A vulcanizing pressure control method and system for a vulcanizing machine

Abstract

The present application relates to the technical field of vulcanization pressure control, and specifically to a vulcanization pressure control method and system for a vulcanizer, the method comprising: determining a pressure response index by analyzing the correlation between all mixing ratio data and all pressure data in each time period, and combining the degree of chaos of all pressure data in the frequency domain; analyzing the difference between the average levels of all the dynamic response indices and the pressure response indices of all time periods, and comprehensively considering all mixing ratio data, all pressure data, and all temperature data within a preset time period before the current moment, determining the urgency of pressure compensation, and correcting the proportional coefficient at the current moment to control the pressure of the vulcanizer at the current moment. The present application solves the problem of prediction failure of traditional linear extrapolation models in continuously changing scenarios, and improves the timeliness and accuracy of pressure compensation.

Description

Technical Field

[0001] The present application relates to the technical field of vulcanization pressure control, and in particular to a vulcanization pressure control method and system for a vulcanizing machine. Background Art

[0002] Vulcanization pressure control of a vulcanizer is a core technology for ensuring product quality in the rubber industry. During the vulcanization process, pressure directly affects the cross-linking density of the rubber molecular chain and the physical properties of the product. Real-time fluctuations in the mixing ratio of natural rubber and synthetic rubber during vulcanization pressure control will significantly change the rheological properties of the rubber, causing the static compression modulus parameters that the traditional pressure setting model relies on to fail, and causing the pressure-deformation relationship curve to deviate from the preset trajectory.

[0003] Existing solutions mainly use integrated online rheometers for feedback correction. However, rheometer detection is difficult to respond to rapid changes in the mixing ratio in a timely manner, resulting in a lag in pressure control compensation. The existing model is only based on linear extrapolation correction of rheological data at discrete time points, and cannot accurately fit the nonlinear modulus response when the mixing ratio changes continuously. As a result, the time-varying characteristics of the modulus parameters under non-steady-state heat transfer conditions are difficult to accurately characterize, which aggravates the lag of pressure compensation and reduces 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 vulcanizing pressure control method and system for a vulcanizing press. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for controlling the vulcanization pressure of a vulcanizer, the method comprising the following steps:

[0006] Real-time collection of mixing ratio, pressure and temperature data of the vulcanizer;

[0007] The preset time period before the current moment is divided into multiple time periods. The pressure index of the vulcanizer in each time period is determined by analyzing the cross-correlation between all mixing ratio data and all pressure data in each time period. The pressure response index of the vulcanizer in each time period is determined by combining the degree of chaos of all pressure data in the frequency domain.

[0008] By analyzing the trend of the pressure response index of all time periods before the current moment, predicting the dynamic response index of the vulcanizer within a preset number of time periods after the current moment, analyzing the difference between all the dynamic response indices and the average level of the pressure response indices of all time periods, the pressure deviation at the current moment is determined; combining all the mixing ratio data, all the pressure data, and all the temperature data within a preset time period before the current moment, the pressure expectation at the current moment is determined, and combined with the pressure deviation, the urgency of pressure compensation of the vulcanizer at the current moment is determined;

[0009] Based on the pressure compensation urgency, the proportional coefficient at the current moment is corrected to control the pressure of the vulcanizer at the current moment.

[0010] Preferably, the method for determining the pressure index of the vulcanizer in each time period is:

[0011] All mixing ratio data and all pressure data in each time period are used as 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 in each time period.

[0012] Preferably, the method for determining the pressure response index of the vulcanizer in each time period is:

[0013] Convert all pressure data in each time period into the frequency domain to obtain a 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 among all modal components arranged in descending order of frequency, and use the average of the preset number of energy entropies as the pressure chaos degree of the vulcanizer in each time period;

[0014] The result of the positive fusion of the pressure index of the vulcanizer in each time period and the pressure chaos degree is used as the pressure response index of the vulcanizer in each time period.

[0015] Preferably, the process of predicting the dynamic response index of the vulcanizer within a preset number of time periods after the current moment is:

[0016] 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, which is recorded as the dynamic response index.

[0017] Preferably, the pressure deviation at the current moment is the ratio of the average value of the dynamic response index of a preset number of time periods after the current moment to the average value of the pressure response index of all time periods before the current moment.

[0018] Preferably, the method for determining the pressure expectation at the current moment is:

[0019] All mixing ratio data, all pressure data, and all temperature data within a preset time period before the current moment are used as inputs of the kernel method, and the output expectation is used as the pressure expectation at the current moment.

[0020] Preferably, the expression of the pressure compensation urgency of the vulcanizer at the current moment is: Where, Indicates the urgency of pressure compensation of the curing machine at the current moment; Indicates the pressure deviation at the current moment; Indicates the pressure expectation at the current moment.

[0021] Preferably, the correction of the current proportional coefficient includes:

[0022] Correction value of the proportional coefficient at the current moment The expression is: Where, Indicates the preset scale factor; Indicates the urgency of pressure compensation of the vulcanizer at the current moment; norm( ) represents the normalization function.

[0023] Preferably, the controlling of the pressure of the vulcanizing machine at the current moment includes:

[0024] 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, wherein the proportional coefficient correction value 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.

[0025] In a second aspect, an embodiment of the present application further provides 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. 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.

[0026] This application has at least the following beneficial effects:

[0027] This application addresses the problem that traditional static compression modulus parameters fail due to real-time fluctuations in the mixing ratio, resulting in pressure changes deviating from the preset trajectory. Cross-correlation is used to analyze the intensity and response delay of the impact of mixing ratio changes on pressure, and a pressure response index is constructed. This helps to reduce the problem of pressure compensation lag caused by mixing ratio fluctuations, accurately characterizes the dynamic relationship between mixing ratio and pressure, and improves the timeliness of pressure compensation and the accuracy of pressure control. Furthermore, this application addresses the problem that rapid changes in mixing ratio cause nonlinear time-varying coupling, which traditional linear extrapolation correction methods cannot accurately model. An autoregressive integral smoothing algorithm is used to quantify the stability of pressure control, combined with Gaussian process regression to reflect the pressure compensation demand, and a pressure compensation urgency is constructed to solve the problem of prediction failure of traditional linear extrapolation models in continuously changing scenarios, thereby improving the timeliness and accuracy of pressure control. Furthermore, this 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0029] Figure 1 A flowchart of a method for controlling the vulcanizing pressure of a vulcanizing machine provided in one embodiment of the present application;

[0030] Figure 2 A schematic diagram of the pressure compensation urgency extraction process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0031] To further illustrate the technical means and effects employed by this application to achieve the intended invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the implementation, structure, features, and effects of a vulcanizing press vulcanizing pressure control method and system proposed in this application. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0032] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0033] The following describes in detail a specific scheme of a vulcanizing pressure control method and system for a vulcanizing machine provided by the present application with reference to the accompanying drawings.

[0034] See also Figure 1 , which shows a flow chart of a method for controlling the vulcanizing pressure of a vulcanizing machine provided by one embodiment of the present application, the method comprising the following steps:

[0035] Step S1: real-time acquisition of mixing ratio, pressure and temperature data of the vulcanizing machine.

[0036] An annular capacitance probe, a high-frequency pressure sensor, and a temperature sensor are embedded on the surface of the vulcanizer to collect the mixing ratio data of natural rubber and synthetic rubber, and the pressure and temperature data of the vulcanization chamber in real time at a frequency f. Furthermore, in order to eliminate the influence of the data dimension on subsequent analysis, all collected data are normalized. In this embodiment, the z-score normalization method is used to normalize the data. In actual application, as another implementation method, the implementer may also use the maximum and minimum value normalization method to normalize the data. This embodiment does not impose any special restrictions on the selection of the normalization method.

[0037] It is also noted that the specific method for obtaining the mixing ratio data is: using the rubber compound dielectric constant formula , reverse the natural rubber proportion x, where is the dielectric constant of natural rubber, which is 2.9. 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 reverse calculation is used as the mixing ratio data.

[0038] In addition, it should be understood that the value of the data acquisition frequency f is manually set. 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. This embodiment does not impose any special restrictions.

[0039] Among them, the z-score normalization method is a well-known technology, and its specific principle will not be described in detail.

[0040] Mixing ratio data is used to characterize the real-time fluctuation characteristics of the rubber composition, pressure data is used to analyze the hysteresis effect of deformation response during the vulcanization process, and temperature data is used to correct the influence of pressure-temperature coupling on modulus calculation. The three data work together to support the optimization of pressure control under the scenario of sudden change in mixing ratio.

[0041] Step S2: Divide the preset time before the current moment into multiple time periods, determine the pressure index of the vulcanizer in each time period by analyzing the correlation between all mixing ratio data and all 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 pressure data in the frequency domain.

[0042] Since the real-time fluctuation of the mixing ratio of natural rubber and synthetic rubber will significantly change the rheological properties of the rubber, the static compression modulus parameter relied on by the traditional vulcanization pressure control model will fail, causing the pressure-deformation relationship curve to deviate from the preset trajectory, resulting in a mismatch between the key parameters of the pressure control model and the actual rubber properties, causing parameter failure, and then causing problems such as vulcanization pressure compensation lag and decreased product uniformity.

[0043] Therefore, based on the above analysis, the preset time before the current moment is divided into multiple time periods. By analyzing the correlation between all mixing ratio data and all pressure data in each time period, the pressure index of the vulcanizer in each time period is determined. Combined with the degree of chaos of all pressure data in the frequency domain, the pressure response index of the vulcanizer in each time period is determined. The specific process is as follows:

[0044] (1) This embodiment divides the preset time before the current moment into W time periods, where the preset time period and the value of W are both manually set. In this embodiment, the preset time period is 30 minutes, and the value of W is 30, that is, the length of each time period is 1 minute. The implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0045] (2) Furthermore, this embodiment determines the pressure index of the vulcanizer in each time period by analyzing the correlation between all mixing ratio data and all pressure data in each time period, specifically:

[0046] In this embodiment, all mixing ratio data and all pressure data in each time period are used as inputs 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 in each time period, which is used to characterize the degree of correlation between the mixing ratio and the pressure index.

[0047] According to the pressure index of the vulcanizer in each time period, it can be understood that the maximum cross-correlation value reflects the correlation strength between the mixing ratio data and the pressure data fluctuation, 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 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, which indicates that the correlation strength between the mixing ratio and the pressure data is greater. Conversely, if the maximum cross-correlation value is smaller and the lag time is longer, the pressure response is more delayed and the corresponding pressure index is smaller, which indicates that the correlation strength between the mixing ratio and the pressure data is smaller.

[0048] The cross-correlation algorithm is a well-known technology, and the specific process of obtaining the maximum cross-correlation value and its corresponding lag time using the cross-correlation algorithm will not be described in detail.

[0049] (3) Furthermore, this embodiment determines the pressure response index of the vulcanizer in each time period based on the pressure index of the vulcanizer in each time period and the degree of chaos of all pressure data in the frequency domain, specifically:

[0050] In this embodiment, all pressure data in each time period are converted to the frequency domain to obtain a frequency domain signal, and the frequency domain signal is modally decomposed to calculate the energy entropy of each of the first preset number of modal components among all modal components arranged in descending order of frequency. The average of the preset number of energy entropies is used as the pressure chaos of the vulcanizer in each time period to characterize the non-stationarity of the compression modulus of the rubber compound. If the pressure chaos is greater, it means that the energy entropy of each modal component is higher, indicating that the rheological characteristics are more complex, that is, the greater the difficulty of pressure control; conversely, if the pressure chaos is smaller, it means that the energy entropy of each modal component is lower, indicating that the rheological characteristics are more simple, that is, the less difficult the pressure control is.

[0051] It should be noted that there are many methods for converting time domain signals into frequency domain signals. In this embodiment, fast Fourier transform is used to convert time domain signals into frequency domain. In actual application, implementers can also use other methods such as wavelet transform. Regarding the selection of the method for converting time domain signals into frequency domain signals, this embodiment does not impose any special restrictions.

[0052] Among them, fast Fourier transform is a well-known technology, and its specific principle is not repeated here.

[0053] In addition, it should be understood that there are many commonly used modal decomposition algorithms. In this embodiment, the empirical mode decomposition algorithm is used to decompose the frequency domain signal. In actual application, as other implementation methods, the implementer may also use other modal decomposition algorithms such as variational mode decomposition. Regarding the selection of modal decomposition algorithms, this embodiment does not impose any special restrictions.

[0054] Among them, empirical mode decomposition is a well-known technology, and its specific principles are not described in detail here.

[0055] Furthermore, this embodiment forwardly integrates the pressure index and pressure chaos of the vulcanizer in each time period as the pressure response index of the vulcanizer in each time period, reflecting the difficulty of vulcanization pressure control. If the pressure response index is larger, it indicates that the mixing ratio is more unstable, that is, the pressure chaos is greater, and the pressure responds more quickly to changes in the mixing ratio, that is, the larger the pressure index, the more significant the deviation of the pressure control from the steady-state characteristics, and the greater the difficulty of controlling the vulcanization pressure; conversely, if the pressure response index is smaller, it indicates that the mixing ratio is more stable, that is, the pressure chaos is smaller, and the pressure responds more laggingly to changes in the mixing ratio, that is, the smaller the pressure index, the less significant the deviation of the pressure control from the steady-state characteristics, and the less difficult the vulcanization pressure is to control.

[0056] It should be understood that forward fusion refers to combining two or more indicators through addition or multiplication to obtain a comprehensive indicator, thereby more comprehensively and accurately evaluating a 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 their specific circumstances and this embodiment does not impose any special restrictions.

[0057] Preferably, in this embodiment, the product of the pressure index of the vulcanizer in each time period and the pressure disorder degree is used as the pressure response index of the vulcanizer in each time period.

[0058] At this point, by analyzing the cross-correlation between mixing ratio and pressure, as well as the frequency domain characteristics of pressure data, the pressure response index of the vulcanizer was obtained. This helps to reduce the problem of pressure compensation lag caused by mixing ratio fluctuations, accurately characterizes the dynamic relationship between mixing ratio and pressure, and improves the accuracy of pressure control.

[0059] Step S3: By analyzing the trend of the pressure response index of all time periods before the current moment, predicting the dynamic response index of the vulcanizer within a preset number of time periods after the current moment, analyzing the difference between the average level of all the dynamic response indices and the pressure response indices of all time periods, and determining the pressure deviation at the current moment; comprehensively analyzing all mixing ratio data, all pressure data and all temperature data within the preset time period before the current moment, determining the pressure expectation at the current moment, and combining the pressure deviation to determine the urgency of pressure compensation of the vulcanizer at the current moment.

[0060] In the actual operation of a vulcanizer, vulcanization pressure control is significantly affected by the dynamic coupling of multiple physical fields. Real-time fluctuations in the mixing ratio alter the degree of entanglement and crosslinking activity of the rubber's molecular chains, causing nonlinear time-varying changes in the rubber's rheological properties, such as viscoelasticity. Simultaneously, the temperature gradient distribution within the vulcanizer's vulcanization chamber reshapes the rubber's flow resistance field, and combined with the non-uniform pressure distribution caused by mold deformation, these three factors combine to create a time-varying hysteresis characteristic in the pressure-deformation relationship curve. When the proportion of natural rubber increases suddenly, its high elastic entropy competes with the viscous dissipation properties of synthetic rubber, causing the compression modulus parameters to drift during the vulcanization cycle. The theoretical pressure setpoints calculated by traditional static models based on fixed modulus parameters do not match the actual dynamic rheological process, ultimately resulting in a phase lag in pressure compensation.

[0061] Therefore, in the dynamic control scenario of vulcanization pressure, this embodiment addresses the problem of sudden changes in the rheological properties of the rubber compound caused by random disturbances in the mixing ratio. By analyzing the trend of the pressure response index of all time periods before the current moment, and analyzing the difference between the average level of all the dynamic response indexes and the pressure response index of all time periods, the pressure deviation at the current moment is determined. All mixing ratio data, all pressure data, and all temperature data within a preset time period before the current moment are integrated, and combined with the pressure deviation, the urgency of pressure compensation of the vulcanizer at the current moment is determined to improve the timeliness and accuracy of pressure compensation. The specific process is as follows:

[0062] (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 of all time periods before the current moment, specifically:

[0063] 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, which is recorded as the dynamic response index.

[0064] It should be noted that there are many commonly used time series prediction algorithms. In this embodiment, the autoregressive integral sliding 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, as other implementation methods, the implementer may also adopt other time series prediction methods such as the exponential smoothing method. Regarding the selection of the time series decomposition algorithm, this embodiment does not impose any special restrictions.

[0065] Among them, the autoregressive integral sliding algorithm is a well-known technology, and its specific principle will not be repeated here.

[0066] It should be noted that the value of the preset number is manually set. In this embodiment, the value of the preset number is 3. The implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0067] (2) Furthermore, this embodiment determines the pressure deviation at the current moment by analyzing the ratio of all the dynamic response indices to the average level of the pressure response indices of all time periods, specifically:

[0068] In this embodiment, the difference between the average of the dynamic response index of a preset number of time periods after the current moment and the average of the pressure response index of all time periods before the current moment is used as the pressure deviation at the current moment, which is used to characterize the risk of pressure response instability caused by a sudden change 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 a sudden change in the mixing ratio. Conversely, 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 a sudden change in the mixing ratio.

[0069] It should be noted that the value of the preset number is set manually. In this embodiment, the value of the preset number is 3. In actual application, the implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0070] (3) Furthermore, this embodiment determines the pressure expectation at the current moment by integrating all mixing ratio data, all pressure data, and all temperature data within a preset time period before the current moment. Specifically:

[0071] In this embodiment, all mixing ratio data, all pressure data, and all temperature data within a preset time period before the current moment are used as inputs of the kernel method, and the output expectation is used as the pressure expectation at the current moment.

[0072] It should be noted that there are many commonly used kernel methods. In this embodiment, the radial basis function of Gaussian process regression is used to establish a nonlinear mapping relationship between pressure data, mixing ratio data and temperature data, and output the expected value, which is the optimal estimate of the pressure compensation amount. In actual application, as other implementation methods, the implementer may also adopt other kernel methods. Regarding the selection of kernel methods, this embodiment does not impose any special restrictions.

[0073] The radial basis function of Gaussian process regression is a well-known technology, and its specific principle will not be described in detail.

[0074] (4) Furthermore, this embodiment determines the urgency of pressure compensation of the vulcanizer at the current moment based on the pressure expectation at the current moment and in combination with the pressure deviation, specifically:

[0075] As an implementation method, in this embodiment, the pressure compensation urgency of the vulcanizer at the current moment is The expression is: Where, Indicates the pressure deviation at the current moment; Indicates the pressure expectation at the current moment.

[0076] According to the urgency of pressure compensation of the vulcanizer at the current moment, 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. The future pressure control complexity is predicted by the autoregressive integral smoothing algorithm to judge the stable state of the pressure control. The closer the pressure deviation is to 1, the more consistent the future and historical pressure responses are, and the lower the pressure compensation demand is. The pressure expectation captures the coupling effect of multi-source signals through nonlinear modeling, thereby mapping it to the pressure compensation demand. The pressure expectation The smaller the value, the smaller the deviation between the pressure control parameters under the current working conditions and the actual demand, the less urgent the compensation demand is, and the lower the urgency of the pressure compensation is, indicating that the current demand for pressure compensation is lower.

[0077] On the contrary, the greater the difference between the pressure deviation and 1, the more inconsistent the future pressure response is with the historical one, and the higher the pressure compensation demand is. The larger the value is, the greater the deviation between the pressure control parameters under the current working conditions and the actual demand is, the more urgent the compensation demand is, and the greater the urgency of the final pressure compensation is, indicating that the flow of the rubber in the mold cavity has multiple overlapping relaxation states, causing the pressure oscillation to intensify and the response lag to be significant, resulting in a sharp increase in the risk of instability of the vulcanization pressure deviating from the process set value, and a higher demand for pressure compensation.

[0078] Preferably, the schematic diagram of the pressure compensation urgency extraction process provided in this embodiment is as follows: Figure 2 shown.

[0079] At this point, the urgency of pressure compensation was obtained by calculating the difference between the predicted average dynamic response index and the historical average pressure response index, and combining the mixing ratio data, pressure data, and temperature data. The difference between the dynamic response index and the pressure response index was predicted, which intuitively reflected the instability risk caused by sudden changes in the mixing ratio. At the same time, the pressure compensation demand was accurately estimated, thereby improving the accuracy of pressure control.

[0080] Step S4: Based on the pressure compensation urgency, the proportional coefficient at the current moment is corrected to control the pressure of the vulcanizer at the current moment.

[0081] In the vulcanization pressure control system, pressure compensation urgency B serves as the core parameter of dynamic compensation. By real-time prediction and optimization of the vulcanization pressure compensation amount, it directly drives the control system parameter adjustment and hydraulic output optimization, thereby significantly improving the real-time performance and accuracy of vulcanization pressure control.

[0082] In this embodiment, the PID control algorithm is used to control the vulcanization pressure. Specifically, the initial proportional, integral and differential coefficients of the PID algorithm are 、 and The value ranges are: To prevent slow response or system oscillation; , to balance the relationship between eliminating steady-state error and avoiding integral saturation; , to suppress overshoot and avoid noise amplification. Specifically, in this embodiment, 、 and The specific values ​​are 5, 0.5 and 0.1 respectively.

[0083] Since the dynamic change of mixing ratio will lead to nonlinear response and hysteresis effect of 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 relationship is:

[0084] Correction value of the proportional coefficient at the current moment The expression is: Where, Indicates the preset scale factor; Indicates the urgency of pressure compensation of the vulcanizer at the current moment; norm( ) represents the normalization function.

[0085] It is additionally noted that the value of Kp in this embodiment is as described above, which is 5. The implementer may also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0086] Since the pressure compensation urgency B reflects the complexity and urgency of vulcanization pressure control during the vulcanization process, when B increases, it means that the dynamic disturbance of the vulcanization pressure control system is stronger and the pressure compensation demand is higher. At this time, Kp is dynamically increased to speed up the control speed, significantly improving the real-time performance and accuracy of vulcanization pressure control, and effectively solving the problems of vulcanization pressure compensation lag and insufficient control accuracy caused by mixing ratio fluctuations in the existing technology.

[0087] 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, wherein the proportional coefficient correction value 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.

[0088] The preset pressure value is set manually. In this embodiment, the preset pressure value is 100 MPa. In actual application, the implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0089] Based on the same inventive concept as the above method, an embodiment of the present application also provides 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. When the processor executes the computer program, the steps of any one of the above-mentioned vulcanization pressure control methods for a vulcanizer are implemented.

[0090] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0091] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0092] The above description is only a preferred embodiment of the present application and is 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 scope of protection of the present application.

Claims

1. A vulcanizing pressure control method for a vulcanizing machine, characterized in that: The method comprises the following steps: Real-time collection of mixing ratio, pressure and temperature data of the vulcanizer; The preset time period before the current moment is divided into multiple time periods, and the pressure index of the vulcanizer in each time period is determined by analyzing the cross-correlation between all mixing ratio data and all pressure data in each time period, and the pressure response index of the vulcanizer in each time period is determined in combination with the degree of chaos of all pressure data in the frequency domain; the method for determining the pressure response index of the vulcanizer in each time period is as follows: all pressure data in each time period is converted into the frequency domain to obtain a frequency domain signal, modal decomposition is performed on the frequency domain signal, and the energy entropy of each of the first preset number of modal components of all modal components arranged in descending order of frequency is calculated, and the average of the preset number of energy entropies is used as the pressure chaos degree of the vulcanizer in each time period; the result of forward fusion of the pressure index of the vulcanizer in each time period and the pressure chaos degree is used as the pressure response index of the vulcanizer in each time period; By analyzing the trend of the pressure response index of all time periods before the current moment, predicting the dynamic response index of the vulcanizer within a preset number of time periods after the current moment, and analyzing the difference between all the dynamic response indices and the average level of the pressure response indices of all time periods, the pressure deviation at the current moment is determined; combining all the mixing ratio data, all the pressure data, and all the temperature data within the preset time period before the current moment, the pressure expectation at the current moment is determined, and combined with the pressure deviation, the pressure compensation urgency of the vulcanizer at the current moment is determined; the expression of the pressure compensation urgency of the vulcanizer at the current moment is: Where, Indicates the urgency of pressure compensation of the curing machine at the current moment; Indicates the pressure deviation at the current moment, which is determined by the ratio of all dynamic response indices to the average level of pressure response indices over all time periods; Indicates the expectation of stress at the current moment; Based on the pressure compensation urgency, the proportional coefficient at the current moment is corrected to control the pressure of the vulcanizer at the current moment.

2. The vulcanizing pressure control method of a vulcanizing machine according to claim 1, characterized in that: The method for determining the pressure index of the vulcanizer in each time period is as follows: All mixing ratio data and all pressure data in each time period are used as 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 in each time period.

3. The vulcanizing pressure control method of a vulcanizing machine according to claim 1, characterized in that: The process of predicting the dynamic response index of the vulcanizer within a preset number of time periods after the current moment is as follows: 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, which is recorded as the dynamic response index.

4. The vulcanizing pressure control method of a vulcanizing machine according to claim 1, wherein: The pressure deviation at the current moment is the ratio of the average value of the dynamic response index of a preset number of time periods after the current moment to the average value of the pressure response index of all time periods before the current moment.

5. The vulcanizing pressure control method of a vulcanizing machine according to claim 1, wherein: The method for determining the pressure expectation at the current moment is: All mixing ratio data, all pressure data, and all temperature data within a preset time period before the current moment are used as inputs of the kernel method, and the output expectation is used as the pressure expectation at the current moment.

6. The vulcanizing pressure control method of a vulcanizing machine according to claim 1, wherein: The correction of the current proportional coefficient includes: Correction value of the proportional coefficient at the current moment The expression is: Where, Indicates the preset scale factor; Indicates the urgency of pressure compensation of the vulcanizer at the current moment; norm( ) represents the normalization function.

7. The vulcanizing pressure control method of a vulcanizing machine according to claim 1, wherein: The controlling of the pressure of the vulcanizing machine 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, wherein the proportional coefficient correction value 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.

8. A vulcanizing pressure control system for a vulcanizing machine, 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, the steps of the vulcanizing pressure control method of a vulcanizing press as described in any one of claims 1 to 7 are implemented.

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