Tire vulcanization adjusting method and device

Abstract

The invention discloses a tire vulcanization adjusting method and device, and relates to the technical field of tire vulcanization, and the method comprises the following steps: obtaining an initial heating rate, an initial mold filling pressure and corresponding constraint conditions; randomly disturbing the initial heating rate and the initial mold filling pressure in a constraint condition range, and randomly combining to generate a plurality of control parameter sets; building a thermal-mechanical coupling simulation model of tire vulcanization, and respectively performing parallel simulation based on the control parameter sets to obtain thermal behavior data under each group of control parameter sets; acquiring the demand data of the tire to be vulcanized to distribute proportion weights to various characteristics in the thermal behavior data, and weighting to obtain a control parameter set evaluation index; and a screening display model is constructed according to the control parameter set evaluation index and the control parameter set, curved surface analysis is carried out, and an optimal control parameter set is screened out to regulate and control tire vulcanization, so that the problems of non-uniform vulcanization, high defect rate and energy efficiency waste are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of tire vulcanization, and more particularly to a tire vulcanization adjustment method and device. Background Art

[0002] The "vulcanization stage" of the tire manufacturing process is the last critical step in the entire production process, which directly determines the final performance of the tire, such as strength, elasticity, wear resistance and heat resistance.

[0003] Vulcanization refers to the process of subjecting unvulcanized raw rubber to the action of heat, pressure and time to form a cross-linked structure between rubber molecular chains, thereby giving the rubber excellent physical and mechanical properties.

[0004] The vulcanization process is the final and most critical step in the tire manufacturing process. Its purpose is to induce cross-linking reactions between rubber molecules through heating and pressurization, thereby imparting the desired elasticity, strength, and wear resistance to the tire. In practice, the tire blank is placed in a heated mold. An inflatable bladder applies pressure to hold the tire tightly against the mold cavity. Simultaneously, the mold is heated, rapidly raising the temperature to the vulcanization zone. After a set vulcanization time, the rubber transforms from a plastic state into a highly elastic three-dimensional network structure. Throughout this process, precise coordination of factors such as the heating rate, pressure profile, vulcanization time, and exhaust control ensures a clear tire tread, stable dimensions, and a dense structure, ultimately achieving finished product and finalized performance.

[0005] For example, the invention patent with the publication number CN117850235A discloses a data-driven learning control method for the temperature of a rubber mixing chamber, which includes the data-driven learning control method disclosed by the present invention and belongs to the field of rubber production. The present invention mainly addresses the challenges existing in the rubber mixing temperature process, such as different initial states, non-repetitive uncertainties, variable batch lengths, and the inability to obtain accurate models. The control scheme is as follows: establishing a thermodynamic model of the rubber mixing temperature process with actuator constraints; establishing an equivalent iterative linear data model along the batch direction; designing an iterative linear prediction model to compensate for output temperatures that do not reach the expected operating length; designing an iterative extended state observer to estimate different initial states and non-repetitive uncertainties; designing an iterative adaptive update law and an iterative learning control law for uncertainty compensation to achieve temperature regulation of the mixing process; the iterative learning temperature control method disclosed by the present invention comprehensively considers the above-mentioned challenging issues, has good temperature tracking accuracy and strong anti-interference ability, and meets the temperature control requirements of the rubber mixing process.

[0006] For example, the invention patent announcement with the publication number CN116184807A discloses a temperature control method and system for a steel rolling walking beam heating furnace, including the following: using an RBF neural network to online identify and obtain the sub-models of the heating furnace, the sub-models of the heating furnace, the sub-models of the heating furnace, the sub-models of the heating furnace, the sub-models of the heating furnace, the two-degree-of-freedom PID controller and the sub-model, and using a hybrid optimization algorithm module to tune the PID parameters of the two-degree-of-freedom PID controller to obtain the optimal solution, and controlling the sub-model through the optimal solution, thereby controlling the heating furnace temperature model to output the optimal temperature of each section. The present invention uses a hybrid optimization algorithm module to tune the parameters of the two-degree-of-freedom PID controller, sets a judgment criterion and implements a hybrid of the simulated annealing algorithm and the least squares method, combines the global optimization performance and efficient local optimization capabilities of the two to perform parameter tuning, so that the system can quickly track the target value and output stably, thereby improving the controller quality.

[0007] The above-disclosed technical solution has at least the following technical problems: During the tire vulcanization process, the matching relationship between the heating rate and the applied pressure plays a decisive role in the quality of the final product. If the heating rate is too fast, the rubber surface will be vulcanized prematurely to form a dense structure, which will hinder the internal heat conduction, resulting in "outside ripening and inside rawness", resulting in insufficient structural strength; while heating too slowly will extend the molding cycle, reduce production efficiency, and may lead to incomplete vulcanization. In terms of pressure, if it is applied too early or too high, it will make it difficult to discharge the residual gas in the mold cavity, resulting in defects such as bubbles, scorch or unclear patterns; conversely, if the pressure is too low or applied too late, it may cause the rubber to not fit tightly into the mold cavity, resulting in blurred pattern contours or rubber offset.

[0008] In the existing technology, fixed parameters are mostly used to control the pressure and heating rate, and there is a lack of a dynamic coordination mechanism for the tire structure and the mold cavity exhaust characteristics, which can easily lead to problems such as uneven vulcanization, high defect rate and energy waste. Summary of the Invention

[0009] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a tire vulcanization adjustment method and device, which solves the problems of uneven vulcanization, high defect rate and energy waste through coordinated adaptive analysis and control of heating rate and pressure.

[0010] To achieve the above object, the present invention provides the following technical solutions: A tire vulcanization adjustment method includes: obtaining an initial heating rate and an initial mold filling pressure and their corresponding constraints; randomly perturbing the initial heating rate and the initial mold filling pressure within the constraints to generate multiple parameter control parameter sets; performing parallel simulations based on each control parameter set to obtain corresponding thermal behavior data; assigning weights to characteristics of the thermal behavior data based on tire demand data, and performing weighted calculation to obtain evaluation indicators for each control parameter set; and performing surface analysis based on the control parameter sets and their evaluation indicators to select the optimal control parameter set for tire vulcanization control.

[0011] In the above scheme, the specific method for obtaining the initial heating rate is: based on the thermal balance requirements of the vulcanization startup stage, a thermal simulation model of the initial heating process of the rubber material is constructed, the mold cavity temperature distribution under different heating rates is simulated, and the uniformity of the temperature field at each moment is evaluated; under the constraints of equipment response speed and thermal stability of the rubber material, the heating rate with the maximum temperature field uniformity is selected as the initial heating rate.

[0012] In the above scheme, the method for obtaining the initial filling pressure is: constructing a non-Newtonian flow model of the rubber during the mold cavity filling process; simulating the flow and deformation behavior of the rubber under different filling pressures, and obtaining the stress distribution and strain rate distribution at the end of filling; calculating the stress distribution uniformity and strain rate gradient index; under the constraints of the rubber shear stability and equipment structure strength, selecting the filling pressure with the most uniform stress distribution and the lowest strain rate gradient as the initial filling pressure.

[0013] In the above scheme, the method for obtaining the constraint condition of the heating rate is: obtaining the maximum allowable heating rate of the vulcanization equipment; obtaining the maximum safe heating rate of the rubber during the heating process; taking the smaller value of the maximum allowable heating rate and the maximum safe heating rate as the heating rate constraint condition.

[0014] In the above scheme, the control parameter set also includes filling pressure. The constraint condition of the filling pressure is specifically obtained by: determining the first pressure upper limit based on the flow characteristics of the rubber; determining the second pressure upper limit based on the structural strength of the equipment; taking the smaller value of the first pressure upper limit and the second pressure upper limit as the filling pressure constraint condition.

[0015] In the above scheme, the parallel simulation based on each control parameter set is specifically as follows: constructing a two-dimensional simulation model of the tire cross-section and setting boundary conditions and material properties; inputting the heating rate as the thermal boundary change rate and the filling pressure as the boundary driving pressure; establishing a joint simulation model based on the thermal-mechanical-fluid multi-physics field coupling principle; and inputting multiple sets of control parameter sets containing different heating rates and filling pressures into the joint simulation model for simulation.

[0016] In the above scheme, the weights assigned to the characteristics of the thermal behavior data based on the tire demand data are specifically as follows: obtaining the temperature distribution data of the rubber material in the mold cavity; dividing the mold cavity into multiple temperature sensing areas and calculating the temperature statistics of each area, wherein the temperature statistics include the average temperature and standard deviation of each area; calculating the regional temperature difference coefficient based on the temperature statistics of each area; and taking a weighted average of the temperature difference coefficients of all areas to obtain a temperature distribution characteristic value that characterizes the uniformity of the overall temperature distribution.

[0017] In the above scheme, the temperature distribution data includes equivalent stress distribution characteristics, and the method for extracting the equivalent stress distribution characteristics is: based on the thermal-mechanical coupling non-Newtonian flow model, obtaining the equivalent stress distribution data of the rubber material in the mold cavity at the end of mold filling; dividing the mold cavity into multiple regions and calculating the average equivalent stress of each region; calculating the range of the average equivalent stress of each region, and using it as the equivalent stress distribution characteristic value characterizing the uniformity of stress distribution.

[0018] In the above scheme, the surface analysis based on the control parameter set and its evaluation index is performed to screen the optimal control parameter set for tire vulcanization control. Specifically, a two-dimensional parameter plane is constructed with the heating rate and the filling pressure as the coordinate axes; the evaluation index of each control parameter set is used as the height coordinate to construct a three-dimensional screening display model; the discrete points in the three-dimensional screening display model are fitted with a surface to extract the extreme points of the fitted surface; and the heating rate and filling pressure parameters corresponding to the extreme points are output as the optimal control set.

[0019] A device for a tire vulcanization adjustment method includes: an initial data acquisition module for acquiring an initial heating rate and an initial mold filling pressure and their corresponding constraints; a control parameter set generation module for randomly perturbing the initial heating rate and the initial mold filling pressure within the constraints to generate multiple control parameter sets; a behavior simulation module for performing parallel simulation based on each control parameter set to obtain corresponding thermal behavior data; an evaluation module for assigning weights to features of the thermal behavior data based on tire demand data and obtaining evaluation indicators for each control parameter set through weighted calculation; and a control module for performing surface analysis based on the control parameter set and its evaluation indicators to screen the optimal control parameter set for tire vulcanization regulation.

[0020] This invention optimizes the heating rate and mold filling pressure during the tire vulcanization process, ensuring uniformity of the temperature field and stability of the stress distribution, effectively improving the thermal balance of the rubber compound and the fluidity of the mold filling process. Furthermore, by combining the constraints of the equipment and the rubber compound, multiple control parameter sets are randomly generated and simulated in parallel, from which the optimal process parameter combination is selected, achieving precise control of the vulcanization process. This technology not only improves the efficiency and stability of the production process but also optimizes the quality of the tire vulcanization process, possessing high engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The present invention is a schematic flow chart of a tire vulcanization adjustment method.

[0022] Figure 2 The figure is a schematic structural diagram of a tire vulcanization adjustment device according to the present invention. DETAILED DESCRIPTION

[0023] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] Example 1, Figure 1 The present invention provides a tire vulcanization adjustment method, comprising the following steps: S1, obtain the initial heating rate and initial filling pressure and their corresponding constraints, specifically: Based on the thermal balance requirements during the vulcanization startup phase, a two-dimensional heat conduction model of the initial temperature rise process of the rubber compound was constructed to simulate the mold cavity temperature distribution at different heating rates and evaluate the uniformity of the temperature field at each moment. Under the premise of meeting the equipment response speed and thermal stability limits of the rubber compound, the heating rate with the largest uniformity of the temperature field is screened and determined as the initial heating rate; It should be noted that the two-dimensional heat conduction model for the initial temperature rise process of the rubber compound is constructed by setting the two-dimensional plane area of ​​the tire rubber compound cross section to construct the transient two-dimensional heat conduction equation; Assume that the boundary temperature increases linearly with the heating rate, and apply this boundary condition to the cavity contact boundary, while the other boundaries are adiabatic boundaries; The finite difference method is used to discretize time and space, and the two-dimensional temperature field distribution at different times is obtained. The standard deviation of the temperature field distribution at a certain target time is taken as the uniformity of the temperature field.

[0025] Among them, the feasible transient two-dimensional heat conduction equation is:

[0026] Where, is the density of the rubber compound, is the specific heat capacity, is the temperature distribution at position (x, y) and time t, is the thermal conductivity.

[0027] It should be noted that the boundary temperature is set to increase linearly with the heating rate, and this boundary condition is applied to the cavity contact boundary, while the other boundaries are set as adiabatic boundaries. The purpose is to accurately simulate the actual heat transfer path in the early stage of vulcanization during the simulation process. That is, the main heating behavior of the cavity on the rubber compound occurs only at the contact surface, and the process of heat conduction to the interior is subject to the thermal conductivity of the material itself, rather than the non-real heat conduction at other boundaries, thereby achieving a reasonable boundary closure of the heat conduction behavior. It also has the following advantages: The heating method of the mold cavity temperature control system is usually linear control, so the use of linear heating boundaries can accurately correspond to the process characteristics; the non-contact boundaries are set as adiabatic boundaries to effectively prevent non-physical heat dissipation on non-heating surfaces and improve the accuracy of temperature distribution simulation. The temperature field obtained under this setting is more representative, which helps to calculate the actual impact of the heating rate on the thermal equilibrium of the rubber material and provide highly reliable heat conduction simulation results for the optimization of the heating rate parameters.

[0028] It should be noted that to determine the temperature distribution during the initial curing temperature rise under specified boundary conditions, the finite difference method (FDM) is used to numerically solve the governing two-dimensional heat conduction equations. The time and space domains are discretized into a number of small units, and a system of discrete difference equations is constructed in either explicit or implicit format. Iterative calculations are performed under the constraints of initial and boundary conditions to gradually obtain the temperature distribution field corresponding to different time steps. This method can more intuitively reflect the temperature diffusion path and heat transfer trends within the cross-section of the rubber compound, and is suitable for modeling the dynamic response of varying heating rates to thermal equilibrium analysis. Due to the widespread application and mature algorithm of the FDM in heat conduction problems, the relevant details are not elaborated here.

[0029] S2, randomly perturbs the initial heating rate and initial filling pressure within the constraints to generate multiple parameter control parameter sets, including: S21: Determine the initial filling pressure based on the uniformity of the stress distribution and the flowable strain rate of the rubber compound; In this embodiment, the initial mold filling pressure is determined based on the uniformity of the stress distribution and the flowable strain rate of the rubber material, specifically: A non-Newtonian flow model of the rubber compound during the mold filling process was constructed. The boundary driving pressure under different filling pressure conditions was set, and the flow and deformation behavior of the rubber compound in the mold cavity were simulated using the fluid-structure coupling finite element method. Obtain the equivalent stress distribution diagram and equivalent strain rate distribution diagram of the rubber material at the end of mold filling under different pressure conditions; Calculate stress standard deviation and maximum strain rate gradient; Under the premise of satisfying the constraints of rubber shear stability and equipment structure strength, the pressure value with the smallest standard deviation of stress distribution and the lowest strain rate gradient is screened and determined as the initial mold filling pressure.

[0030] It should be noted that the rubber compound during the mold filling process usually exhibits non-Newtonian flow behavior, which can be characterized by the following Power-Law model:

[0031] Where, is the shear stress, is the flow consistency coefficient, is the shear rate, is the mobility index; The flow and deformation of the rubber compound are simulated using the fluid-solid coupling finite element method, which can be expressed as:

[0032] Where, is the fluid velocity, is the fluid pressure, is the dynamic viscosity of the fluid, is the external body force.

[0033] The maximum strain rate gradient can be expressed by the following formula: , Where, is the strain rate, and x and y are the coordinates of the equivalent strain rate distribution diagram.

[0034] Under the constraints of ensuring the shear stability of the rubber compound and the structural strength of the equipment, the stress standard deviation and maximum strain rate gradient under different pressure conditions were analyzed. The pressure value with the smallest stress distribution standard deviation and the lowest strain rate gradient was selected. Ultimately, this was determined as the initial mold filling pressure.

[0035] It should be noted that during the filling process, the boundary driving pressure of the mold cavity changes with time. The filling pressure simulates the flow and deformation behavior of the rubber material by gradually increasing the boundary driving pressure. The above conditions are set as the filling pressure boundary conditions.

[0036] It should be noted that the flow index determines the non-Newtonian properties of the fluid. When n is 1, it is a Newtonian fluid.

[0037] S22: Obtaining heating rate constraint conditions and filling pressure constraint conditions, and randomly perturbing the initial heating rate and initial filling pressure within the constraint range, and randomly combining them to generate several control parameter sets.

[0038] The control parameter set includes a mold filling pressure and a heating rate.

[0039] In this embodiment, the heating rate constraint conditions include equipment response speed constraint and rubber thermal stability constraint; wherein, the mold filling pressure constraint conditions include rubber shear stability constraint and equipment structural strength constraint; It should be noted that the method for obtaining the heating rate constraint is as follows: based on the test data of the heating element characteristics of the vulcanization equipment, the maximum temperature rise rate that the equipment can achieve is obtained as the upper limit of the equipment response speed; at the same time, based on the thermal stability test of the rubber compound, the highest safe heating rate that does not cause thermal degradation such as scorching and premature cross-linking during the heating process is determined, and the smaller value of the two is finally taken as the heating rate constraint.

[0040] in, is the upper limit of the heating rate, The upper limit of the device response speed, This is the highest safe heating rate.

[0041] It should be noted that the method for obtaining the filling pressure constraint condition is as follows: through the shear viscosity and strain rate relationship curve of the rubber material, combined with its non-Newtonian model parameters, the maximum safe shear rate of the rubber material without shear structural damage is determined, and the corresponding maximum filling pressure is reversed; secondly, based on the finite element mechanical simulation results of the mold cavity structure, the maximum structural pressure that the equipment can withstand under safe working conditions is determined.

[0042] Finally, the smaller value of the two is taken as the filling pressure constraint condition.

[0043] The initial heating rate and initial filling pressure are randomly perturbed within the constraints and randomly combined to generate several control parameter sets.

[0044] S3, performing parallel simulations based on each control parameter set to obtain corresponding thermal behavior data, specifically by constructing a thermal-mechanical-fluid coupled simulation model for tire vulcanization and performing parallel simulations based on each control parameter set to obtain thermal behavior data under each control parameter set; In this embodiment, a thermal-mechanical-fluid coupled simulation model of tire vulcanization is constructed, and parallel simulations are performed based on a set of control parameters, specifically: Build a 2D tire cross-section simulation model, set boundary conditions and material properties, input the heating rate as the thermal boundary change rate, and input the filling pressure as the boundary driving pressure; A heat conduction model is used to describe the temperature field changes of the rubber compound, and a fluid-solid coupling model is used to describe the non-Newtonian flow behavior and structural stress response of the rubber compound during the mold filling process. The influence of the thermal field on the viscosity of the rubber compound is introduced into the flow equation to achieve a joint simulation of the thermal, mechanical and fluid multi-physics fields. For each set of control parameters, a set of heating rates and filling pressures are input into the simulation model respectively, and parallel simulation calculations are performed to output the temperature field distribution, equivalent stress field distribution, and equivalent strain rate distribution results corresponding to each set of control parameters.

[0045] It should be noted that the thermal field has a significant impact on the viscosity of the rubber compound. An increase in temperature will cause the viscosity of the rubber compound to decrease, which in turn affects its fluidity and mold filling behavior. Therefore, when constructing a thermal-mechanical-fluid coupling model, temperature is introduced into the flow equation as a control variable for viscosity, so that the flow characteristics dynamically respond to temperature changes. Specifically, by establishing a temperature-viscosity relationship function (such as an Arrhenius-type exponential relationship or an empirical fitting relationship), the local temperature field results are applied to the non-Newtonian fluid viscosity model to achieve dynamic regulation of the thermal field on the force field and flow field, thereby completing the accurate simulation of the mutual coupling behavior of the thermal, mechanical, and fluid multi-physical fields during the entire vulcanization process. The following are feasible temperature-viscosity relationship expressions: , Where, is the viscosity of the rubber compound, is the initial viscosity at the reference temperature, is the activation energy, is the universal gas constant, is the local temperature field value.

[0046] This embodiment optimizes the heating rate and mold filling pressure during the tire vulcanization process through a precise thermal-mechanical-fluid coupling simulation model. Using a two-dimensional heat conduction model and the fluid-solid coupling finite element method, the uniformity of the temperature field and the stability of the stress distribution are ensured, effectively improving the thermal balance of the rubber compound and the fluidity of the mold filling process. Furthermore, by combining the constraints of the equipment and the rubber compound, multiple control parameter sets are randomly generated and simulated in parallel, from which the optimal process parameter combination is selected, achieving precise control of the vulcanization process. This technology not only improves the efficiency and stability of the production process but also optimizes the quality of the tire vulcanization process, possessing high engineering application value.

[0047] S4, assign weights to the characteristics of the thermal behavior data according to the tire demand data, and calculate the evaluation index of each control parameter set by weighted calculation, specifically: In this embodiment, the thermal behavior data includes temperature distribution characteristics, equivalent stress distribution characteristics, and equivalent strain rate characteristics; The temperature distribution characteristic refers to the temperature distribution of the rubber compound within the mold cavity over time during the tire vulcanization process. The temperature distribution characteristic can reflect the uniformity of the rubber compound's heating process, which in turn affects the vulcanization effect of the rubber compound and the ultimate performance of the tire. Specifically, the temperature distribution characteristic is typically evaluated by quantifying statistical quantities such as the standard deviation and maximum temperature difference of temperature values ​​at different locations within the mold cavity to assess temperature uniformity. A more uniform temperature distribution helps improve the consistency of the vulcanization process, reduce the risk of local overheating or uneven cooling, and thus enhance the structural stability and performance of the tire.

[0048] Analyzing temperature distribution characteristics has the following advantages for screening and evaluating control parameter sets to address the lack of a dynamic coordination mechanism for tire structure and mold cavity venting characteristics: Temperature distribution characteristics can help assess the heating uniformity of the rubber compound within the mold cavity. By accurately monitoring and optimizing temperature distribution, local overheating or excessive temperature differences can be avoided, minimizing performance variations or structural defects in the rubber compound caused by temperature non-uniformity. This improves thermal uniformity control and ultimately enhances overall tire quality.

[0049] Monitoring and optimizing temperature distribution helps regulate the gas discharge pattern within the mold cavity during vulcanization, reducing heat buildup and gas stagnation. By better coordinating gas discharge characteristics with temperature field changes and enhancing the coordination between cavity gas discharge and heat transfer, pressure fluctuations and uneven deformation caused by poor gas flow or uneven temperature can be avoided.

[0050] As the curing requirements of different tire types vary, changes in temperature distribution characteristics can serve as the basis for dynamically adjusting the control parameter set. By analyzing temperature distribution characteristics at different times and under different conditions, control parameters such as heating rate and filling pressure can be more precisely adjusted. This supports dynamic adjustment and optimization of the control parameter set to ensure the adaptability and efficiency of different tires during the curing process.

[0051] The optimized temperature distribution characteristics can effectively reduce the time waste and energy consumption in the vulcanization process, while ensuring the consistency of the vulcanization effect and reducing the negative impact of temperature fluctuations on the properties of the rubber compound, thereby improving production efficiency and the consistency of the final product.

[0052] In this embodiment, the specific method for obtaining the temperature distribution characteristics is as follows: Based on the constructed two-dimensional heat conduction model, the temperature distribution of the rubber compound in the tire mold cavity under different control conditions was simulated; Divide the temperature distribution into several sensing areas and average all temperature data in each sensing area; Calculate the standard deviation of the temperature values ​​in each sensing area, and divide the standard deviation of each sensing area by the average temperature of the corresponding sensing area to obtain the temperature difference coefficient; The difference coefficients of each sensing area are weighted averaged to obtain the temperature distribution characteristics, and the weight of the weighted average of the difference coefficients is the proportion of each area.

[0053] The equivalent stress distribution characteristic refers to the distribution of stress states experienced by the tire compound at different locations during the vulcanization process. By simulating the stress changes experienced by the compound within the mold cavity during the filling process, stress distribution maps can be generated for different regions (such as the tread and sidewall). This distribution map reflects the concentration or dispersion of stress in different parts of the tire and is a key indicator for evaluating the uniformity of stress experienced by the compound during vulcanization. The equivalent stress distribution characteristic effectively reveals the stress state of various regions of the compound during the molding process and is crucial for optimizing mold filling pressure and ensuring uniform tire structure.

[0054] Analyzing the equivalent stress distribution characteristics is crucial for selecting and evaluating control parameter sets to address the lack of a dynamic coordination mechanism between the tire structure and the mold cavity's venting characteristics. By analyzing the equivalent stress distribution, the stress state in different areas within the mold cavity can be assessed, ensuring uniform stress distribution during vulcanization, avoiding localized defects caused by stress concentration, and ultimately improving the tire's overall performance and service life.

[0055] In addition, the equivalent stress distribution characteristics can reveal the stress changes in different parts of the tire, helping to select the filling pressure and heating rate that can best maintain the stability of the tire structure in the control parameter set, thereby improving structural stability and avoiding tire deformation or cracks caused by uneven stress distribution.

[0056] Within the mold cavity, appropriate filling pressure and heating rate significantly influence the compound's fluidity and cavity venting. Analyzing the equivalent stress distribution characteristics effectively integrates cavity venting characteristics, ensuring dynamic coordination between gas emission and compound flow within the cavity, thereby improving production efficiency and product quality, and enhancing venting and structural coordination.

[0057] As a quantifiable indicator, the equivalent stress distribution characteristics can provide data support for screening the optimal control parameter set, ensuring that the selected control parameters (such as filling pressure and heating rate) can meet tire performance requirements while optimizing the thermal-mechanical-fluid coupling effect in the production process, providing a quantitative basis for control parameter screening.

[0058] In this embodiment, the specific method for obtaining the equivalent stress distribution characteristics is as follows: Construct a thermal-mechanical coupled non-Newtonian flow model for the rubber compound in the mold cavity, set a fixed initial heating rate and filling pressure, and simulate the flow and force behavior of the rubber compound during the entire filling process; At the end of mold filling, the equivalent stress value of each node of the rubber compound in the mold cavity is extracted to generate an equivalent stress distribution diagram; Based on the equivalent stress distribution diagram, the mold cavity is divided into areas, the average equivalent stress value of each area is calculated, and the difference between the maximum and minimum values ​​is taken as the equivalent stress distribution feature.

[0059] The equivalent strain rate feature characterizes the degree of flow activity in a localized area during mold filling. Higher values ​​indicate faster deformation and greater fluidity. By extracting the equivalent strain rate field at the end of mold filling within a thermal-mechanical-fluid coupled simulation model, high-gradient regions within the mold cavity are identified. The maximum equivalent strain rate gradient is then calculated, serving as a key metric for flow continuity and cavity filling stability. This feature helps identify potential areas of uneven filling or gas stagnation, improving the adaptability of control parameter sets and molding quality.

[0060] Analyzing the equivalent strain rate characteristics is crucial for screening and evaluating control parameter sets to address the lack of a dynamic coordination mechanism between tire structure and mold cavity venting characteristics. It can also intuitively reflect the flow continuity of the rubber compound within complex structural areas, identify possible areas of flow stagnation or dead corners, and provide a basis for optimizing venting paths and mold filling strategies. By analyzing the spatial distribution of the equivalent strain rate, the differences in filling rhythms in different areas of the mold cavity are revealed, facilitating the coordination of the matching relationship between tire structural details and mold cavity ventilation characteristics. Quantitative evaluation of simulation results for different control parameter sets in combination with strain rate characteristics helps to select the optimal combination of heating rate and filling pressure while ensuring flow balance and smooth exhaust, thereby improving the consistency and pass rate of vulcanization molding.

[0061] The specific method for extracting the equivalent strain rate characteristics of this embodiment is as follows: Construct a finite element model of the rubber flow during the mold cavity filling process, introduce non-Newtonian flow characteristics, and set the heating rate and filling pressure corresponding to the control parameter set as boundary input conditions; In the simulation of the mold filling process, the equivalent strain rate value at each node in the mold cavity at the end of the mold filling is extracted; Based on the global node data, the maximum gradient value of the equivalent strain rate is calculated to characterize the flow balance of the rubber material in the mold cavity; The maximum gradient value is taken as the equivalent strain rate characteristic.

[0062] In this embodiment, the demand data of the tire to be vulcanized is obtained and the weights of the various features in the thermal behavior data are assigned as follows: The demand data of tires to be vulcanized include Class A demand, Class B demand and Class C demand; According to the demand data of the tire to be vulcanized, the corresponding distribution weight is set based on experience, and the corresponding control parameter set evaluation index is obtained by weighting; It should be noted that Category A demands focus on temperature control accuracy and structural consistency, such as high-performance passenger car tires, with a focus on temperature uniformity and stress distribution; Category B demands require higher molding strength and rubber shear stability, such as off-road tires, with a focus on stress distribution and strain rate gradient; Category C demands emphasize structural safety and process stability, such as commercial heavy-duty tires, with balanced considerations and relatively equal weights allocated to each.

[0063] S5, performing surface analysis based on the control parameter set and its evaluation index to select the optimal control parameter set for tire vulcanization control, specifically: The control parameter set is used as the horizontal axis and the vertical axis to construct the base of the screening display model, and the output of the corresponding control parameter set evaluation index is used as the change to construct the screening display model; The points in the screening display model are fitted into a surface, and the control parameter set corresponding to the vertices of the surface is used as the optimal control parameter set to regulate tire vulcanization.

[0064] This application optimizes the regulation of temperature distribution, stress distribution, and strain rate characteristics during tire vulcanization by constructing a control parameter set evaluation index and weighting the features in the thermal behavior data in combination with tire demand data. Specifically, the temperature distribution characteristics help improve the heating uniformity of the rubber compound, avoid local overheating or excessive temperature differences, thereby improving the consistency of the vulcanization process and the structural stability of the tire. The stress distribution characteristics help optimize the filling pressure and heating rate, avoid stress concentration leading to local defects, and improve the overall performance and service life of the tire. The equivalent strain rate characteristics effectively identify uneven filling or gas stagnation areas, and optimize the stability of mold cavity filling. By adjusting the weighted weights of the control parameter set according to the demand data of different types of tires, dynamic adjustment of the control parameters is achieved, improving the adaptability, efficiency, and product consistency of the vulcanization process. In addition, through the screening display model and surface analysis technology, the optimal control parameter set can be accurately screened, further improving the accuracy and stability of tire vulcanization regulation.

[0065] The present invention optimizes the regulation of temperature distribution, stress distribution, and strain rate characteristics during the tire vulcanization process by constructing a control parameter set evaluation index and weighting the features in the thermal behavior data in combination with tire demand data. Specifically, the temperature distribution characteristics help improve the heating uniformity of the rubber compound, avoid local overheating or excessive temperature differences, thereby improving the consistency of the vulcanization process and the structural stability of the tire. The stress distribution characteristics help optimize the filling pressure and heating rate, avoid local defects caused by stress concentration, and improve the overall performance and service life of the tire. The equivalent strain rate characteristics effectively identify uneven filling or gas stagnation areas, and optimize the stability of mold cavity filling. By adjusting the weighted weights of the control parameter set according to the demand data of different types of tires, dynamic adjustment of the control parameters is achieved, improving the adaptability, efficiency, and product consistency of the vulcanization process. In addition, through the screening display model and surface analysis technology, the optimal control parameter set can be accurately screened, further improving the accuracy and stability of tire vulcanization regulation.

[0066] Example 2, Figure 2 A tire vulcanization adjustment device is provided, which includes an initial data acquisition module, a control parameter set generation module, a behavior simulation module, and a control module: Initial data acquisition module, used to obtain the initial heating rate and initial filling pressure as well as corresponding constraints; A control parameter set generation module is used to randomly perturb the initial heating rate and initial filling pressure within the constraint conditions, and randomly combine them to generate several control parameter sets; The behavior simulation module is used to build a thermal-mechanical coupling simulation model for tire vulcanization and conduct parallel simulations based on the control parameter sets to obtain the thermal behavior data under each set of control parameters; An evaluation module is used to obtain the demand data of the tire to be vulcanized and assign proportional weights to various features in the thermal behavior data, and obtain the evaluation index of the control parameter set by weighting; The control module is used to construct a screening display model based on the control parameter set evaluation index and the control parameter set, and perform surface analysis to screen out the optimal control parameter set for tire vulcanization regulation.

[0067] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0068] Those skilled in the art will clearly understand that for the sake of convenience and brevity in description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0069] In the embodiments provided in the present disclosure, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the systems, methods, and computer program products according to the various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a portion of code, and the above-mentioned module, program segment, or a portion of code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified functions or actions, or can be implemented using a combination of dedicated hardware and computer instructions.

[0070] It should be noted that, in this disclosure, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element limited by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0071] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A tire vulcanization adjustment method, characterized in that: include: Obtain the initial heating rate and initial filling pressure and their corresponding constraints; Randomly perturb the initial heating rate and initial filling pressure within the constraints to generate multiple parameter control parameter sets; Based on parallel simulation of each control parameter set, the corresponding thermal behavior data is obtained; Assign weights to the characteristics of thermal behavior data based on tire demand data, and use weighted calculation to obtain evaluation indicators for each control parameter set; Surface analysis is performed based on the control parameter set and its evaluation indicators to screen the optimal control parameter set for tire vulcanization control.

2. The tire vulcanization adjustment method according to claim 1, characterized in that: The specific method for obtaining the initial heating rate is: Based on the thermal balance requirements during the vulcanization startup phase, a thermal simulation model of the initial temperature rise process of the rubber compound was constructed to simulate the mold cavity temperature distribution at different heating rates and evaluate the uniformity of the temperature field at each moment. Under the constraints of equipment response speed and thermal stability of rubber, the heating rate with the maximum temperature field uniformity is selected as the initial heating rate.

3. The tire vulcanization adjustment method according to claim 2, characterized in that: The method for obtaining the initial filling pressure is: Construct a non-Newtonian flow model of the rubber compound during the mold cavity filling process; Simulate the flow and deformation behavior of the rubber material under different filling pressures to obtain the stress distribution and strain rate distribution at the end of filling; Calculate stress distribution uniformity and strain rate gradient indicators; Under the constraints of rubber shear stability and equipment structure strength, the filling pressure with the most uniform stress distribution and the lowest strain rate gradient is selected as the initial filling pressure.

4. The tire vulcanization adjustment method according to claim 3, characterized in that: The control parameter set includes a heating rate; the method for obtaining the constraint condition of the heating rate is: Obtain the maximum allowable heating rate of the vulcanization equipment; Obtain the highest safe heating rate of the rubber during the heating process; The smaller value of the maximum allowable heating rate and the maximum safe heating rate is taken as the heating rate constraint condition.

5. The tire vulcanization adjustment method according to claim 4, characterized in that: The control parameter set also includes the filling pressure, and the constraint condition of the filling pressure is obtained in the following way: determining a first upper pressure limit based on the flow characteristics of the rubber material; determining a second upper pressure limit based on the structural strength of the equipment; The smaller value between the first upper pressure limit and the second upper pressure limit is taken as the filling pressure constraint condition.

6. The tire vulcanization adjustment method according to claim 5, characterized in that: The parallel simulation based on each control parameter set is specifically as follows: Build a 2D simulation model of the tire cross section and set boundary conditions and material properties; The heating rate is input as the thermal boundary change rate, and the filling pressure is input as the boundary driving pressure; Establish a joint simulation model based on the principle of thermal-mechanical-fluid multi-physics field coupling; Multiple sets of control parameter sets including different heating rates and filling pressures are respectively input into the joint simulation model for simulation.

7. The tire vulcanization adjustment method according to claim 6, characterized in that: The weights assigned to the features of the thermal behavior data according to the tire demand data are specifically: Obtain temperature distribution data of the rubber compound in the mold cavity; The mold cavity is divided into multiple temperature sensing areas and the temperature statistics of each area are calculated, including the average temperature and standard deviation of each area. The regional temperature difference coefficient is calculated based on the temperature statistics of each area. The temperature difference coefficients of all areas are weighted averaged to obtain the temperature distribution characteristic value that characterizes the uniformity of the overall temperature distribution.

8. The tire vulcanization adjustment method according to claim 7, characterized in that: The temperature distribution data includes equivalent stress distribution characteristics, and the method for extracting the equivalent stress distribution characteristics is: Based on the thermal-mechanical coupling non-Newtonian flow model, the equivalent stress distribution data of the rubber material in the mold cavity at the end of mold filling is obtained; Divide the mold cavity into multiple areas and calculate the average equivalent stress of each area; The range of the average value of the equivalent stress in each region is calculated and used as the characteristic value of the equivalent stress distribution to characterize the uniformity of the stress distribution.

9. The tire vulcanization adjustment method according to claim 8, characterized in that: The surface analysis is performed based on the control parameter set and its evaluation index to screen the optimal control parameter set for tire vulcanization control, specifically: A two-dimensional parameter plane is constructed with the heating rate and filling pressure as coordinate axes; The evaluation index of each control parameter set is used as the height coordinate to construct a three-dimensional screening display model; Perform surface fitting on discrete points in the three-dimensional screening display model and extract the extreme points of the fitting surface; The heating rate and filling pressure parameters corresponding to the extreme points are output as the optimal control set.

10. A device using the tire vulcanization adjustment method according to any one of claims 1 to 9, characterized in that: Initial data acquisition module, used to obtain the initial heating rate and initial filling pressure and their corresponding constraints; A control parameter set generation module is used to randomly perturb the initial heating rate and the initial filling pressure within the constraint conditions to generate multiple parameter control parameter sets; Behavior simulation module, used for parallel simulation based on various control parameter sets to obtain corresponding thermal behavior data; An evaluation module is used to assign weights to the characteristics of thermal behavior data based on tire demand data, and to obtain evaluation indicators for each control parameter set through weighted calculation; The control module is used to perform surface analysis based on the control parameter set and its evaluation index, and screen the optimal control parameter set for tire vulcanization control.

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