all the temperature data within a preset duration before the current moment are used as the input of the kernel method, and the output expectation is used as the pressure expectation at the current moment.

[0050] It should be noted that there are many common kernel methods. In this embodiment, the radial basis function of Gaussian process regression is used to establish the non - linear mapping relationship between the pressure data, the mixing ratio data, and the temperature data, and the output expectation represents the optimal estimate of the pressure compensation amount. In actual application, as other implementation methods, the implementer can also use other kernel methods. Regarding the selection of the kernel method, this embodiment does not make special restrictions.

[0051] Among them, the radial basis function of Gaussian process regression is a well - known technology, and its specific principle will not be elaborated here.

[0052] (4) Further, in this embodiment, based on the pressure expectation at the current moment and in combination with the pressure deviation, the urgency of pressure compensation for the vulcanizer at the current moment is determined, specifically: As an implementation method, in this embodiment, the urgency of pressure compensation for the vulcanizer at the current moment The expression is: ; in the formula, represents the pressure deviation at the current moment; Represents the pressure expectation at the current moment.

[0053] Based on the urgency of pressure compensation for the vulcanizer at the current moment, it can be understood that the ratio of the mean value of the dynamic response index to the mean value of the pressure response index quantifies the short-term trend change of the pressure response index. By using the autoregressive integrated smoothing algorithm to predict the future pressure control complexity and judge the stable state of pressure control, when the pressure deviation degree is closer to 1, it indicates that the future pressure response is more consistent with the historical one, and the pressure compensation requirement is lower; the pressure expectation captures the coupling effect of multi-source signals through non-linear modeling, and thus maps to the pressure compensation requirement. The pressure expectation The smaller it is, the smaller the deviation between the pressure control parameters and the actual demand under the current working conditions, the less urgent the compensation requirement, and the smaller the finally obtained pressure compensation urgency, indicating that the current demand for pressure compensation is lower. On the contrary, when the pressure deviation degree differs more from 1, it indicates that the future pressure response is more inconsistent with the historical one, and the pressure compensation requirement is higher; the pressure expectation The larger it is, the larger the deviation between the pressure control parameters and the actual demand under the current working conditions, the more urgent the compensation requirement, and the larger the finally obtained pressure compensation urgency, indicating that there are multiple relaxation state overlaps in the flow of the rubber compound in the mold cavity, resulting in intensified pressure oscillation and significant response lag, leading to a sharp increase in the instability risk of the vulcanization pressure deviating from the process set value, and the higher the demand for pressure compensation.

[0054] Preferably, the schematic diagram of the process for extracting the pressure compensation urgency provided in this embodiment is as Figure 2 shown.

[0055] So far, through the difference between the predicted mean value of the dynamic response index and the mean value of the historical pressure response index, and by comprehensively considering the mixing ratio data, pressure data and temperature data, the pressure compensation urgency has been obtained, the difference between the dynamic response index and the pressure response index has been predicted, which intuitively reflects the instability risk caused by the sudden change of the mixing ratio, and at the same time accurately estimates the pressure compensation requirement, improving the accuracy of pressure control.

[0056] Step S4: Based on the pressure compensation urgency, correct the proportional coefficient at the current moment to control the pressure of the vulcanizer at the current moment.

[0057] In the vulcanization pressure control system, the pressure compensation urgency B, as the core parameter of dynamic compensation, directly drives the parameter adjustment of the control system and the optimization of hydraulic output by real-time predicting and optimizing the vulcanization pressure compensation amount, thus significantly improving the real-time performance and accuracy of vulcanization pressure control.

[0058] In this embodiment, the PID control algorithm is used to achieve the regulation of the vulcanization pressure. Specifically, the initial proportional, integral and differential coefficients of the PID algorithm 、 and The value ranges of are respectively to prevent slow response or system oscillation; is to balance the relationship between eliminating steady-state error and avoiding integral saturation; is to suppress overshoot and avoid noise amplification. Specifically, in this embodiment, , and take specific values of 5, 0.5, and 0.1 respectively.

[0059] Since the dynamic change of the mixing ratio will cause the non-linear response and hysteresis effect of the vulcanization pressure control, the proportional coefficient of the PID controller is corrected in real time according to the pressure compensation urgency B. The specific correction formula is: The correction value of the proportional coefficient at the current moment is expressed as: ; in the formula, represents the preset proportional coefficient; represents the pressure compensation urgency of the vulcanizer at the current moment; norm( ) represents the normalization function.

[0060] It should be added that in this embodiment, the value of Kp is as described above, which is 5. Implementers can also set it by themselves according to specific situations, and this embodiment does not make special restrictions.

[0061] Since the pressure compensation urgency B reflects the complexity and urgency of the vulcanization pressure control in the vulcanization process, when B increases, it means that the dynamic disturbance of the vulcanization pressure control system is stronger and the pressure compensation requirement is higher. At this time, Kp is dynamically increased to accelerate the control speed, significantly improving the real-time performance and accuracy of the vulcanization pressure control, and effectively solving the problems of vulcanization pressure compensation lag and insufficient control accuracy caused by the mixing ratio fluctuation in the prior art.

[0062] Furthermore, the deviation between the pressure data of the vulcanizer at the current moment and the preset pressure value is used as the input of the PID controller. Among them, the correction value of the proportional coefficient at the current moment is used as the current proportional coefficient of the PID controller, and a pressure control signal is output to control the pressure of the vulcanizer at the current moment.

[0063] Among them, the value of the preset pressure value is set manually. In this embodiment, the value of the preset pressure value is 100 MPa. In actual application, implementers can also set it by themselves according to specific situations, and this embodiment does not make special restrictions.

[0064] Based on the same inventive concept as the above method, an embodiment of the present application further provides a vulcanization pressure control system for a vulcanizer, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above vulcanization pressure control methods for a vulcanizer are implemented.

[0065] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. In addition, the above specific embodiments of the present specification have been described. Moreover, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0066] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

[0067] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vulcanization pressure control method for a vulcanizer, characterized in that, The method includes the following steps: Collect the mixing ratio, pressure, and temperature data of the vulcanizer in real time; Divide the preset time period before the current moment into multiple time intervals. By analyzing the cross-correlation between all the mixing ratio data and all the pressure data within each time interval, determine the pressure index of the vulcanizer within each time interval, and combine the degree of chaos of all the pressure data in the frequency domain to determine the pressure response index of the vulcanizer within each time interval; By analyzing the trend of the pressure response indices of all the time intervals before the current moment, predict the dynamic response indices of the vulcanizer within a preset number of time intervals after the current moment. Analyze the difference in the average level between all the dynamic response indices and the pressure response indices of all the time intervals to determine the pressure deviation at the current moment; Synthesize all the mixing ratio data, all the pressure data, and all the temperature data within the preset time period before the current moment to determine the pressure expectation at the current moment, and combine the pressure deviation to determine the urgency of pressure compensation for the vulcanizer at the current moment; Based on the urgency of pressure compensation, correct the proportionality coefficient at the current moment to control the pressure of the vulcanizer at the current moment.

2. The vulcanization pressure control method of a vulcanizer according to claim 1, characterized in that, The method for determining the pressure index of the vulcanizer within each time interval is as follows: Take all the mixing ratio data and all the pressure data within each time interval as the input of the cross-correlation algorithm, output the maximum cross-correlation value and its corresponding lag time, and take the ratio of the maximum cross-correlation value to the lag time as the pressure index of the vulcanizer within each time interval.

3. The vulcanization pressure control method of a vulcanizer according to claim 1, characterized in that, The method for determining the pressure response index of the vulcanizer within each time interval is as follows: Convert all the pressure data within each time interval to the frequency domain to obtain the frequency domain signal. Perform modal decomposition on the frequency domain signal, calculate the energy entropy of each of the first preset number of modal components arranged in descending order of frequency among all the modal components, and take the mean of the preset number of energy entropies as the pressure chaos degree of the vulcanizer within each time interval; Take the result of positively fusing the pressure index and the pressure chaos degree of the vulcanizer within each time interval as the pressure response index of the vulcanizer within each time interval.

4. A vulcanization pressure control method for a vulcanizer according to claim 1, characterized in that, The process of predicting the dynamic response indices of the vulcanizer within a preset number of time intervals after the current moment is as follows: Take the pressure response indices of the vulcanizer at all the time intervals within the preset time period before the current moment as the input of the time series prediction algorithm, and output the pressure response indices of each of the preset number of time intervals after the current moment, denoted as the dynamic response indices.

5. A vulcanization pressure control method for a vulcanizer according to claim 1, characterized in that, The pressure deviation at the current moment is the ratio of the mean of the dynamic response indices of a preset number of time intervals after the current moment to the mean of the pressure response indices of all the time intervals before the current moment.

6. The vulcanization pressure control method of a vulcanizer according to claim 1, characterized in that, The method for determining the pressure expectation at the current moment is as follows: Take all the mixing ratio data, all the pressure data, and all the temperature data within the preset time period before the current moment as the input of the kernel method, and take the output expectation as the pressure expectation at the current moment.

7. A vulcanization pressure control method for a vulcanizer according to claim 1, characterized in that, The expression for the urgency of pressure compensation of the vulcanizer at the current moment is as follows: ; In the formula, represents the urgency of pressure compensation of the vulcanizer at the current moment; represents the pressure deviation at the current moment; represents the pressure expectation at the current moment.

8. The vulcanization pressure control method of a vulcanizer according to claim 1, characterized in that, The correction of the proportionality coefficient at the current moment includes: Correction value of the proportionality coefficient at the current moment The expression is as follows: ; where represents the preset proportionality coefficient; represents the urgency of pressure compensation of the vulcanizer at the current moment; norm( ) represents the normalization function.

9. The vulcanization pressure control method of a vulcanizer according to claim 1, characterized in that The control of the pressure of the vulcanizer at the current moment includes: The deviation between the pressure data of the vulcanizer at the current moment and the preset pressure value is used as the input of the PID controller. Among them, the correction value of the proportionality coefficient at the current moment is used as the current proportionality coefficient of the PID controller, and a pressure control signal is output to control the pressure of the vulcanizer at the current moment.

10. A vulcanization pressure control system for a vulcanizer, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the vulcanization pressure control method of a vulcanizer according to any one of claims 1-9.

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